5SSG2060_Practical_2_Processing spatial data_Answers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# This Week’s Overview\n",
    "\n",
    "\n",
    "You will further developing you skills of data handling and processing in this practical by finishing 10 small tasks about:\n",
    "\n",
    "- Working with streaming data. You will load weather data through API. It is harder conceptually because API data is harder to understand -- we've simplified it quite a bit but it's still got some parts that are going to be hard going.\n",
    "- Making an interactive map using skills learned last week.\n",
    "- Converting queried API data into a well-formatted DataFrame. Some DataFrame operation such as 'join','append',’merge’ you learned in last term will be used.\n",
    "- Create a ShapeFile using Shapely and GeoPandas - get a sense of projected and geographic coordinate system.\n",
    "- Calculating distance between points."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Learning Outcomes\n",
    "\n",
    "By the end of this practical you should have:\n",
    "- Used API to request streaming data\n",
    "- Enhanced your skills of manipulating data frame \n",
    "- Known calculate geographical distance in various ways"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(always remember) The first thing we need to do is setup our working environment. Run the scripts below to import the relevant libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7.0\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import folium  \n",
    "import os\n",
    "\n",
    "print (folium.__version__)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "pd.set_option('display.max_rows', 300) # specifies number of rows to show\n",
    "pd.options.display.float_format = '{:5,.4f}'.format # specifies default number format to 4 decimal places\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Weather Data  - background knowledge you should know\n",
    "\n",
    "The UK's Met Office is a world-leading weather and climate research centre, and even if it doesn't always seem like their forecasts are very accurate that's because Britain's weather is inherently _unpredictable_. They've also done a lot of work to make their weather data widely available to people like us.\n",
    "\n",
    "I probably don't need to say a _lot_ about weather data because you've probably been making use of forecasts for much of your life! But it's _still_ worth understanding something about how weather data is gathered and reported: many organisations operate weather stations where data on wind speed, temperature, rain, and amount of sun are collected and then transmitted to a server to be integrated into a larger data set of weather _observations_ at a national or global scale. Of course, any _one_ station might be in the 'wrong' place (somewhere shady or protected from the rain) or it might even break down, but the idea is that if you have enough of them you can collect a pretty good range of data for the country and begin to look for patterns and, potentially, make predictions.\n",
    "\n",
    "We will be accessing data from the MetOffice from weather stations where observations, such as the ones below, are collected:\n",
    "* <Param name=\"F\" units=\"C\">Feels Like Temperature (units: degrees Celsius)\n",
    "* <Param name=\"G\" units=\"mph\">Wind Gust (units: mph)</Param>\n",
    "* <Param name=\"H\" units=\"%\">Screen Relative Humidity (units: percent)</Param> \n",
    "* <Param name=\"T\" units=\"C\">Temperature (units: degrees Celsius)</Param> \n",
    "* <Param name=\"V\" units=\"\">Visibility (units: km?)</Param> \n",
    "* <Param name=\"D\" units=\"compass\">Wind Direction (units: compass degrees)</Param>  \n",
    "* <Param name=\"S\" units=\"mph\">Wind Speed (units: mph)</Param> \n",
    "* <Param name=\"U\" units=\"\">Max UV Index (units: index value)</Param> \n",
    "* <Param name=\"W\" units=\"\">Weather Type (units: categorical)</Param> \n",
    "* <Param name=\"Pp\" units=\"%\">Precipitation Probability (units: percent)</Param>\n",
    "\n",
    "These observations are associated with a particular station (where did we see these values/where _will_ we see these values?), they will also be associated with _either_ a particular time in the past (when were they collected?) or, if they're forecasts, with a particular time in the future (when do we expect to see them?). \n",
    "\n",
    "So although weather data might seem more 'objective' than data on social class (though for obvious reasons it turns out that both are just attempts to capture data about reality, not reality itself), it may also turn out to be very complex to store and manage beccause of the temporal element _and_ the fact that it's not just a count of one thing, each of these observations uses a very different set of units.\n",
    "\n",
    "To really get to grips with the MetOffice API you will need to RTM (Read The Manual): http://www.metoffice.gov.uk/media/pdf/3/0/DataPoint_API_reference.pdf. The ruder version of that, which you will sometimes see on StackOverflow and elsewhere, is: RTFM."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting Weather Data via an API\n",
    "\n",
    "Because the weather is changing all the time, so is the data! And, 'worse', it's becoming obsolete: the forecast from 2 years ago isn't particularly useful to us now. *And* asking for \"yesterday's weather\" depends on the day that we're asking! When you have data that is always changing from minute to minute or day to day then you use an API (Application Programming Interface) to access it: the API knows that \"yesterday's weather\" means \"work out what day it is right now and then get the weather from the day before\", and it also knows that \"give me the current weather from station X\" means \"look up station X and find the latest weather report that I've received\". In other words, an API is  designed with programmatic, dynamic interaction in mind right from the start.\n",
    "\n",
    "#### So What _is_ an API?\n",
    "\n",
    "There's a nice, friendly introduction to APIs over at [Free Code Camp](https://medium.freecodecamp.com/what-is-an-api-in-english-please-b880a3214a82#.rmjnli2nn). \n",
    "\n",
    "Helpfully, the MetOffice provides a lot of documentation about their API (I'd suggest bookmarking it): http://www.metoffice.gov.uk/datapoint/support/api-reference\n",
    "\n",
    "This type of data requires a lot more research up front to work with, but it's very flexible once you know how to 'speak API' because you can _customise_ the API request so that the server responds with _only_ the data we're interested in instead of being 'stuck' with what the provider wants to give us.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Task 1: Obtaining an API Key\n",
    "\n",
    "The first step to working with the API from the MetOffice is to obtain an API key: [Click to register and obtain the API Key here](http://www.metoffice.gov.uk/datapoint/API). \n",
    "\n",
    "Make a note of this key in your notebook. Right here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "api_key   = \"75038866-617b-4f32-b7a1-2af56d36fe63\" # your API key"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That way your API key is saved somewhere easy to access.\n",
    "\n",
    "We _always_ have to use the key as part of an API request: the process by which we _ask_ for data. Think of the key as being _your_ unique identifier: no two people share the same key and that way the MetOffice can cut off people who abuse the system or look at which APIs are popular with lots of users... **Twitter and Facebook do the same thing.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 2: Obtaining a List of Sites from the API\n",
    "\n",
    "How to start? Well, the first thing that we need to know is: for what locations can I get weather data? For this to work, we need to know how to ask the API nicely for a list of available sites... "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we import two new modules: one that makes requests to a web server, and one that will parse JSON* responses from the server in order to turn them into something that we can work with more easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json, requests # Libraries we need"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we set up some default variables (api_url, site_url) that will help us to build our request to the MetOffice's server. The comments help us to remember what each of these variables holds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "api_url  = \"http://datapoint.metoffice.gov.uk/public/data/\" # base URL\n",
    "site_url = \"val/wxobs/all/json/sitelist\" # sites API URL\n",
    "payload = {'key': api_key} # Dictionary to hold request parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You'll notice that the payload is just a dictionary and that this dictionary is then passed to the requests library (the get function). All it does it convert this dictionary to a key-value pair in the format expected by the API. Think of it as a kind of translation between languages: from the language of Python to the language of the web (HTTP, to be precise).\n",
    "We issue our request and it returns a response that we store in s (short for sites data)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = requests.get(api_url + site_url, params=payload) # Do the request"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lastly, we ask the response object to convert the reply into a JSON data structure... more on JSON in a second, but first let's look at what we got from our request!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "sites = s.json() # Capture the output\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://datapoint.metoffice.gov.uk/public/data/val/wxobs/all/json/sitelist?key=75038866-617b-4f32-b7a1-2af56d36fe63\n"
     ]
    }
   ],
   "source": [
    "# Show the requested URL\n",
    "print(s.url) # Click on the link below to see it nicely formatted automatically!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Locations': {'Location': [{'elevation': '7.0', 'id': '3066', 'latitude': '57.6494', 'longitude': '-3.5606', 'name': 'Kinloss', 'region': 'gr', 'unitaryAuthArea': 'Moray'}, {'elevation': '6.0', 'id': '3068', 'latitude': '57.712', 'longitude': '-3.322', 'obsSource': 'LNDSYN', 'name': 'Lossiemouth', 'region': 'gr', 'unitaryAuthArea': 'Moray'}, {'elevation': '36.0', 'id': '3075', 'latitude': '58.454', 'longitude': '-3.089', 'obsSource': 'LNDSYN', 'name': 'Wick John O Groats Airport', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '15.0', 'id': '3002', 'latitude': '60.749', 'longitude': '-0.854', 'name': 'Baltasound', 'region': 'os', 'unitaryAuthArea': 'Shetland Islands'}, {'elevation': '82.0', 'id': '3005', 'latitude': '60.139', 'longitude': '-1.183', 'obsSource': 'LNDSYN', 'name': 'Lerwick (S. Screen)', 'region': 'os', 'unitaryAuthArea': 'Shetland Islands'}, {'elevation': '57.0', 'id': '3008', 'latitude': '59.527', 'longitude': '-1.628', 'name': 'Fair Isle', 'region': 'os', 'unitaryAuthArea': 'Shetland Islands'}, {'elevation': '22.0', 'id': '3014', 'latitude': '60.111', 'longitude': '-2.063', 'obsSource': 'LNDSYN', 'name': 'Foula', 'region': 'os', 'unitaryAuthArea': 'Shetland Islands'}, {'elevation': '11.0', 'id': '3034', 'latitude': '57.859', 'longitude': '-5.636', 'name': 'Aultbea', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '18.0', 'id': '3037', 'latitude': '57.257', 'longitude': '-5.809', 'obsSource': 'LNDSYN', 'name': 'Skye/Lusa', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '81.0', 'id': '3044', 'latitude': '58.288', 'longitude': '-4.442', 'name': 'Altnaharra Saws', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '237.0', 'id': '3047', 'latitude': '56.867', 'longitude': '-4.708', 'name': 'Tulloch Bridge', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '117.0', 'id': '3796', 'latitude': '51.133', 'longitude': '1.348', 'name': 'Langdon Bay', 'region': 'se', 'unitaryAuthArea': 'Kent'}, {'elevation': '31.0', 'id': '3803', 'latitude': '49.913', 'longitude': '-6.301', 'name': 'Scilly St Marys', 'region': 'sw', 'unitaryAuthArea': 'Isles of Scilly'}, {'elevation': '200.0', 'id': '3823', 'latitude': '50.502', 'longitude': '-4.667', 'name': 'Cardinham', 'region': 'sw', 'unitaryAuthArea': 'Cornwall'}, {'elevation': '52.0', 'id': '3857', 'latitude': '50.522', 'longitude': '-2.454', 'name': 'Isle Of Portland', 'region': 'sw', 'unitaryAuthArea': 'Dorset'}, {'elevation': '13.0', 'id': '3876', 'latitude': '50.836', 'longitude': '-0.292', 'name': 'Shoreham', 'region': 'se', 'unitaryAuthArea': 'West Sussex'}, {'elevation': '84.0', 'id': '3895', 'latitude': '49.2079', 'longitude': '-2.1955', 'obsSource': 'LNDSYN', 'name': 'Jersey', 'region': 'sw', 'unitaryAuthArea': 'Jersey'}, {'elevation': '225.0', 'id': '3911', 'latitude': '54.721', 'longitude': '-6.814', 'name': 'Lough Fea', 'region': 'ni', 'unitaryAuthArea': 'County Londonderry'}, {'elevation': '156.0', 'id': '3916', 'latitude': '55.181', 'longitude': '-6.153', 'name': 'Ballypatrick Forest', 'region': 'ni', 'unitaryAuthArea': 'County Antrim'}, {'elevation': '25.0', 'id': '3953', 'latitude': '51.933', 'longitude': '-10.25', 'obsSource': 'LNDSYN', 'name': 'Valentia Observatory'}, {'elevation': '177.0', 'id': '99081', 'latitude': '50.767', 'longitude': '-3.9', 'name': 'North Wyke', 'region': 'sw', 'unitaryAuthArea': 'Devon'}, {'elevation': '99.0', 'id': '3520', 'latitude': '52.242', 'longitude': '-2.885', 'name': 'Shobdon Saws', 'region': 'wm', 'unitaryAuthArea': 'Herefordshire'}, {'elevation': '75.0', 'id': '3522', 'latitude': '52.083', 'longitude': '-2.8', 'name': 'Hereford', 'region': 'wm', 'unitaryAuthArea': 'Herefordshire'}, {'elevation': '96.0', 'id': '3535', 'latitude': '52.48', 'longitude': '-1.689', 'name': 'Coleshill', 'region': 'wm', 'unitaryAuthArea': 'Warwickshire'}, {'elevation': '85.0', 'id': '3560', 'latitude': '52.225', 'longitude': '-0.464', 'name': 'Bedford', 'region': 'ee', 'unitaryAuthArea': 'Bedford'}, {'elevation': '3.0', 'id': '3605', 'latitude': '51.713', 'longitude': '-4.368', 'name': 'Pembrey Sands', 'region': 'wl', 'unitaryAuthArea': 'Carmarthenshire'}, {'elevation': '210.0', 'id': '3647', 'latitude': '51.86', 'longitude': '-1.692', 'name': 'Little Rissington (Esaws)', 'region': 'sw', 'unitaryAuthArea': 'Gloucestershire'}, {'elevation': '204.0', 'id': '3660', 'latitude': '51.68', 'longitude': '-0.802', 'name': 'High Wycombe', 'region': 'se', 'unitaryAuthArea': 'Buckinghamshire'}, {'elevation': '87.0', 'id': '3684', 'latitude': '51.896', 'longitude': '0.453', 'name': 'Andrewsfield', 'region': 'ee', 'unitaryAuthArea': 'Essex'}, {'elevation': '49.0', 'id': '3716', 'latitude': '51.405', 'longitude': '-3.44', 'name': 'St-Athan', 'region': 'wl', 'unitaryAuthArea': 'Vale of Glamorgan'}, {'elevation': '145.0', 'id': '3740', 'latitude': '51.5031', 'longitude': '-1.9924', 'name': 'Lyneham', 'region': 'sw', 'unitaryAuthArea': 'Wiltshire'}, {'elevation': '72.0', 'id': '3768', 'latitude': '51.279', 'longitude': '-0.772', 'name': 'Farnborough', 'region': 'se', 'unitaryAuthArea': 'Hampshire'}, {'elevation': '113.0', 'id': '3153', 'latitude': '54.803', 'longitude': '-4.008', 'name': 'Dundrennan', 'region': 'dg', 'unitaryAuthArea': 'Dumfries and Galloway'}, {'elevation': '245.0', 'id': '3155', 'latitude': '55.627', 'longitude': '-3.735', 'name': 'Drumalbin', 'region': 'st', 'unitaryAuthArea': 'South Lanarkshire'}, {'elevation': '242.0', 'id': '3162', 'latitude': '55.311', 'longitude': '-3.206', 'name': 'Eskdalemuir', 'region': 'dg', 'unitaryAuthArea': 'Dumfries and Galloway'}, {'elevation': '57.0', 'id': '3166', 'latitude': '55.928', 'longitude': '-3.343', 'name': 'Edinburgh/Gogarbank', 'region': 'dg', 'unitaryAuthArea': 'Edinburgh'}, {'elevation': '227.0', 'id': '3226', 'latitude': '54.572', 'longitude': '-2.413', 'name': 'Warcop', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '211.0', 'id': '3230', 'latitude': '55.285', 'longitude': '-2.279', 'name': 'Redesdale Camp', 'nationalPark': 'Northumberland National Park', 'region': 'ne', 'unitaryAuthArea': 'Northumberland'}, {'elevation': '146.0', 'id': '3238', 'latitude': '55.02', 'longitude': '-1.88', 'name': 'Albemarle', 'region': 'ne', 'unitaryAuthArea': 'Northumberland'}, {'elevation': '32.0', 'id': '3257', 'latitude': '54.296', 'longitude': '-1.53', 'name': 'Leeming', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '33.0', 'id': '3261', 'latitude': '54.134', 'longitude': '-1.414', 'name': 'Dishforth Airfield', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '14.0', 'id': '3266', 'latitude': '54.045', 'longitude': '-1.25', 'name': 'Linton On Ouse', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '73.0', 'id': '3462', 'latitude': '52.6111', 'longitude': '-0.459', 'name': 'Wittering', 'region': 'ee', 'unitaryAuthArea': 'Peterborough'}, {'elevation': '21.0', 'id': '3482', 'latitude': '52.651', 'longitude': '0.569', 'name': 'Marham', 'region': 'ee', 'unitaryAuthArea': 'Norfolk'}, {'elevation': '6.0', 'id': '3907', 'latitude': '55.1604', 'longitude': '-6.9492', 'name': 'Magilligan', 'region': 'ni', 'unitaryAuthArea': 'County Londonderry'}, {'elevation': '228.0', 'id': '3063', 'latitude': '57.206', 'longitude': '-3.827', 'name': 'Aviemore', 'nationalPark': 'Cairngorms National Park', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '9.0', 'id': '3100', 'latitude': '56.497', 'longitude': '-6.887', 'obsSource': 'LNDSYN', 'name': 'Tiree', 'region': 'st', 'unitaryAuthArea': 'Argyll and Bute'}, {'elevation': '78.0', 'id': '3809', 'latitude': '50.085', 'longitude': '-5.257', 'obsSource': 'LNDSYN', 'name': 'Culdrose', 'region': 'sw', 'unitaryAuthArea': 'Cornwall'}, {'elevation': '252.0', 'id': '3840', 'latitude': '50.86', 'longitude': '-3.239', 'name': 'Dunkeswell Aerodrome', 'region': 'sw', 'unitaryAuthArea': 'Devon'}, {'elevation': '10.0', 'id': '3862', 'latitude': '50.779', 'longitude': '-1.835', 'obsSource': 'LNDSYN', 'name': 'Bournemouth Airport', 'region': 'sw', 'unitaryAuthArea': 'Dorset'}, {'elevation': '9.0', 'id': '3976', 'latitude': '54.233', 'longitude': '-10.001', 'obsSource': 'LNDSYN', 'name': 'Belmullet'}, {'elevation': '348.0', 'id': '3710', 'latitude': '51.087', 'longitude': '-3.608', 'name': 'Liscombe', 'nationalPark': 'Exmoor National Park', 'region': 'sw', 'unitaryAuthArea': 'Somerset'}, {'elevation': '132.0', 'id': '3743', 'latitude': '51.201', 'longitude': '-1.805', 'name': 'Larkhill', 'region': 'sw', 'unitaryAuthArea': 'Wiltshire'}, {'elevation': '126.0', 'id': '3746', 'latitude': '51.161', 'longitude': '-1.754', 'name': 'Boscombe Down', 'region': 'sw', 'unitaryAuthArea': 'Wiltshire'}, {'elevation': '67.0', 'id': '3769', 'latitude': '51.15', 'longitude': '-0.2333', 'name': 'Charlwood', 'region': 'se', 'unitaryAuthArea': 'Surrey'}, {'elevation': '10.0', 'id': '3171', 'latitude': '56.377', 'longitude': '-2.862', 'obsSource': 'LNDSYN', 'name': 'Leuchars', 'region': 'ta', 'unitaryAuthArea': 'Fife'}, {'elevation': '262.0', 'id': '3281', 'latitude': '54.362', 'longitude': '-0.673', 'name': 'Fylingdales', 'nationalPark': 'North York Moors National Park', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '10.0', 'id': '3302', 'latitude': '53.252', 'longitude': '-4.537', 'obsSource': 'LNDSYN', 'name': 'Valley', 'region': 'wl', 'unitaryAuthArea': 'Isle of Anglesey'}, {'elevation': '262.0', 'id': '3344', 'latitude': '53.811', 'longitude': '-1.865', 'name': 'Bingley Samos', 'region': 'yh', 'unitaryAuthArea': 'West Yorkshire'}, {'elevation': '62.0', 'id': '3379', 'latitude': '53.031', 'longitude': '-0.502', 'name': 'Cranwell', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '3.0', 'id': '3392', 'latitude': '53.088', 'longitude': '0.274', 'name': 'Wainfleet', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '72.0', 'id': '3414', 'latitude': '52.794', 'longitude': '-2.663', 'name': 'Shawbury', 'region': 'wm', 'unitaryAuthArea': 'Shropshire'}, {'elevation': '1245.0', 'id': '3065', 'latitude': '57.116', 'longitude': '-3.642', 'name': 'Cairn Gorm Summit', 'nationalPark': 'Cairngorms National Park', 'region': 'he', 'unitaryAuthArea': 'Moray'}, {'elevation': '933.0', 'id': '3072', 'latitude': '56.879', 'longitude': '-3.42', 'name': 'Cairnwell', 'nationalPark': 'Cairngorms National Park', 'region': 'ta', 'unitaryAuthArea': 'Perth and Kinross'}, {'elevation': '65.0', 'id': '3091', 'latitude': '57.206', 'longitude': '-2.202', 'obsSource': 'LNDSYN', 'name': 'Aberdeen Airport', 'region': 'gr', 'unitaryAuthArea': 'Aberdeen'}, {'elevation': '17.0', 'id': '3105', 'latitude': '55.681', 'longitude': '-6.256', 'obsSource': 'LNDSYN', 'name': 'Islay Airport', 'region': 'st', 'unitaryAuthArea': 'Argyll and Bute'}, {'elevation': '12.0', 'id': '3010', 'latitude': '59.083', 'longitude': '-4.404', 'obsSource': 'LNDSYN', 'name': 'Sule Skerry', 'region': 'os', 'unitaryAuthArea': 'Highland'}, {'elevation': '20.0', 'id': '3853', 'latitude': '51.006', 'longitude': '-2.64', 'name': 'Yeovilton', 'region': 'sw', 'unitaryAuthArea': 'Somerset'}, {'elevation': '20.0', 'id': '3980', 'latitude': '55.366', 'longitude': '-7.333', 'obsSource': 'LNDSYN', 'name': 'Malin Head'}, {'elevation': '89.0', 'id': '99057', 'latitude': '52.017', 'longitude': '-0.6', 'name': 'Woburn', 'region': 'ee', 'unitaryAuthArea': 'Central Bedfordshire'}, {'elevation': '35.0', 'id': '3529', 'latitude': '52.148', 'longitude': '-2.04', 'name': 'Pershore', 'region': 'wm', 'unitaryAuthArea': 'Worcestershire'}, {'elevation': '44.0', 'id': '3604', 'latitude': '51.708', 'longitude': '-5.055', 'name': 'Milford Haven C.B.', 'region': 'wl', 'unitaryAuthArea': 'Pembrokeshire'}, {'elevation': '59.0', 'id': '3628', 'latitude': '51.521', 'longitude': '-2.576', 'name': 'Filton', 'region': 'sw', 'unitaryAuthArea': 'South Gloucestershire'}, {'elevation': '2.0', 'id': '3693', 'latitude': '51.554', 'longitude': '0.83', 'obsSource': 'LNDSYN', 'name': 'Shoeburyness', 'region': 'ee', 'unitaryAuthArea': 'Essex'}, {'elevation': '91.0', 'id': '3749', 'latitude': '51.149', 'longitude': '-1.57', 'name': 'Middle Wallop', 'region': 'se', 'unitaryAuthArea': 'Hampshire'}, {'elevation': '118.0', 'id': '3761', 'latitude': '51.238', 'longitude': '-0.944', 'name': 'Odiham', 'region': 'se', 'unitaryAuthArea': 'Hampshire'}, {'elevation': '11.0', 'id': '3132', 'latitude': '54.859', 'longitude': '-4.936', 'name': 'West Freugh', 'region': 'dg', 'unitaryAuthArea': 'Dumfries and Galloway'}, {'elevation': '27.0', 'id': '3136', 'latitude': '55.515', 'longitude': '-4.585', 'name': 'Prestwick Rnas', 'region': 'st', 'unitaryAuthArea': 'South Ayrshire'}, {'elevation': '112.0', 'id': '3158', 'latitude': '55.709', 'longitude': '-2.383', 'name': 'Charterhall', 'region': 'dg', 'unitaryAuthArea': 'Scottish Borders'}, {'elevation': '124.0', 'id': '3210', 'latitude': '54.5181', 'longitude': '-3.615', 'obsSource': 'LNDSYN', 'name': 'St. Bees Head', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '81.0', 'id': '3212', 'latitude': '54.614', 'longitude': '-3.157', 'name': 'Keswick', 'nationalPark': 'Lake District National Park', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '28.0', 'id': '3220', 'latitude': '54.933', 'longitude': '-2.963', 'name': 'Carlisle', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '285.0', 'id': '3224', 'latitude': '55.05', 'longitude': '-2.553', 'name': 'Spadeadam', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '9.0', 'id': '3316', 'latitude': '53.497', 'longitude': '-3.056', 'obsSource': 'LNDSYN', 'name': 'Crosby', 'region': 'nw', 'unitaryAuthArea': 'Merseyside'}, {'elevation': '68.0', 'id': '3377', 'latitude': '53.175', 'longitude': '-0.521', 'name': 'Waddington', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '360.0', 'id': '3410', 'latitude': '52.757', 'longitude': '-3.464', 'name': 'Lake Vyrnwy Saws', 'region': 'wl', 'unitaryAuthArea': 'Powys'}, {'elevation': '21.0', 'id': '3488', 'latitude': '52.949', 'longitude': '1.127', 'obsSource': 'LNDSYN', 'name': 'Weybourne', 'region': 'ee', 'unitaryAuthArea': 'Norfolk'}, {'elevation': '35.0', 'id': '3351', 'latitude': '53.3598', 'longitude': '-2.3805', 'name': 'Rostherne No 2', 'region': 'nw', 'unitaryAuthArea': 'Cheshire East'}, {'elevation': '128.0', 'id': '3680', 'latitude': '51.8067', 'longitude': '-0.3602', 'name': 'Rothamsted', 'region': 'ee', 'unitaryAuthArea': 'Hertfordshire'}, {'elevation': '140.0', 'id': '3080', 'latitude': '57.077', 'longitude': '-2.836', 'name': 'Aboyne', 'region': 'gr', 'unitaryAuthArea': 'Aberdeenshire'}, {'elevation': '134.0', 'id': '3088', 'latitude': '56.852', 'longitude': '-2.264', 'name': 'Inverbervie', 'region': 'gr', 'unitaryAuthArea': 'Aberdeenshire'}, {'elevation': '10.0', 'id': '3111', 'latitude': '55.441', 'longitude': '-5.699', 'obsSource': 'LNDSYN', 'name': 'Campbeltown Airport', 'region': 'st', 'unitaryAuthArea': 'Argyll and Bute'}, {'elevation': '15.0', 'id': '3026', 'latitude': '58.214', 'longitude': '-6.325', 'obsSource': 'LNDSYN', 'name': 'Stornoway', 'region': 'he', 'unitaryAuthArea': 'Na h-Eileanan Siar'}, {'elevation': '265.0', 'id': '3031', 'latitude': '57.725', 'longitude': '-4.896', 'name': 'Loch Glascarnoch', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '773.0', 'id': '3039', 'latitude': '57.4175', 'longitude': '-5.689', 'name': 'Bealach Na Ba', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '87.0', 'id': '3808', 'latitude': '50.218', 'longitude': '-5.33', 'name': 'Camborne', 'region': 'sw', 'unitaryAuthArea': 'Cornwall'}, {'elevation': '16.0', 'id': '3866', 'latitude': '50.577', 'longitude': '-1.297', 'name': 'St Catherines Pt.', 'region': 'se', 'unitaryAuthArea': 'Isle of Wight'}, {'elevation': '4.0', 'id': '3872', 'latitude': '50.815', 'longitude': '-0.923', 'name': 'Thorney Island', 'region': 'se', 'unitaryAuthArea': 'West Sussex'}, {'elevation': '52.0', 'id': '3882', 'latitude': '50.89', 'longitude': '0.319', 'name': 'Herstmonceux West End', 'region': 'se', 'unitaryAuthArea': 'East Sussex'}, {'elevation': '49.0', 'id': '3904', 'latitude': '54.707', 'longitude': '-7.577', 'name': 'Castlederg', 'region': 'ni', 'unitaryAuthArea': 'County Tyrone'}, {'elevation': '40.0', 'id': '3952', 'latitude': '51.799', 'longitude': '-8.25', 'obsSource': 'LNDSYN', 'name': 'Roches Point'}, {'elevation': '115.0', 'id': '99060', 'latitude': '53.85', 'longitude': '-2.467', 'name': 'Stonyhurst', 'region': 'nw', 'unitaryAuthArea': 'Lancashire'}, {'elevation': '63.0', 'id': '3503', 'latitude': '52.344', 'longitude': '-3.947', 'name': 'Trawsgoed', 'region': 'wl', 'unitaryAuthArea': 'Ceredigion'}, {'elevation': '307.0', 'id': '3507', 'latitude': '52.063', 'longitude': '-3.614', 'name': 'Sennybridge', 'region': 'wl', 'unitaryAuthArea': 'Powys'}, {'elevation': '81.0', 'id': '3649', 'latitude': '51.758', 'longitude': '-1.576', 'name': 'Brize Norton', 'region': 'se', 'unitaryAuthArea': 'Oxfordshire'}, {'elevation': '40.0', 'id': '3672', 'latitude': '51.548', 'longitude': '-0.415', 'name': 'Northolt', 'region': 'se', 'unitaryAuthArea': 'Greater London'}, {'elevation': '6.0', 'id': '3707', 'latitude': '51.089', 'longitude': '-4.149', 'name': 'Chivenor', 'region': 'sw', 'unitaryAuthArea': 'Devon'}, {'elevation': '25.0', 'id': '3772', 'latitude': '51.479', 'longitude': '-0.449', 'name': 'Heathrow', 'region': 'se', 'unitaryAuthArea': 'Greater London'}, {'elevation': '59.0', 'id': '3134', 'latitude': '55.907', 'longitude': '-4.533', 'name': 'Glasgow/Bishopton', 'region': 'st', 'unitaryAuthArea': 'Renfrewshire'}, {'elevation': '15.0', 'id': '3214', 'latitude': '54.125', 'longitude': '-3.257', 'name': 'Walney Island', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '255.0', 'id': '3225', 'latitude': '54.501', 'longitude': '-2.684', 'name': 'Shap', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '847.0', 'id': '3227', 'latitude': '54.684', 'longitude': '-2.45', 'name': 'Great Dun Fell 2', 'region': 'nw', 'unitaryAuthArea': 'Cumbria'}, {'elevation': '298.0', 'id': '3330', 'latitude': '53.12755', 'longitude': '-1.97993', 'name': 'Leek', 'region': 'wm', 'unitaryAuthArea': 'Staffordshire'}, {'elevation': '57.0', 'id': '3373', 'latitude': '53.307', 'longitude': '-0.546', 'name': 'Scampton', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '95.0', 'id': '3405', 'latitude': '52.789', 'longitude': '-4.742', 'name': 'Aberdaron', 'region': 'wl', 'unitaryAuthArea': 'Gwynedd'}, {'elevation': '27.0', 'id': '3839', 'latitude': '50.737', 'longitude': '-3.405', 'name': 'Exeter Airport', 'region': 'sw', 'unitaryAuthArea': 'Devon'}, {'elevation': '4.0', 'id': '3023', 'latitude': '57.358', 'longitude': '-7.397', 'obsSource': 'LNDSYN', 'name': 'South Uist Range', 'region': 'he', 'unitaryAuthArea': 'Na h-Eileanan Siar'}, {'elevation': '1130.0', 'id': '3041', 'latitude': '56.822', 'longitude': '-4.97', 'name': 'Aonach Mor Summit', 'region': 'he', 'unitaryAuthArea': 'Highland'}, {'elevation': '3.0', 'id': '3784', 'latitude': '51.464', 'longitude': '0.314', 'name': 'Gravesend-Broadness', 'region': 'se', 'unitaryAuthArea': 'Kent'}, {'elevation': '54.0', 'id': '3797', 'latitude': '51.3422', 'longitude': '1.3461', 'obsSource': 'LNDSYN', 'name': 'Manston', 'region': 'se', 'unitaryAuthArea': 'Kent'}, {'elevation': '50.0', 'id': '3827', 'latitude': '50.354', 'longitude': '-4.121', 'obsSource': 'LNDSYN', 'name': 'Mount Batten', 'region': 'sw', 'unitaryAuthArea': 'Plymouth'}, {'elevation': '161.0', 'id': '3923', 'latitude': '54.237', 'longitude': '-6.502', 'name': 'Glenanne', 'region': 'ni', 'unitaryAuthArea': 'County Armagh'}, {'elevation': '133.0', 'id': '3502', 'latitude': '52.139', 'longitude': '-4.571', 'name': 'Aberporth', 'region': 'wl', 'unitaryAuthArea': 'Ceredigion'}, {'elevation': '107.0', 'id': '3544', 'latitude': '52.358', 'longitude': '-1.33', 'name': 'Church Lawford', 'region': 'wm', 'unitaryAuthArea': 'Warwickshire'}, {'elevation': '158.0', 'id': '3275', 'latitude': '54.563', 'longitude': '-0.863', 'name': 'Loftus (Samos)', 'region': 'ne', 'unitaryAuthArea': 'Redcar and Cleveland'}, {'elevation': '216.0', 'id': '3305', 'latitude': '53.093', 'longitude': '-3.941', 'name': 'Capel Curig', 'nationalPark': 'Snowdonia National Park', 'region': 'wl', 'unitaryAuthArea': 'Conwy'}, {'elevation': '3.0', 'id': '3469', 'latitude': '52.873', 'longitude': '0.141', 'name': 'Holbeach', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '26.0', 'id': '3017', 'latitude': '58.954', 'longitude': '-2.9', 'obsSource': 'LNDSYN', 'name': 'Kirkwall', 'region': 'os', 'unitaryAuthArea': 'Orkney Islands'}, {'elevation': '170.0', 'id': '3781', 'latitude': '51.303', 'longitude': '-0.09', 'name': 'Kenley', 'region': 'se', 'unitaryAuthArea': 'Surrey'}, {'elevation': '101.0', 'id': '3894', 'latitude': '49.44', 'longitude': '-2.6', 'obsSource': 'LNDSYN', 'name': 'Guernsey', 'region': 'sw', 'unitaryAuthArea': 'Guernsey'}, {'elevation': '63.0', 'id': '3917', 'latitude': '54.664', 'longitude': '-6.224', 'obsSource': 'LNDSYN', 'name': 'Belfast International Airport', 'region': 'ni', 'unitaryAuthArea': 'County Antrim'}, {'elevation': '89.0', 'id': '3590', 'latitude': '52.123', 'longitude': '0.961', 'name': 'Wattisham', 'region': 'ee', 'unitaryAuthArea': 'Suffolk'}, {'elevation': '32.0', 'id': '3609', 'latitude': '51.565', 'longitude': '-3.981', 'name': 'Mumbles Head', 'region': 'wl', 'unitaryAuthArea': 'Swansea'}, {'elevation': '57.0', 'id': '3658', 'latitude': '51.62', 'longitude': '-1.097', 'name': 'Benson', 'region': 'se', 'unitaryAuthArea': 'Oxfordshire'}, {'elevation': '35.0', 'id': '3144', 'latitude': '56.326', 'longitude': '-3.729', 'name': 'Strathallan', 'region': 'ta', 'unitaryAuthArea': 'Perth and Kinross'}, {'elevation': '564.0', 'id': '3148', 'latitude': '56.423', 'longitude': '-4.32', 'name': 'Glen Ogle', 'nationalPark': 'Loch Lomond and the Trossachs National Park', 'region': 'ta', 'unitaryAuthArea': 'Stirling'}, {'elevation': '16.0', 'id': '3204', 'latitude': '54.0849', 'longitude': '-4.6321', 'obsSource': 'LNDSYN', 'name': 'Ronaldsway', 'region': 'nw'}, {'elevation': '23.0', 'id': '3240', 'latitude': '55.421', 'longitude': '-1.6', 'obsSource': 'LNDSYN', 'name': 'Boulmer', 'region': 'ne', 'unitaryAuthArea': 'Northumberland'}, {'elevation': '25.0', 'id': '3265', 'latitude': '54.204', 'longitude': '-1.39', 'name': 'Topcliffe', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '15.0', 'id': '3292', 'latitude': '54.094', 'longitude': '-0.174', 'name': 'Bridlington Mrsc', 'region': 'yh', 'unitaryAuthArea': 'East Riding of Yorkshire'}, {'elevation': '77.0', 'id': '3313', 'latitude': '53.259', 'longitude': '-3.509', 'name': 'Rhyl', 'region': 'wl', 'unitaryAuthArea': 'Denbighshire'}, {'elevation': '10.0', 'id': '3321', 'latitude': '53.174', 'longitude': '-2.986', 'name': 'Hawarden', 'region': 'wl', 'unitaryAuthArea': 'Flintshire'}, {'elevation': '117.0', 'id': '3354', 'latitude': '53.005', 'longitude': '-1.25', 'name': 'Watnall', 'region': 'em', 'unitaryAuthArea': 'Nottinghamshire'}, {'elevation': '7.0', 'id': '3382', 'latitude': '53.867', 'longitude': '-0.433', 'name': 'Leconfield Sar', 'region': 'yh', 'unitaryAuthArea': 'East Riding of Yorkshire'}, {'elevation': '8.0', 'id': '3385', 'latitude': '53.473', 'longitude': '0.154', 'obsSource': 'LNDSYN', 'name': 'Donna Nook', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '6.0', 'id': '3391', 'latitude': '53.094', 'longitude': '-0.171', 'name': 'Coningsby', 'region': 'em', 'unitaryAuthArea': 'Lincolnshire'}, {'elevation': '110.0', 'id': '99142', 'latitude': '54.273', 'longitude': '-0.421', 'name': 'Scarborough', 'region': 'yh', 'unitaryAuthArea': 'North Yorkshire'}, {'elevation': '27.0', 'id': '3844', 'latitude': '50.7366', 'longitude': '-3.40458', 'name': 'Exeter Airport 2', 'region': 'sw', 'unitaryAuthArea': 'Devon'}]}}\n"
     ]
    }
   ],
   "source": [
    "# Capture the returned data\n",
    "print(sites)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3: Parse JSON files\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have played around GeoJSON file last week. JSON is just like GeoJSON, but without embedded geographic data structures. Now that you have a better idea of what data the reply contains, let's see if we can convert the JSON reply into something useful for Python; if you scroll back up to where we printed out the reply you'll notice that it all starts with a '{', meaning that it's a dictionary. \n",
    "\n",
    "Yes, look just like the GeoJSON file. (So you should known how to parse it)\n",
    "\n",
    "Let's start by printing out the keys in the dictionary and the _type_ of data associated as a value to that key:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Key: Locations\n",
      "Value: <class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "for k in sites.keys():\n",
    "    print(\"Key: \" + str(k))\n",
    "    print(\"Value: \" + str(type(sites[k])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not the most exciting answer, but at least we know that the value is a dictionary. Let's try moving down a level:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Key: Locations\n",
      "Value: <class 'dict'>\n",
      "\tKey: Location\n",
      "\tValue: <class 'list'>\n"
     ]
    }
   ],
   "source": [
    "for k in sites.keys():\n",
    "    print(\"Key: \" + str(k))\n",
    "    print(\"Value: \" + str(type(sites[k])))\n",
    "    for k2 in sites[k].keys():\n",
    "        print(\"\\tKey: \" + str(k2))\n",
    "        print(\"\\tValue: \" + str(type(sites[k][k2])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**This isn't great design in the reply: we have a dictionary that contains only one key/value pair, and _that_ dictionary in turn contains only one key/value pair. But after that we get to a long, long list containing the data...**\n",
    "\n",
    "The MetOffice is not making life easy for us here: there's a _lot_ of extra 'baggage' in this API response. But we at least know that the next level down is a list and _that_ suggests that things are about to get a bit more interesting... Let's simplify our code at the same time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List in API response is 148 long\n"
     ]
    }
   ],
   "source": [
    "apiList = sites['Locations']['Location']\n",
    "print(\"List in API response is \" + str(len(apiList)) + \" long\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now _that_ is a rather more interesting response. What it means is that our JSON reply has this structure:\n",
    "```\n",
    "{\n",
    "    'Locations': {\n",
    "        'Location': [\n",
    "            ... lots of data here ...\n",
    "        ]\n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "If you scroll back up to the JSON reply you should now be able to read a little bit more of the response... and this should give you a clue as to how to print out the `name`, `id`, and `longitude` of the first five sites. I'll get you started:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Location: Kinloss (id: 3066) is at longitude: -3.5606\n",
      "Location: Lossiemouth (id: 3068) is at longitude: -3.322\n",
      "Location: Wick John O Groats Airport (id: 3075) is at longitude: -3.089\n",
      "Location: Baltasound (id: 3002) is at longitude: -0.854\n",
      "Location: Lerwick (S. Screen) (id: 3005) is at longitude: -1.183\n"
     ]
    }
   ],
   "source": [
    "for i in range(5):\n",
    "    location = apiList[i]\n",
    "    print(\"Location: \" + location['name'] + \" (id: \" + location['id'] + \") is at longitude: \" + location['longitude'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your answer should look like this:\n",
    "\n",
    "`\n",
    "Location: Kinloss (id: 3066) is at longitude: -3.5606\n",
    "Location: Lossiemouth (id: 3068) is at longitude: -3.322\n",
    "Location: Wick John O Groats Airport (id: 3075) is at longitude: -3.089\n",
    "Location: Baltasound (id: 3002) is at longitude: -0.854\n",
    "Location: Lerwick (S. Screen) (id: 3005) is at longitude: -1.183\n",
    "`\n",
    "\n",
    "And _now_ that we know where all the data was 'hidden', we can convert this to a proper data structure in which it is possible to _interact_ with it. To do that, we'll put the site data into a pandas data frame..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 4: Turning API data into a Pandas DataFrame\n",
    "\n",
    "Pandas is remarkably intelligent and will _often_ -- though not always -- work out the sensible thing to do from many kinds of data structures (list-of-lists, dictionary-of-lists, list-of-dictionaries...). So let's see what happens when we simply pass `apiList` (a LoD) directly to the `DataFrame` 'constructor' instead of passing the data through, for instance, the `read_csv` function as we did above with a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  elevation    id latitude longitude                        name nationalPark  \\\n",
      "0       7.0  3066  57.6494   -3.5606                     Kinloss          NaN   \n",
      "1       6.0  3068   57.712    -3.322                 Lossiemouth          NaN   \n",
      "2      36.0  3075   58.454    -3.089  Wick John O Groats Airport          NaN   \n",
      "3      15.0  3002   60.749    -0.854                  Baltasound          NaN   \n",
      "4      82.0  3005   60.139    -1.183         Lerwick (S. Screen)          NaN   \n",
      "\n",
      "  obsSource region   unitaryAuthArea  \n",
      "0       NaN     gr             Moray  \n",
      "1    LNDSYN     gr             Moray  \n",
      "2    LNDSYN     he          Highland  \n",
      "3       NaN     os  Shetland Islands  \n",
      "4    LNDSYN     os  Shetland Islands  \n"
     ]
    }
   ],
   "source": [
    "site_df = pd.DataFrame(apiList)\n",
    "print(site_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wow, that's... almost scarily easy. You can see that pandas worked out the structure of our LoD and then automatically converted that to columns in a data frame. So it got the hardest part of the process exactly right and has saved us a lot of work. _That_ is the point of functions and of code: to be constructively lazy.\n",
    "\n",
    "Of course, we could have predicted that pandas would cope since there is a whole section in the documentaiton [devoted to creating data frames from different structures](http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe).\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The problem is that pandas didn't know what we expected the columns to be, so it's treated them all as 'objects' (basically: strings) and not as numeric data types. To fix that you need to know that there's a function called `'astype'` that allows pandas to convert between different data types where it's fairly easy for pandas to figure out what we want to do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in ['region','unitaryAuthArea']:\n",
    "    site_df[c] = site_df[c].astype('str')\n",
    "for c in ['elevation','latitude','longitude']:\n",
    "    site_df[c] = site_df[c].astype('float')\n",
    "for c in ['id']:\n",
    "    site_df[c] = site_df[c].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>elevation</th>\n",
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       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
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       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>148.0000</td>\n",
       "      <td>148.0000</td>\n",
       "      <td>148.0000</td>\n",
       "      <td>148.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>119.2432</td>\n",
       "      <td>6,033.1216</td>\n",
       "      <td>53.7383</td>\n",
       "      <td>-2.8579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>189.2141</td>\n",
       "      <td>15,564.2395</td>\n",
       "      <td>2.5321</td>\n",
       "      <td>2.2598</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.0000</td>\n",
       "      <td>3,002.0000</td>\n",
       "      <td>49.2079</td>\n",
       "      <td>-10.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>20.7500</td>\n",
       "      <td>3,169.7500</td>\n",
       "      <td>51.6062</td>\n",
       "      <td>-4.1917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63.0000</td>\n",
       "      <td>3,407.5000</td>\n",
       "      <td>53.2555</td>\n",
       "      <td>-2.6735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>132.2500</td>\n",
       "      <td>3,768.2500</td>\n",
       "      <td>55.3247</td>\n",
       "      <td>-1.2332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1,245.0000</td>\n",
       "      <td>99,142.0000</td>\n",
       "      <td>60.7490</td>\n",
       "      <td>1.3480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "       elevation          id  latitude  longitude\n",
       "count   148.0000    148.0000  148.0000   148.0000\n",
       "mean    119.2432  6,033.1216   53.7383    -2.8579\n",
       "std     189.2141 15,564.2395    2.5321     2.2598\n",
       "min       2.0000  3,002.0000   49.2079   -10.2500\n",
       "25%      20.7500  3,169.7500   51.6062    -4.1917\n",
       "50%      63.0000  3,407.5000   53.2555    -2.6735\n",
       "75%     132.2500  3,768.2500   55.3247    -1.2332\n",
       "max   1,245.0000 99,142.0000   60.7490     1.3480"
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     "execution_count": 15,
     "metadata": {},
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   ],
   "source": [
    "site_df.describe() # only the numeric paratmers shows here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 5: Making an interactive map using Folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we go further, lets make use of your mapping skills learned last week to visually identify where are the locations collects weather data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the map to be created, we are able to answer the first question: for what locations can I get weather data? - Let's add all sites (points) to the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
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                var icon_ff37b3662eb84fa4a3d3881e46f7a030 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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            var popup_2fa2e5f7c6f248848a8171173c3db770 = L.popup({maxWidth: '300'
            
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                var html_65f80327165649b8ba4a547db683eefe = $(`<div id="html_65f80327165649b8ba4a547db683eefe" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_c057f867b3fa45cc9021c4b87a482d62.bindPopup(popup_2fa2e5f7c6f248848a8171173c3db770)
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        var marker_3fb8fdbb497b496a869dad0f224a9f82 = L.marker(
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                var icon_4421b000ae1947938263d4acf6009367 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_ed8726c13ba04166ba4eb62d2767de8e = L.popup({maxWidth: '300'
            
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                var html_69919fb054254d2ebdc7a71ad5af5d29 = $(`<div id="html_69919fb054254d2ebdc7a71ad5af5d29" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_3fb8fdbb497b496a869dad0f224a9f82.bindPopup(popup_ed8726c13ba04166ba4eb62d2767de8e)
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        var marker_6bb37265daec4a01b2c932d40ffbb65d = L.marker(
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                var icon_8174184848f84b41892a4af6d510083c = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_773b1a3e2fcc4a4fa7feb4844bd2285a = L.popup({maxWidth: '300'
            
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                var html_c8249e03f6c241c6b5cf1b97cedd9422 = $(`<div id="html_c8249e03f6c241c6b5cf1b97cedd9422" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_773b1a3e2fcc4a4fa7feb4844bd2285a.setContent(html_c8249e03f6c241c6b5cf1b97cedd9422);
            

            marker_6bb37265daec4a01b2c932d40ffbb65d.bindPopup(popup_773b1a3e2fcc4a4fa7feb4844bd2285a)
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        var marker_8f760d6760e34b7286fda4ea8885ab14 = L.marker(
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                var icon_13707653f9f44857a14f9bff13f86b05 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_8f760d6760e34b7286fda4ea8885ab14.setIcon(icon_13707653f9f44857a14f9bff13f86b05);
            
    
            var popup_8a40c282180d4eacab7518c1bf8f7d3e = L.popup({maxWidth: '300'
            
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                var html_30d5699bdb4d4ccd9b83934a0d548aa4 = $(`<div id="html_30d5699bdb4d4ccd9b83934a0d548aa4" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_8a40c282180d4eacab7518c1bf8f7d3e.setContent(html_30d5699bdb4d4ccd9b83934a0d548aa4);
            

            marker_8f760d6760e34b7286fda4ea8885ab14.bindPopup(popup_8a40c282180d4eacab7518c1bf8f7d3e)
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        var marker_22f10cf954dd4fe99f80618a19b83d93 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_7b4fd35e813a4d25acf4c653f597256b = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_8c89db42de0b4093bfb6145942c9c8c3 = L.popup({maxWidth: '300'
            
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                var html_a71eab33182646039af5d5e8a43c1a19 = $(`<div id="html_a71eab33182646039af5d5e8a43c1a19" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_22f10cf954dd4fe99f80618a19b83d93.bindPopup(popup_8c89db42de0b4093bfb6145942c9c8c3)
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        var marker_cf36044fbb764f14af2cab1d0708d866 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_fdcfe902c4c842fa9ab2f9422bdb25fc = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_cf36044fbb764f14af2cab1d0708d866.setIcon(icon_fdcfe902c4c842fa9ab2f9422bdb25fc);
            
    
            var popup_315cb6a2fc24416b8ab37fafcd22d862 = L.popup({maxWidth: '300'
            
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                var html_e35e63b2bb494bfcaaff37cd20e2ff76 = $(`<div id="html_e35e63b2bb494bfcaaff37cd20e2ff76" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_315cb6a2fc24416b8ab37fafcd22d862.setContent(html_e35e63b2bb494bfcaaff37cd20e2ff76);
            

            marker_cf36044fbb764f14af2cab1d0708d866.bindPopup(popup_315cb6a2fc24416b8ab37fafcd22d862)
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        var marker_32bbd91bee89434297eb7c5f826e7430 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_222c43991612447f9e8e609a61dbe228 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_32bbd91bee89434297eb7c5f826e7430.setIcon(icon_222c43991612447f9e8e609a61dbe228);
            
    
            var popup_3129c651d2994902904d73efc6f54e0e = L.popup({maxWidth: '300'
            
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                var html_c8b5ff8ed1054c899337ef71d8664bf1 = $(`<div id="html_c8b5ff8ed1054c899337ef71d8664bf1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_3129c651d2994902904d73efc6f54e0e.setContent(html_c8b5ff8ed1054c899337ef71d8664bf1);
            

            marker_32bbd91bee89434297eb7c5f826e7430.bindPopup(popup_3129c651d2994902904d73efc6f54e0e)
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        var marker_4b9f435ce3f64f2ca2d1f3ab24085ced = L.marker(
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                var icon_c022d65f6af14ea69d0b373b24e20064 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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            var popup_48bbea5f1e6b4047889fca19285311ca = L.popup({maxWidth: '300'
            
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                var html_7fad041b1e84459db2bfaaae504a9184 = $(`<div id="html_7fad041b1e84459db2bfaaae504a9184" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_48bbea5f1e6b4047889fca19285311ca.setContent(html_7fad041b1e84459db2bfaaae504a9184);
            

            marker_4b9f435ce3f64f2ca2d1f3ab24085ced.bindPopup(popup_48bbea5f1e6b4047889fca19285311ca)
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        var marker_93262027a1f34bcea00e222b948bac5a = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_bdc3088033e642ca9daaa50c62534a09 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_ec06df25dd4f4c37a8cfd8f13afe631e = L.popup({maxWidth: '300'
            
            });

            
                var html_cc92930fb15848aa8ecec59379d9adc1 = $(`<div id="html_cc92930fb15848aa8ecec59379d9adc1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_ec06df25dd4f4c37a8cfd8f13afe631e.setContent(html_cc92930fb15848aa8ecec59379d9adc1);
            

            marker_93262027a1f34bcea00e222b948bac5a.bindPopup(popup_ec06df25dd4f4c37a8cfd8f13afe631e)
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        var marker_345442f8eacd48e4be41b53376027bc6 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_832b10e309cb443c9936a3123c0c5483 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_345442f8eacd48e4be41b53376027bc6.setIcon(icon_832b10e309cb443c9936a3123c0c5483);
            
    
            var popup_533879da5dcd47c68d0c0a522f15c192 = L.popup({maxWidth: '300'
            
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                var html_369994fab25d4efa82d4a318f8a6f012 = $(`<div id="html_369994fab25d4efa82d4a318f8a6f012" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_533879da5dcd47c68d0c0a522f15c192.setContent(html_369994fab25d4efa82d4a318f8a6f012);
            

            marker_345442f8eacd48e4be41b53376027bc6.bindPopup(popup_533879da5dcd47c68d0c0a522f15c192)
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        var marker_6db3ba55dc2447858f034157f2621e62 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_3eff49019ee943ea9fd1d5e0468cde21 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_6db3ba55dc2447858f034157f2621e62.setIcon(icon_3eff49019ee943ea9fd1d5e0468cde21);
            
    
            var popup_9775c120e1e940b4915f8a3ff9e934d1 = L.popup({maxWidth: '300'
            
            });

            
                var html_7410608b63a742f58ea7c8739e3bca6d = $(`<div id="html_7410608b63a742f58ea7c8739e3bca6d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_9775c120e1e940b4915f8a3ff9e934d1.setContent(html_7410608b63a742f58ea7c8739e3bca6d);
            

            marker_6db3ba55dc2447858f034157f2621e62.bindPopup(popup_9775c120e1e940b4915f8a3ff9e934d1)
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        var marker_b1788dac9b084df69eb2f5e517923ff8 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_57f8ff9dc5594aa183cfb9f40850c2bb = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_b1788dac9b084df69eb2f5e517923ff8.setIcon(icon_57f8ff9dc5594aa183cfb9f40850c2bb);
            
    
            var popup_fad8e0c380e543eb944f89829edd11d4 = L.popup({maxWidth: '300'
            
            });

            
                var html_9c65a8f69fe542dcb5d5b1e405e567a1 = $(`<div id="html_9c65a8f69fe542dcb5d5b1e405e567a1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_fad8e0c380e543eb944f89829edd11d4.setContent(html_9c65a8f69fe542dcb5d5b1e405e567a1);
            

            marker_b1788dac9b084df69eb2f5e517923ff8.bindPopup(popup_fad8e0c380e543eb944f89829edd11d4)
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        var marker_e9612f20886f433686a68288d36fb971 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_07b67108a664403e926d6a8e56989a14 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_e9612f20886f433686a68288d36fb971.setIcon(icon_07b67108a664403e926d6a8e56989a14);
            
    
            var popup_b4f36511d4ac451db7bd7e9c4fb04a0b = L.popup({maxWidth: '300'
            
            });

            
                var html_1fba9d642091486598a77e21d68d5c82 = $(`<div id="html_1fba9d642091486598a77e21d68d5c82" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b4f36511d4ac451db7bd7e9c4fb04a0b.setContent(html_1fba9d642091486598a77e21d68d5c82);
            

            marker_e9612f20886f433686a68288d36fb971.bindPopup(popup_b4f36511d4ac451db7bd7e9c4fb04a0b)
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        var marker_ce59cc2007274d0598673468547ccf80 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_b9a8b331ffb94f5e9cba194d4fe51063 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_ce59cc2007274d0598673468547ccf80.setIcon(icon_b9a8b331ffb94f5e9cba194d4fe51063);
            
    
            var popup_04fcf21e34294bb88254f8e6fc389bf1 = L.popup({maxWidth: '300'
            
            });

            
                var html_e4f435ef295c4c26acc5bbab1daf5e37 = $(`<div id="html_e4f435ef295c4c26acc5bbab1daf5e37" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_04fcf21e34294bb88254f8e6fc389bf1.setContent(html_e4f435ef295c4c26acc5bbab1daf5e37);
            

            marker_ce59cc2007274d0598673468547ccf80.bindPopup(popup_04fcf21e34294bb88254f8e6fc389bf1)
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        var marker_b2c6e4df93fa4c61a0d0c803a7dd90be = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_97eb589140b444eea2b4435461049130 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_b2c6e4df93fa4c61a0d0c803a7dd90be.setIcon(icon_97eb589140b444eea2b4435461049130);
            
    
            var popup_d38f7293adf240119f200989c7843c94 = L.popup({maxWidth: '300'
            
            });

            
                var html_aa57ff3b14b743109032a99f9367d5d4 = $(`<div id="html_aa57ff3b14b743109032a99f9367d5d4" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_d38f7293adf240119f200989c7843c94.setContent(html_aa57ff3b14b743109032a99f9367d5d4);
            

            marker_b2c6e4df93fa4c61a0d0c803a7dd90be.bindPopup(popup_d38f7293adf240119f200989c7843c94)
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        var marker_6831c6a54e4140bfba5ee57125d86a71 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_967948dfe9ff4aff8b8b00dba104b7a1 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_6831c6a54e4140bfba5ee57125d86a71.setIcon(icon_967948dfe9ff4aff8b8b00dba104b7a1);
            
    
            var popup_49161f9a4df54f91aa2c2aaa61f82a47 = L.popup({maxWidth: '300'
            
            });

            
                var html_b7717b61705e40fa95410e9eb010f925 = $(`<div id="html_b7717b61705e40fa95410e9eb010f925" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_49161f9a4df54f91aa2c2aaa61f82a47.setContent(html_b7717b61705e40fa95410e9eb010f925);
            

            marker_6831c6a54e4140bfba5ee57125d86a71.bindPopup(popup_49161f9a4df54f91aa2c2aaa61f82a47)
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        var marker_a35f79b221034abfbd1e5786676f3129 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_07b29901e2d0419ab0948839553bc683 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_a35f79b221034abfbd1e5786676f3129.setIcon(icon_07b29901e2d0419ab0948839553bc683);
            
    
            var popup_757922837a5a4f409fe40342fdf758fc = L.popup({maxWidth: '300'
            
            });

            
                var html_7d04c68eb64d4706bb1733fd8968cd05 = $(`<div id="html_7d04c68eb64d4706bb1733fd8968cd05" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_757922837a5a4f409fe40342fdf758fc.setContent(html_7d04c68eb64d4706bb1733fd8968cd05);
            

            marker_a35f79b221034abfbd1e5786676f3129.bindPopup(popup_757922837a5a4f409fe40342fdf758fc)
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        var marker_5f5aadbb1e334affbfc92dfd2c422c4e = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_8f938441ce6b466f9077077ef56b5ee9 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
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            var popup_949e58e49f834e86b70521dfe3caf192 = L.popup({maxWidth: '300'
            
            });

            
                var html_494734657e1b47fa8c18788af12b85db = $(`<div id="html_494734657e1b47fa8c18788af12b85db" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_5f5aadbb1e334affbfc92dfd2c422c4e.bindPopup(popup_949e58e49f834e86b70521dfe3caf192)
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        var marker_b9f0be92afdd4a80878bc4bc3a67268f = L.marker(
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                var icon_57c9ac389d134e118c4382919a7a5a9e = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_0b42e993cd1c4fd8893f11ef3b53278e = L.popup({maxWidth: '300'
            
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                var html_659f6a24a95249dd9af339c1cb371aca = $(`<div id="html_659f6a24a95249dd9af339c1cb371aca" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_b9f0be92afdd4a80878bc4bc3a67268f.bindPopup(popup_0b42e993cd1c4fd8893f11ef3b53278e)
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        var marker_20f7bac88fac4f39bc0a0d1c51cf01ad = L.marker(
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                var icon_a83e98414825496ba7ca7dfd002762c4 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_20f7bac88fac4f39bc0a0d1c51cf01ad.setIcon(icon_a83e98414825496ba7ca7dfd002762c4);
            
    
            var popup_103772312d26402ebc9263a62dfa175d = L.popup({maxWidth: '300'
            
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                var html_8105b64184294dccb1e440a83dcde8c0 = $(`<div id="html_8105b64184294dccb1e440a83dcde8c0" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_103772312d26402ebc9263a62dfa175d.setContent(html_8105b64184294dccb1e440a83dcde8c0);
            

            marker_20f7bac88fac4f39bc0a0d1c51cf01ad.bindPopup(popup_103772312d26402ebc9263a62dfa175d)
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        var marker_49bd4ac6ddce4198ba0d083c31709c65 = L.marker(
            [51.405, -3.44],
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_9d656c9a13ee43349b98fed691f8a3fb = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_49bd4ac6ddce4198ba0d083c31709c65.setIcon(icon_9d656c9a13ee43349b98fed691f8a3fb);
            
    
            var popup_b4313526b9a04c8c9e719c71c6dfbd94 = L.popup({maxWidth: '300'
            
            });

            
                var html_88e85a71f8d442a49ec4402f7fa43f0d = $(`<div id="html_88e85a71f8d442a49ec4402f7fa43f0d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b4313526b9a04c8c9e719c71c6dfbd94.setContent(html_88e85a71f8d442a49ec4402f7fa43f0d);
            

            marker_49bd4ac6ddce4198ba0d083c31709c65.bindPopup(popup_b4313526b9a04c8c9e719c71c6dfbd94)
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        var marker_034113c9e30a4e2f8f9df02f1a964979 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_006b592cc8064418b1e46f20f84b4813 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_034113c9e30a4e2f8f9df02f1a964979.setIcon(icon_006b592cc8064418b1e46f20f84b4813);
            
    
            var popup_9b51cc3998bf4da0affb1bbf14cfc0a8 = L.popup({maxWidth: '300'
            
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                var html_c8840d2a50c44773a77bf10918e31826 = $(`<div id="html_c8840d2a50c44773a77bf10918e31826" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_9b51cc3998bf4da0affb1bbf14cfc0a8.setContent(html_c8840d2a50c44773a77bf10918e31826);
            

            marker_034113c9e30a4e2f8f9df02f1a964979.bindPopup(popup_9b51cc3998bf4da0affb1bbf14cfc0a8)
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        var marker_59bee021c19941849f9a9edd3357a784 = L.marker(
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                var icon_26c7ef233285418ab0b32e2981f6d0a5 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_59bee021c19941849f9a9edd3357a784.setIcon(icon_26c7ef233285418ab0b32e2981f6d0a5);
            
    
            var popup_30c7795a2d27470fb68e2336416fcbac = L.popup({maxWidth: '300'
            
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                var html_66b893afb1a44b48b37d67de3a6369c2 = $(`<div id="html_66b893afb1a44b48b37d67de3a6369c2" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_30c7795a2d27470fb68e2336416fcbac.setContent(html_66b893afb1a44b48b37d67de3a6369c2);
            

            marker_59bee021c19941849f9a9edd3357a784.bindPopup(popup_30c7795a2d27470fb68e2336416fcbac)
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        var marker_64552e551f124b69a718a7309a99a431 = L.marker(
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                var icon_ded571565b1149dfbf4796a8054a1b53 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_64552e551f124b69a718a7309a99a431.setIcon(icon_ded571565b1149dfbf4796a8054a1b53);
            
    
            var popup_b702986444c44bb88724e64e3268ea1d = L.popup({maxWidth: '300'
            
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                var html_07f7e053123f4c9a843ac197cceed784 = $(`<div id="html_07f7e053123f4c9a843ac197cceed784" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b702986444c44bb88724e64e3268ea1d.setContent(html_07f7e053123f4c9a843ac197cceed784);
            

            marker_64552e551f124b69a718a7309a99a431.bindPopup(popup_b702986444c44bb88724e64e3268ea1d)
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        var marker_7b7be93ddee64620a2190af3c0f8def1 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_8854efddad2b43859abea1767fcfe5d5 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_7b7be93ddee64620a2190af3c0f8def1.setIcon(icon_8854efddad2b43859abea1767fcfe5d5);
            
    
            var popup_67fc4c6161fa47cba51e9a5dff904111 = L.popup({maxWidth: '300'
            
            });

            
                var html_48639e7ca3534c78a3c5bf5218d387d9 = $(`<div id="html_48639e7ca3534c78a3c5bf5218d387d9" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_67fc4c6161fa47cba51e9a5dff904111.setContent(html_48639e7ca3534c78a3c5bf5218d387d9);
            

            marker_7b7be93ddee64620a2190af3c0f8def1.bindPopup(popup_67fc4c6161fa47cba51e9a5dff904111)
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        var marker_2c6568f0aef44d539671fb4dd6a54e8a = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_7bdf61d3d6ab475b84d5a5c8384ccf40 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_2c6568f0aef44d539671fb4dd6a54e8a.setIcon(icon_7bdf61d3d6ab475b84d5a5c8384ccf40);
            
    
            var popup_91986b67a5f64cffac68c116a2cdfe3d = L.popup({maxWidth: '300'
            
            });

            
                var html_5e37d972b3e0467eab4ad8bb1a428368 = $(`<div id="html_5e37d972b3e0467eab4ad8bb1a428368" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_91986b67a5f64cffac68c116a2cdfe3d.setContent(html_5e37d972b3e0467eab4ad8bb1a428368);
            

            marker_2c6568f0aef44d539671fb4dd6a54e8a.bindPopup(popup_91986b67a5f64cffac68c116a2cdfe3d)
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        var marker_3094aaa34e8948ac963e5f8dafa90254 = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e102c8914c1740748a8f05ba3c7787aa = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_3094aaa34e8948ac963e5f8dafa90254.setIcon(icon_e102c8914c1740748a8f05ba3c7787aa);
            
    
            var popup_fba60db14b9c4d51b8dadb11f6174084 = L.popup({maxWidth: '300'
            
            });

            
                var html_534c6e05d40746b7a62ed7b21ed9e97c = $(`<div id="html_534c6e05d40746b7a62ed7b21ed9e97c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_fba60db14b9c4d51b8dadb11f6174084.setContent(html_534c6e05d40746b7a62ed7b21ed9e97c);
            

            marker_3094aaa34e8948ac963e5f8dafa90254.bindPopup(popup_fba60db14b9c4d51b8dadb11f6174084)
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        var marker_0dc6f795c18c4532b71e713e0548beed = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_05b04dca5425436aae6bb6e9156a6488 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_0dc6f795c18c4532b71e713e0548beed.setIcon(icon_05b04dca5425436aae6bb6e9156a6488);
            
    
            var popup_741ba09695334e4a92def7f3644bd82b = L.popup({maxWidth: '300'
            
            });

            
                var html_082e5767e5dc45b380d23fb695877f2b = $(`<div id="html_082e5767e5dc45b380d23fb695877f2b" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_741ba09695334e4a92def7f3644bd82b.setContent(html_082e5767e5dc45b380d23fb695877f2b);
            

            marker_0dc6f795c18c4532b71e713e0548beed.bindPopup(popup_741ba09695334e4a92def7f3644bd82b)
            ;

            
        
    
        var marker_3555f0ec59424c16863dd6726b3707ff = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_ed53118c101f42af8061117a268e042c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_3555f0ec59424c16863dd6726b3707ff.setIcon(icon_ed53118c101f42af8061117a268e042c);
            
    
            var popup_f19da4796b57438bb145cb88d47277e8 = L.popup({maxWidth: '300'
            
            });

            
                var html_f1a3b9c25e5143e3a333753214343e95 = $(`<div id="html_f1a3b9c25e5143e3a333753214343e95" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f19da4796b57438bb145cb88d47277e8.setContent(html_f1a3b9c25e5143e3a333753214343e95);
            

            marker_3555f0ec59424c16863dd6726b3707ff.bindPopup(popup_f19da4796b57438bb145cb88d47277e8)
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        var marker_8a5b176348a04e30aa145c33e39f43a2 = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_ac6bda68443343aca409d411ed79101d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_8a5b176348a04e30aa145c33e39f43a2.setIcon(icon_ac6bda68443343aca409d411ed79101d);
            
    
            var popup_0df2132696b2451cb3abd20e915afc33 = L.popup({maxWidth: '300'
            
            });

            
                var html_8dcda1b4bca646dca79c809e84527c07 = $(`<div id="html_8dcda1b4bca646dca79c809e84527c07" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_0df2132696b2451cb3abd20e915afc33.setContent(html_8dcda1b4bca646dca79c809e84527c07);
            

            marker_8a5b176348a04e30aa145c33e39f43a2.bindPopup(popup_0df2132696b2451cb3abd20e915afc33)
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        var marker_4f29ba3180e045bf8ddc05edf0d1e153 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_da0063bf34154d5599de5ab73762913e = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_4f29ba3180e045bf8ddc05edf0d1e153.setIcon(icon_da0063bf34154d5599de5ab73762913e);
            
    
            var popup_af0d4859d4af4b9ba2c7036ce42346a5 = L.popup({maxWidth: '300'
            
            });

            
                var html_4ac46e53e1784f298107aae834bc62ff = $(`<div id="html_4ac46e53e1784f298107aae834bc62ff" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_af0d4859d4af4b9ba2c7036ce42346a5.setContent(html_4ac46e53e1784f298107aae834bc62ff);
            

            marker_4f29ba3180e045bf8ddc05edf0d1e153.bindPopup(popup_af0d4859d4af4b9ba2c7036ce42346a5)
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        var marker_1824d974c675476cb74a2b586621a6df = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_be0fba37897b4e7788509392e10e3425 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_1824d974c675476cb74a2b586621a6df.setIcon(icon_be0fba37897b4e7788509392e10e3425);
            
    
            var popup_c9f38ac99b694ce682eb6101d7fe728f = L.popup({maxWidth: '300'
            
            });

            
                var html_36c94f9b37de4798a8cb3bb126b476c1 = $(`<div id="html_36c94f9b37de4798a8cb3bb126b476c1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c9f38ac99b694ce682eb6101d7fe728f.setContent(html_36c94f9b37de4798a8cb3bb126b476c1);
            

            marker_1824d974c675476cb74a2b586621a6df.bindPopup(popup_c9f38ac99b694ce682eb6101d7fe728f)
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        var marker_0ae1eff6e680452bbef067eea1ba901e = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_095cc0d90fb04005bb3811d382c86410 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_0ae1eff6e680452bbef067eea1ba901e.setIcon(icon_095cc0d90fb04005bb3811d382c86410);
            
    
            var popup_2477fbf60057420088af77eacfbcf62e = L.popup({maxWidth: '300'
            
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                var html_a27dcdd64f534bdb8a8070e271c2bee0 = $(`<div id="html_a27dcdd64f534bdb8a8070e271c2bee0" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2477fbf60057420088af77eacfbcf62e.setContent(html_a27dcdd64f534bdb8a8070e271c2bee0);
            

            marker_0ae1eff6e680452bbef067eea1ba901e.bindPopup(popup_2477fbf60057420088af77eacfbcf62e)
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        var marker_1c47ebfbd16a4b88b359984e58ef8511 = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_dee766a9668b441492855f26563ced7d = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_1c47ebfbd16a4b88b359984e58ef8511.setIcon(icon_dee766a9668b441492855f26563ced7d);
            
    
            var popup_00be967561854ecb99d153e03ba3aed2 = L.popup({maxWidth: '300'
            
            });

            
                var html_aabad0ab01834fe2827d684accc9af31 = $(`<div id="html_aabad0ab01834fe2827d684accc9af31" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_00be967561854ecb99d153e03ba3aed2.setContent(html_aabad0ab01834fe2827d684accc9af31);
            

            marker_1c47ebfbd16a4b88b359984e58ef8511.bindPopup(popup_00be967561854ecb99d153e03ba3aed2)
            ;

            
        
    
        var marker_3e61579ab5174423b252cd980e6db4fd = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_aad007c693f243d1bd1c9004c9c3923a = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_3e61579ab5174423b252cd980e6db4fd.setIcon(icon_aad007c693f243d1bd1c9004c9c3923a);
            
    
            var popup_bafd066e204a45cb8f46323f03e6f4b6 = L.popup({maxWidth: '300'
            
            });

            
                var html_89a876b79f404661b522b121254eebaa = $(`<div id="html_89a876b79f404661b522b121254eebaa" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_bafd066e204a45cb8f46323f03e6f4b6.setContent(html_89a876b79f404661b522b121254eebaa);
            

            marker_3e61579ab5174423b252cd980e6db4fd.bindPopup(popup_bafd066e204a45cb8f46323f03e6f4b6)
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        var marker_00226694e5344e64a6a53026a3afae8d = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_f725634784ab43ebaba1973a266ad482 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_00226694e5344e64a6a53026a3afae8d.setIcon(icon_f725634784ab43ebaba1973a266ad482);
            
    
            var popup_c30eec16e31241ed82f25a20d5ec9b62 = L.popup({maxWidth: '300'
            
            });

            
                var html_b296e5fccbf24f77a4d31bf69cf9f588 = $(`<div id="html_b296e5fccbf24f77a4d31bf69cf9f588" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c30eec16e31241ed82f25a20d5ec9b62.setContent(html_b296e5fccbf24f77a4d31bf69cf9f588);
            

            marker_00226694e5344e64a6a53026a3afae8d.bindPopup(popup_c30eec16e31241ed82f25a20d5ec9b62)
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        var marker_d62b95a1a6ae41a384f4c6d560951db4 = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_1d2ac9ea199442c68082b7401c12f9c0 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_d62b95a1a6ae41a384f4c6d560951db4.setIcon(icon_1d2ac9ea199442c68082b7401c12f9c0);
            
    
            var popup_af8954d885ab4bed94eaa7ab661c2346 = L.popup({maxWidth: '300'
            
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                var html_975180d36dac4024a9b3ccc779371cff = $(`<div id="html_975180d36dac4024a9b3ccc779371cff" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_af8954d885ab4bed94eaa7ab661c2346.setContent(html_975180d36dac4024a9b3ccc779371cff);
            

            marker_d62b95a1a6ae41a384f4c6d560951db4.bindPopup(popup_af8954d885ab4bed94eaa7ab661c2346)
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        var marker_82cfedc2a3394bf88f4c6c7b8eae26bb = L.marker(
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                var icon_83cdae3c06324c5b943ac0c4c606de2e = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_82cfedc2a3394bf88f4c6c7b8eae26bb.setIcon(icon_83cdae3c06324c5b943ac0c4c606de2e);
            
    
            var popup_e33cdd6b51e34f6c9369553aecf71cea = L.popup({maxWidth: '300'
            
            });

            
                var html_e6c92261dc0644e7a67c08f8617109cc = $(`<div id="html_e6c92261dc0644e7a67c08f8617109cc" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_e33cdd6b51e34f6c9369553aecf71cea.setContent(html_e6c92261dc0644e7a67c08f8617109cc);
            

            marker_82cfedc2a3394bf88f4c6c7b8eae26bb.bindPopup(popup_e33cdd6b51e34f6c9369553aecf71cea)
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        var marker_289a915f16824738a9845abb3fea3e35 = L.marker(
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_3bdddabd17f043368c5148c9e4338655 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_289a915f16824738a9845abb3fea3e35.setIcon(icon_3bdddabd17f043368c5148c9e4338655);
            
    
            var popup_dbe80e22b84944b0a7d6f7a1b91c8316 = L.popup({maxWidth: '300'
            
            });

            
                var html_6ae58a956fbb416d90c2d87c7060b807 = $(`<div id="html_6ae58a956fbb416d90c2d87c7060b807" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_dbe80e22b84944b0a7d6f7a1b91c8316.setContent(html_6ae58a956fbb416d90c2d87c7060b807);
            

            marker_289a915f16824738a9845abb3fea3e35.bindPopup(popup_dbe80e22b84944b0a7d6f7a1b91c8316)
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        var marker_2de03118ead74461ae83cab1dfd8c23f = L.marker(
            [50.86, -3.239],
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_1d4f6e17dacb43faaaf52ecc265b78dd = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_2de03118ead74461ae83cab1dfd8c23f.setIcon(icon_1d4f6e17dacb43faaaf52ecc265b78dd);
            
    
            var popup_df08b2a4232948b48a13c208e7019cd8 = L.popup({maxWidth: '300'
            
            });

            
                var html_58189651921643f598968d4f6fe96f4d = $(`<div id="html_58189651921643f598968d4f6fe96f4d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_df08b2a4232948b48a13c208e7019cd8.setContent(html_58189651921643f598968d4f6fe96f4d);
            

            marker_2de03118ead74461ae83cab1dfd8c23f.bindPopup(popup_df08b2a4232948b48a13c208e7019cd8)
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        var marker_27397d377f3a4e7980f03035ef95dc69 = L.marker(
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            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_1b1c7fcc576a4c8b90a8ac2a5a4a4186 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_27397d377f3a4e7980f03035ef95dc69.setIcon(icon_1b1c7fcc576a4c8b90a8ac2a5a4a4186);
            
    
            var popup_4f937208250245039686b76c53397890 = L.popup({maxWidth: '300'
            
            });

            
                var html_2576bedb7e9b4689a4e373a2f7ba04eb = $(`<div id="html_2576bedb7e9b4689a4e373a2f7ba04eb" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4f937208250245039686b76c53397890.setContent(html_2576bedb7e9b4689a4e373a2f7ba04eb);
            

            marker_27397d377f3a4e7980f03035ef95dc69.bindPopup(popup_4f937208250245039686b76c53397890)
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        var marker_118b444339d74ed4acf3a62656a9434a = L.marker(
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_7a5a1c7f38f54a5cb727055a67f03f2c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_118b444339d74ed4acf3a62656a9434a.setIcon(icon_7a5a1c7f38f54a5cb727055a67f03f2c);
            
    
            var popup_9a2b3c4b22bb409880adb405a25119a6 = L.popup({maxWidth: '300'
            
            });

            
                var html_f4b8b6d3fd4545be90df5b2bea349b44 = $(`<div id="html_f4b8b6d3fd4545be90df5b2bea349b44" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_9a2b3c4b22bb409880adb405a25119a6.setContent(html_f4b8b6d3fd4545be90df5b2bea349b44);
            

            marker_118b444339d74ed4acf3a62656a9434a.bindPopup(popup_9a2b3c4b22bb409880adb405a25119a6)
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        var marker_f0dc1c76242a41578868b429466d0c40 = L.marker(
            [51.087, -3.608],
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_1a58acff917d4a15bf67487e441b7f39 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_f0dc1c76242a41578868b429466d0c40.setIcon(icon_1a58acff917d4a15bf67487e441b7f39);
            
    
            var popup_6763abd2c95e4cd5a49bb0ed322f3a6b = L.popup({maxWidth: '300'
            
            });

            
                var html_3c7dc8fdc0e44a76990541ea4f396d1a = $(`<div id="html_3c7dc8fdc0e44a76990541ea4f396d1a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_6763abd2c95e4cd5a49bb0ed322f3a6b.setContent(html_3c7dc8fdc0e44a76990541ea4f396d1a);
            

            marker_f0dc1c76242a41578868b429466d0c40.bindPopup(popup_6763abd2c95e4cd5a49bb0ed322f3a6b)
            ;

            
        
    
        var marker_663271d855f348d68191b12f0e9b2b94 = L.marker(
            [51.201, -1.805],
            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_b9bea9bbc01941b28d394b5a0b0b7b30 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_663271d855f348d68191b12f0e9b2b94.setIcon(icon_b9bea9bbc01941b28d394b5a0b0b7b30);
            
    
            var popup_e0fb42bd2b144083a3c8c19a0664c733 = L.popup({maxWidth: '300'
            
            });

            
                var html_a5dd237bb40f48f18589d53d6faa448a = $(`<div id="html_a5dd237bb40f48f18589d53d6faa448a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_e0fb42bd2b144083a3c8c19a0664c733.setContent(html_a5dd237bb40f48f18589d53d6faa448a);
            

            marker_663271d855f348d68191b12f0e9b2b94.bindPopup(popup_e0fb42bd2b144083a3c8c19a0664c733)
            ;

            
        
    
        var marker_0d72558738ca4635be82689d317c5612 = L.marker(
            [51.161, -1.754],
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                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_2415f300e5cf42aa9588c41c76bba061 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_0d72558738ca4635be82689d317c5612.setIcon(icon_2415f300e5cf42aa9588c41c76bba061);
            
    
            var popup_98c6bf1de0c94597b5aada5c121067f1 = L.popup({maxWidth: '300'
            
            });

            
                var html_27c9d8bdda4b4259a28539462bc45093 = $(`<div id="html_27c9d8bdda4b4259a28539462bc45093" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_98c6bf1de0c94597b5aada5c121067f1.setContent(html_27c9d8bdda4b4259a28539462bc45093);
            

            marker_0d72558738ca4635be82689d317c5612.bindPopup(popup_98c6bf1de0c94597b5aada5c121067f1)
            ;

            
        
    
        var marker_f61ba845d2ac4629808c50fac948b74c = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_123a4157aaa741859594f06165eb5d21 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f61ba845d2ac4629808c50fac948b74c.setIcon(icon_123a4157aaa741859594f06165eb5d21);
            
    
            var popup_1aaee24dd9b4488fab07e4184e9f9bec = L.popup({maxWidth: '300'
            
            });

            
                var html_c237f5982ee74f7db10f8544d5bc3510 = $(`<div id="html_c237f5982ee74f7db10f8544d5bc3510" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1aaee24dd9b4488fab07e4184e9f9bec.setContent(html_c237f5982ee74f7db10f8544d5bc3510);
            

            marker_f61ba845d2ac4629808c50fac948b74c.bindPopup(popup_1aaee24dd9b4488fab07e4184e9f9bec)
            ;

            
        
    
        var marker_f990dade02b842e7801b409b02fdf350 = L.marker(
            [56.377, -2.862],
            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_8ed8b47d7a104c519772a28749f6b036 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f990dade02b842e7801b409b02fdf350.setIcon(icon_8ed8b47d7a104c519772a28749f6b036);
            
    
            var popup_fc5282eaaaae4da18b43cf0462219c10 = L.popup({maxWidth: '300'
            
            });

            
                var html_04caaf2251304caa9d6e3189fba8cd52 = $(`<div id="html_04caaf2251304caa9d6e3189fba8cd52" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_fc5282eaaaae4da18b43cf0462219c10.setContent(html_04caaf2251304caa9d6e3189fba8cd52);
            

            marker_f990dade02b842e7801b409b02fdf350.bindPopup(popup_fc5282eaaaae4da18b43cf0462219c10)
            ;

            
        
    
        var marker_fdb543cf56df468f975a481fbbfb5d28 = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_6fe483de0d6148dc9d71e1a95acca11a = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_fdb543cf56df468f975a481fbbfb5d28.setIcon(icon_6fe483de0d6148dc9d71e1a95acca11a);
            
    
            var popup_1965bf99ada640c0adbd7512f6c9c84c = L.popup({maxWidth: '300'
            
            });

            
                var html_c47797dcfaa44f4d88f60288517af4f5 = $(`<div id="html_c47797dcfaa44f4d88f60288517af4f5" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1965bf99ada640c0adbd7512f6c9c84c.setContent(html_c47797dcfaa44f4d88f60288517af4f5);
            

            marker_fdb543cf56df468f975a481fbbfb5d28.bindPopup(popup_1965bf99ada640c0adbd7512f6c9c84c)
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        var marker_31cf9e01f70e4188a77b8e7423f0933a = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_4e5ba4627a3141cf86029275cb54aeaa = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_31cf9e01f70e4188a77b8e7423f0933a.setIcon(icon_4e5ba4627a3141cf86029275cb54aeaa);
            
    
            var popup_5f935342d5e24d2eaf5e54ccc424fee3 = L.popup({maxWidth: '300'
            
            });

            
                var html_e004e7ba3e1c46dda9b804271ba4aea1 = $(`<div id="html_e004e7ba3e1c46dda9b804271ba4aea1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_5f935342d5e24d2eaf5e54ccc424fee3.setContent(html_e004e7ba3e1c46dda9b804271ba4aea1);
            

            marker_31cf9e01f70e4188a77b8e7423f0933a.bindPopup(popup_5f935342d5e24d2eaf5e54ccc424fee3)
            ;

            
        
    
        var marker_cf6731b970aa4b6dbe6ecd43514c7fca = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c207a77ad4c340cb91616aed3872626b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_cf6731b970aa4b6dbe6ecd43514c7fca.setIcon(icon_c207a77ad4c340cb91616aed3872626b);
            
    
            var popup_c67364011f844c5690ab978f6d3ab0a1 = L.popup({maxWidth: '300'
            
            });

            
                var html_f7739396e62e43359833d348efcf6c46 = $(`<div id="html_f7739396e62e43359833d348efcf6c46" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c67364011f844c5690ab978f6d3ab0a1.setContent(html_f7739396e62e43359833d348efcf6c46);
            

            marker_cf6731b970aa4b6dbe6ecd43514c7fca.bindPopup(popup_c67364011f844c5690ab978f6d3ab0a1)
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        var marker_73e682a2ca4444f4a1f85fe060fc72aa = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_000523d4efad4ed8b1063085e123c0ab = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_73e682a2ca4444f4a1f85fe060fc72aa.setIcon(icon_000523d4efad4ed8b1063085e123c0ab);
            
    
            var popup_0bd9737c303b4a279cb0f624deb93da8 = L.popup({maxWidth: '300'
            
            });

            
                var html_695dbd0a9ee54603aebc48236adcfcd4 = $(`<div id="html_695dbd0a9ee54603aebc48236adcfcd4" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_0bd9737c303b4a279cb0f624deb93da8.setContent(html_695dbd0a9ee54603aebc48236adcfcd4);
            

            marker_73e682a2ca4444f4a1f85fe060fc72aa.bindPopup(popup_0bd9737c303b4a279cb0f624deb93da8)
            ;

            
        
    
        var marker_b3e09ef8465941b9b0a8cd59a37c662b = L.marker(
            [53.088, 0.274],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_9cb986988ee940d2b2339509efc9612b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b3e09ef8465941b9b0a8cd59a37c662b.setIcon(icon_9cb986988ee940d2b2339509efc9612b);
            
    
            var popup_ae99788317a54b769a16e46cfbcc5b70 = L.popup({maxWidth: '300'
            
            });

            
                var html_95da0d83a2644363916c17ad4c676d1c = $(`<div id="html_95da0d83a2644363916c17ad4c676d1c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_b3e09ef8465941b9b0a8cd59a37c662b.bindPopup(popup_ae99788317a54b769a16e46cfbcc5b70)
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        var marker_bc84af1cebf04693a95aea29c3f850f9 = L.marker(
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                var icon_bdd706a36ae541f78a5c56e92a130774 = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_bc84af1cebf04693a95aea29c3f850f9.setIcon(icon_bdd706a36ae541f78a5c56e92a130774);
            
    
            var popup_03ee6ef406124b7cb92fc66cefe4d815 = L.popup({maxWidth: '300'
            
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                var html_e45bd8668d9f4091a30ddba0dbcb20eb = $(`<div id="html_e45bd8668d9f4091a30ddba0dbcb20eb" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
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            marker_bc84af1cebf04693a95aea29c3f850f9.bindPopup(popup_03ee6ef406124b7cb92fc66cefe4d815)
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        var marker_03533fc467f5495ea3823668931d70a9 = L.marker(
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                var icon_e23c2464ff8b4b53bdd7cde3b86548be = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_f51f1f80cb114f2eaa798730bebab470 = L.popup({maxWidth: '300'
            
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                var html_b6750f3b2c1543e3b318c97a39b48215 = $(`<div id="html_b6750f3b2c1543e3b318c97a39b48215" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f51f1f80cb114f2eaa798730bebab470.setContent(html_b6750f3b2c1543e3b318c97a39b48215);
            

            marker_03533fc467f5495ea3823668931d70a9.bindPopup(popup_f51f1f80cb114f2eaa798730bebab470)
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        var marker_e9755dcb3379420bb181ef9adf15643b = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_5c7054e1ec474827aa1badf12c65998c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_e9755dcb3379420bb181ef9adf15643b.setIcon(icon_5c7054e1ec474827aa1badf12c65998c);
            
    
            var popup_414dc76eca3d484a9133fa071dab0bb6 = L.popup({maxWidth: '300'
            
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                var html_72cc1d801a394cf0b31447e803419706 = $(`<div id="html_72cc1d801a394cf0b31447e803419706" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_414dc76eca3d484a9133fa071dab0bb6.setContent(html_72cc1d801a394cf0b31447e803419706);
            

            marker_e9755dcb3379420bb181ef9adf15643b.bindPopup(popup_414dc76eca3d484a9133fa071dab0bb6)
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        var marker_a866f97f781e4a56933fd3fb8ad69072 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_0893bf5884874b0594ac32b1ea1314e2 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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                marker_a866f97f781e4a56933fd3fb8ad69072.setIcon(icon_0893bf5884874b0594ac32b1ea1314e2);
            
    
            var popup_b19c91421f1b4b7d98d2e908947ae7d5 = L.popup({maxWidth: '300'
            
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                var html_dccb481dfd04497d9d335170b4dedfe6 = $(`<div id="html_dccb481dfd04497d9d335170b4dedfe6" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b19c91421f1b4b7d98d2e908947ae7d5.setContent(html_dccb481dfd04497d9d335170b4dedfe6);
            

            marker_a866f97f781e4a56933fd3fb8ad69072.bindPopup(popup_b19c91421f1b4b7d98d2e908947ae7d5)
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        var marker_10ef4f43684c410dbecad170541d9adc = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_a3381de24d9b4c9d97cfc9e90bd76fcb = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
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            var popup_72718417bb294c6ea1c5fc0f622cc023 = L.popup({maxWidth: '300'
            
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                var html_e31d2c8d681a4b338f1e5602e4b686f6 = $(`<div id="html_e31d2c8d681a4b338f1e5602e4b686f6" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_72718417bb294c6ea1c5fc0f622cc023.setContent(html_e31d2c8d681a4b338f1e5602e4b686f6);
            

            marker_10ef4f43684c410dbecad170541d9adc.bindPopup(popup_72718417bb294c6ea1c5fc0f622cc023)
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        var marker_7fa4e120ff9c4c10a3bc31e5864de9d1 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_0cba96dd25e948a885c87216d2bca4fe = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_7fa4e120ff9c4c10a3bc31e5864de9d1.setIcon(icon_0cba96dd25e948a885c87216d2bca4fe);
            
    
            var popup_9f24967f4b6a4e0bbb9d60cfdd1aab0c = L.popup({maxWidth: '300'
            
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                var html_88ea81c35dee43d39ffc09c60ecb4c55 = $(`<div id="html_88ea81c35dee43d39ffc09c60ecb4c55" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_9f24967f4b6a4e0bbb9d60cfdd1aab0c.setContent(html_88ea81c35dee43d39ffc09c60ecb4c55);
            

            marker_7fa4e120ff9c4c10a3bc31e5864de9d1.bindPopup(popup_9f24967f4b6a4e0bbb9d60cfdd1aab0c)
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        var marker_5a2319999d4543da81b303c41e6adcb0 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_d7c2797e9093455099b555f36f2b53cd = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_5a2319999d4543da81b303c41e6adcb0.setIcon(icon_d7c2797e9093455099b555f36f2b53cd);
            
    
            var popup_828c0143ec344d2789f1dffc49c0e282 = L.popup({maxWidth: '300'
            
            });

            
                var html_9347f704990b472a87a75e9af626ed33 = $(`<div id="html_9347f704990b472a87a75e9af626ed33" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_828c0143ec344d2789f1dffc49c0e282.setContent(html_9347f704990b472a87a75e9af626ed33);
            

            marker_5a2319999d4543da81b303c41e6adcb0.bindPopup(popup_828c0143ec344d2789f1dffc49c0e282)
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        var marker_c92443b36bab4095be0168ec1c96fa96 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e9c0bd39be2840f5b1a5bdeb7ede1ebb = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_c92443b36bab4095be0168ec1c96fa96.setIcon(icon_e9c0bd39be2840f5b1a5bdeb7ede1ebb);
            
    
            var popup_3294db02a7c54f598c8599452d8629fe = L.popup({maxWidth: '300'
            
            });

            
                var html_05749b2a31c44abfa5c4c0a2e714a4ce = $(`<div id="html_05749b2a31c44abfa5c4c0a2e714a4ce" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_3294db02a7c54f598c8599452d8629fe.setContent(html_05749b2a31c44abfa5c4c0a2e714a4ce);
            

            marker_c92443b36bab4095be0168ec1c96fa96.bindPopup(popup_3294db02a7c54f598c8599452d8629fe)
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        var marker_91b737799b0f47779b9fe27c732c5fc3 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e4a4681adef940409bfd6b935f7bb948 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_91b737799b0f47779b9fe27c732c5fc3.setIcon(icon_e4a4681adef940409bfd6b935f7bb948);
            
    
            var popup_84fb1174352e46ebac1d169190ae1d29 = L.popup({maxWidth: '300'
            
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                var html_bbcec6ee77664eae80d2cb40a95ddcc4 = $(`<div id="html_bbcec6ee77664eae80d2cb40a95ddcc4" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_84fb1174352e46ebac1d169190ae1d29.setContent(html_bbcec6ee77664eae80d2cb40a95ddcc4);
            

            marker_91b737799b0f47779b9fe27c732c5fc3.bindPopup(popup_84fb1174352e46ebac1d169190ae1d29)
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        var marker_3208081c85864ca29064a12ba9c3f918 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_25b99b5b61c64eac9d94bdc29c7c8ba4 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_3208081c85864ca29064a12ba9c3f918.setIcon(icon_25b99b5b61c64eac9d94bdc29c7c8ba4);
            
    
            var popup_77ede085cb3a4895ab92e7225453bd8f = L.popup({maxWidth: '300'
            
            });

            
                var html_77a12169c66d47e2a2c6149c0f32a7a3 = $(`<div id="html_77a12169c66d47e2a2c6149c0f32a7a3" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_77ede085cb3a4895ab92e7225453bd8f.setContent(html_77a12169c66d47e2a2c6149c0f32a7a3);
            

            marker_3208081c85864ca29064a12ba9c3f918.bindPopup(popup_77ede085cb3a4895ab92e7225453bd8f)
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        var marker_97de807883c1422db03dbc943b8ac852 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_66ba3fb9580948009e69a8f53243e971 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_97de807883c1422db03dbc943b8ac852.setIcon(icon_66ba3fb9580948009e69a8f53243e971);
            
    
            var popup_b0ae6e2f95bb4e6c8254b77687656ba5 = L.popup({maxWidth: '300'
            
            });

            
                var html_9ad2b4c176974424b9994d033d7b01d8 = $(`<div id="html_9ad2b4c176974424b9994d033d7b01d8" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b0ae6e2f95bb4e6c8254b77687656ba5.setContent(html_9ad2b4c176974424b9994d033d7b01d8);
            

            marker_97de807883c1422db03dbc943b8ac852.bindPopup(popup_b0ae6e2f95bb4e6c8254b77687656ba5)
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        var marker_c9759cba27394717af57917a96bd2d8e = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_a5725b4ad12b4db09775c34bdb998e02 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c9759cba27394717af57917a96bd2d8e.setIcon(icon_a5725b4ad12b4db09775c34bdb998e02);
            
    
            var popup_4ab00c080b9040d89cf6f804c4a86e45 = L.popup({maxWidth: '300'
            
            });

            
                var html_f4117494c45740f9bc558dbe1d2d658b = $(`<div id="html_f4117494c45740f9bc558dbe1d2d658b" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4ab00c080b9040d89cf6f804c4a86e45.setContent(html_f4117494c45740f9bc558dbe1d2d658b);
            

            marker_c9759cba27394717af57917a96bd2d8e.bindPopup(popup_4ab00c080b9040d89cf6f804c4a86e45)
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        var marker_eab35d6522fb434d8fae33a6c5195c9f = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_d79613a0eac247df935f0edbf5fb8a56 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_eab35d6522fb434d8fae33a6c5195c9f.setIcon(icon_d79613a0eac247df935f0edbf5fb8a56);
            
    
            var popup_f4c7221ea34549f5a1a16c07717628b5 = L.popup({maxWidth: '300'
            
            });

            
                var html_0466d2a816e349d8b52c903e4b76f345 = $(`<div id="html_0466d2a816e349d8b52c903e4b76f345" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f4c7221ea34549f5a1a16c07717628b5.setContent(html_0466d2a816e349d8b52c903e4b76f345);
            

            marker_eab35d6522fb434d8fae33a6c5195c9f.bindPopup(popup_f4c7221ea34549f5a1a16c07717628b5)
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        var marker_a5d27dddf6c64a9b8935490e60fb89c6 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_26ab92131ed043b3ba2a54700a8e3319 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_a5d27dddf6c64a9b8935490e60fb89c6.setIcon(icon_26ab92131ed043b3ba2a54700a8e3319);
            
    
            var popup_ada39add388d466889f5dee05c2600e2 = L.popup({maxWidth: '300'
            
            });

            
                var html_e3a809e4d7714dd1b2dcf4d524ef5c87 = $(`<div id="html_e3a809e4d7714dd1b2dcf4d524ef5c87" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_ada39add388d466889f5dee05c2600e2.setContent(html_e3a809e4d7714dd1b2dcf4d524ef5c87);
            

            marker_a5d27dddf6c64a9b8935490e60fb89c6.bindPopup(popup_ada39add388d466889f5dee05c2600e2)
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        var marker_6e33d6f63b6c4d2ba34ac7b25c4b3706 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c4a4cf7b430e4085b8d4beb4043a9fe6 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_6e33d6f63b6c4d2ba34ac7b25c4b3706.setIcon(icon_c4a4cf7b430e4085b8d4beb4043a9fe6);
            
    
            var popup_49d02d44dad04f00a3f20aed92387b1e = L.popup({maxWidth: '300'
            
            });

            
                var html_7d4fc68e637f4f40a9ba37ceb7af0825 = $(`<div id="html_7d4fc68e637f4f40a9ba37ceb7af0825" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_49d02d44dad04f00a3f20aed92387b1e.setContent(html_7d4fc68e637f4f40a9ba37ceb7af0825);
            

            marker_6e33d6f63b6c4d2ba34ac7b25c4b3706.bindPopup(popup_49d02d44dad04f00a3f20aed92387b1e)
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        var marker_b8ba32850d844f90b3e6a1f109573a37 = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_d652b55611a14848abe7cd8293d8b78d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_b8ba32850d844f90b3e6a1f109573a37.setIcon(icon_d652b55611a14848abe7cd8293d8b78d);
            
    
            var popup_606aad9d03574fe7a607f877359124f1 = L.popup({maxWidth: '300'
            
            });

            
                var html_b0c68f50adfa45eb845b0febadbc1702 = $(`<div id="html_b0c68f50adfa45eb845b0febadbc1702" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_606aad9d03574fe7a607f877359124f1.setContent(html_b0c68f50adfa45eb845b0febadbc1702);
            

            marker_b8ba32850d844f90b3e6a1f109573a37.bindPopup(popup_606aad9d03574fe7a607f877359124f1)
            ;

            
        
    
        var marker_71c540fd80044277b3ad5124ea730a06 = L.marker(
            [55.515, -4.585],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_93f1ddf63dd0456a85c8faad9c58b6c3 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_71c540fd80044277b3ad5124ea730a06.setIcon(icon_93f1ddf63dd0456a85c8faad9c58b6c3);
            
    
            var popup_578f4e3c072b477b9e5d96b3f5a8355a = L.popup({maxWidth: '300'
            
            });

            
                var html_16f3867c73ef4c6da4db7d4554676cea = $(`<div id="html_16f3867c73ef4c6da4db7d4554676cea" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_578f4e3c072b477b9e5d96b3f5a8355a.setContent(html_16f3867c73ef4c6da4db7d4554676cea);
            

            marker_71c540fd80044277b3ad5124ea730a06.bindPopup(popup_578f4e3c072b477b9e5d96b3f5a8355a)
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        var marker_1b5fa26cbc8f458ca974ec470ee11104 = L.marker(
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_198d83267e494d5fb8d98d28d8140038 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_1b5fa26cbc8f458ca974ec470ee11104.setIcon(icon_198d83267e494d5fb8d98d28d8140038);
            
    
            var popup_f62a59c983764b11ac8d64d1866c31c3 = L.popup({maxWidth: '300'
            
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                var html_ca6c6a56cd124c968fc382608b2492b2 = $(`<div id="html_ca6c6a56cd124c968fc382608b2492b2" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f62a59c983764b11ac8d64d1866c31c3.setContent(html_ca6c6a56cd124c968fc382608b2492b2);
            

            marker_1b5fa26cbc8f458ca974ec470ee11104.bindPopup(popup_f62a59c983764b11ac8d64d1866c31c3)
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        var marker_3fc4a4ceca614191a8759fba0a3e027d = L.marker(
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            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_75b417a65843418688866b2b484489b9 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_3fc4a4ceca614191a8759fba0a3e027d.setIcon(icon_75b417a65843418688866b2b484489b9);
            
    
            var popup_3caf5dff16c84521bff51cf18f0b68eb = L.popup({maxWidth: '300'
            
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                var html_c099ca3ec40947a59847c6d34dbb21f1 = $(`<div id="html_c099ca3ec40947a59847c6d34dbb21f1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_3caf5dff16c84521bff51cf18f0b68eb.setContent(html_c099ca3ec40947a59847c6d34dbb21f1);
            

            marker_3fc4a4ceca614191a8759fba0a3e027d.bindPopup(popup_3caf5dff16c84521bff51cf18f0b68eb)
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        var marker_4b5bb9de98a94729b679e06f1b7b10db = L.marker(
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            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_8c31ce7a05ea4f00953a3847924aa7b0 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_4b5bb9de98a94729b679e06f1b7b10db.setIcon(icon_8c31ce7a05ea4f00953a3847924aa7b0);
            
    
            var popup_923c9fc05c5f425f9c0d0f87397a9483 = L.popup({maxWidth: '300'
            
            });

            
                var html_8f62df01e8d749d382ccf30afbf0e46e = $(`<div id="html_8f62df01e8d749d382ccf30afbf0e46e" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_923c9fc05c5f425f9c0d0f87397a9483.setContent(html_8f62df01e8d749d382ccf30afbf0e46e);
            

            marker_4b5bb9de98a94729b679e06f1b7b10db.bindPopup(popup_923c9fc05c5f425f9c0d0f87397a9483)
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        var marker_9b1999dc543a4ec99a5b30dd521e52cf = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_fa5b1e248ca9423c99739f30034e60ef = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_9b1999dc543a4ec99a5b30dd521e52cf.setIcon(icon_fa5b1e248ca9423c99739f30034e60ef);
            
    
            var popup_1963ba90cc634c0ea1ab20d447a1179a = L.popup({maxWidth: '300'
            
            });

            
                var html_62902bdf03b0428da6930ee4e405a8b6 = $(`<div id="html_62902bdf03b0428da6930ee4e405a8b6" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1963ba90cc634c0ea1ab20d447a1179a.setContent(html_62902bdf03b0428da6930ee4e405a8b6);
            

            marker_9b1999dc543a4ec99a5b30dd521e52cf.bindPopup(popup_1963ba90cc634c0ea1ab20d447a1179a)
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        var marker_49417d950df14539b28bbaaade5499c3 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_12111c7f696c494a8fe01d14573fc60c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_49417d950df14539b28bbaaade5499c3.setIcon(icon_12111c7f696c494a8fe01d14573fc60c);
            
    
            var popup_f9144b56c7b340819e6a2172462e2069 = L.popup({maxWidth: '300'
            
            });

            
                var html_0f99a87922bb47d49e19c15f1d74ae8f = $(`<div id="html_0f99a87922bb47d49e19c15f1d74ae8f" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f9144b56c7b340819e6a2172462e2069.setContent(html_0f99a87922bb47d49e19c15f1d74ae8f);
            

            marker_49417d950df14539b28bbaaade5499c3.bindPopup(popup_f9144b56c7b340819e6a2172462e2069)
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        var marker_317ae00f5e91409dab4bcbe7ef80226f = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_0bcf5375ac684beb8298d690ad3daceb = L.AwesomeMarkers.icon({
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                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_317ae00f5e91409dab4bcbe7ef80226f.setIcon(icon_0bcf5375ac684beb8298d690ad3daceb);
            
    
            var popup_17f1f349a5004b29a0ca3a316460fea3 = L.popup({maxWidth: '300'
            
            });

            
                var html_97394738684541cbbd1b79284d947f2e = $(`<div id="html_97394738684541cbbd1b79284d947f2e" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_17f1f349a5004b29a0ca3a316460fea3.setContent(html_97394738684541cbbd1b79284d947f2e);
            

            marker_317ae00f5e91409dab4bcbe7ef80226f.bindPopup(popup_17f1f349a5004b29a0ca3a316460fea3)
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        var marker_37bdbab545df4b1f99ee0e4c94f25f89 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_56d4711494d54ce888b9b34c285d9d8e = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_37bdbab545df4b1f99ee0e4c94f25f89.setIcon(icon_56d4711494d54ce888b9b34c285d9d8e);
            
    
            var popup_72a785c34d9c49d79468be98274d19da = L.popup({maxWidth: '300'
            
            });

            
                var html_0248be414f5b4bb798bade1c79b6cbbf = $(`<div id="html_0248be414f5b4bb798bade1c79b6cbbf" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_72a785c34d9c49d79468be98274d19da.setContent(html_0248be414f5b4bb798bade1c79b6cbbf);
            

            marker_37bdbab545df4b1f99ee0e4c94f25f89.bindPopup(popup_72a785c34d9c49d79468be98274d19da)
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        var marker_ac36d56dba5b4fb697e6061749ac9c57 = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_76bb275cc3524ed7877a26575e1d56a1 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_ac36d56dba5b4fb697e6061749ac9c57.setIcon(icon_76bb275cc3524ed7877a26575e1d56a1);
            
    
            var popup_2dde2572ede5445f8ae8f143c0bd05a2 = L.popup({maxWidth: '300'
            
            });

            
                var html_075d70d53c1c4927bb2eac5f1db1b43d = $(`<div id="html_075d70d53c1c4927bb2eac5f1db1b43d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2dde2572ede5445f8ae8f143c0bd05a2.setContent(html_075d70d53c1c4927bb2eac5f1db1b43d);
            

            marker_ac36d56dba5b4fb697e6061749ac9c57.bindPopup(popup_2dde2572ede5445f8ae8f143c0bd05a2)
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        var marker_c4e41320a1684c49b275cd85c523317d = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_143d86130e4c4f3d8c965a7b649aa45f = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_c4e41320a1684c49b275cd85c523317d.setIcon(icon_143d86130e4c4f3d8c965a7b649aa45f);
            
    
            var popup_6eb40afbb21648c9b1f18d7a2ea4b535 = L.popup({maxWidth: '300'
            
            });

            
                var html_8b243e3125c74ab98589579862e68bbe = $(`<div id="html_8b243e3125c74ab98589579862e68bbe" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_6eb40afbb21648c9b1f18d7a2ea4b535.setContent(html_8b243e3125c74ab98589579862e68bbe);
            

            marker_c4e41320a1684c49b275cd85c523317d.bindPopup(popup_6eb40afbb21648c9b1f18d7a2ea4b535)
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        var marker_1c05b081c246409e856b3e5c12fc0b83 = L.marker(
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            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_eb0689478e4a434ba013f83fccc8a42d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_1c05b081c246409e856b3e5c12fc0b83.setIcon(icon_eb0689478e4a434ba013f83fccc8a42d);
            
    
            var popup_bf1e468a996146f4b948df36ba085e34 = L.popup({maxWidth: '300'
            
            });

            
                var html_d3e424d7f541401eba917ae45356ace1 = $(`<div id="html_d3e424d7f541401eba917ae45356ace1" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_bf1e468a996146f4b948df36ba085e34.setContent(html_d3e424d7f541401eba917ae45356ace1);
            

            marker_1c05b081c246409e856b3e5c12fc0b83.bindPopup(popup_bf1e468a996146f4b948df36ba085e34)
            ;

            
        
    
        var marker_8ada4cdac45e4699af6bede88e50c1fe = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_7e695e0cac294a22945c20d4d8d02e60 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_8ada4cdac45e4699af6bede88e50c1fe.setIcon(icon_7e695e0cac294a22945c20d4d8d02e60);
            
    
            var popup_b5403a968a8041e5b30fed5be56eb8b0 = L.popup({maxWidth: '300'
            
            });

            
                var html_4fa842736d844ea1aa806fd1de5ef1af = $(`<div id="html_4fa842736d844ea1aa806fd1de5ef1af" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b5403a968a8041e5b30fed5be56eb8b0.setContent(html_4fa842736d844ea1aa806fd1de5ef1af);
            

            marker_8ada4cdac45e4699af6bede88e50c1fe.bindPopup(popup_b5403a968a8041e5b30fed5be56eb8b0)
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        var marker_0240b92a7b3345e1a01bb9efab6f59cd = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_310a51c924124fd88fd3fc7fb2b4878b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_0240b92a7b3345e1a01bb9efab6f59cd.setIcon(icon_310a51c924124fd88fd3fc7fb2b4878b);
            
    
            var popup_1b2d9afa5ab6428bbbc7961f6e1ddc78 = L.popup({maxWidth: '300'
            
            });

            
                var html_d7b581be2c5d4b9cbb44da65ebcde930 = $(`<div id="html_d7b581be2c5d4b9cbb44da65ebcde930" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1b2d9afa5ab6428bbbc7961f6e1ddc78.setContent(html_d7b581be2c5d4b9cbb44da65ebcde930);
            

            marker_0240b92a7b3345e1a01bb9efab6f59cd.bindPopup(popup_1b2d9afa5ab6428bbbc7961f6e1ddc78)
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        var marker_2955a927dae740e5ad822525f3d93e36 = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c20eb964b15f4d65bf4f46512f222cd4 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_2955a927dae740e5ad822525f3d93e36.setIcon(icon_c20eb964b15f4d65bf4f46512f222cd4);
            
    
            var popup_0914ac61341f4231b8c943aeb215a1e4 = L.popup({maxWidth: '300'
            
            });

            
                var html_3b624691f36843bd8a28e41471f4aded = $(`<div id="html_3b624691f36843bd8a28e41471f4aded" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_0914ac61341f4231b8c943aeb215a1e4.setContent(html_3b624691f36843bd8a28e41471f4aded);
            

            marker_2955a927dae740e5ad822525f3d93e36.bindPopup(popup_0914ac61341f4231b8c943aeb215a1e4)
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        var marker_e7828168260547b6b3d4cb91fecc0a81 = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_9130cb82e38a4640b0ff97164a663758 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_e7828168260547b6b3d4cb91fecc0a81.setIcon(icon_9130cb82e38a4640b0ff97164a663758);
            
    
            var popup_b1120d7e4bc34c6e968d62c50cc9e314 = L.popup({maxWidth: '300'
            
            });

            
                var html_cded79a4577c487a8067d8f5ffb5f72b = $(`<div id="html_cded79a4577c487a8067d8f5ffb5f72b" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b1120d7e4bc34c6e968d62c50cc9e314.setContent(html_cded79a4577c487a8067d8f5ffb5f72b);
            

            marker_e7828168260547b6b3d4cb91fecc0a81.bindPopup(popup_b1120d7e4bc34c6e968d62c50cc9e314)
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        var marker_4f752bf33a9a4cf89e3283e809a9d484 = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c266fc734295493f9f4f71f19401b001 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_4f752bf33a9a4cf89e3283e809a9d484.setIcon(icon_c266fc734295493f9f4f71f19401b001);
            
    
            var popup_42af41e00ad2496eb8df0c50385658a7 = L.popup({maxWidth: '300'
            
            });

            
                var html_3c788e444ea34648a96d7da10f99a571 = $(`<div id="html_3c788e444ea34648a96d7da10f99a571" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_42af41e00ad2496eb8df0c50385658a7.setContent(html_3c788e444ea34648a96d7da10f99a571);
            

            marker_4f752bf33a9a4cf89e3283e809a9d484.bindPopup(popup_42af41e00ad2496eb8df0c50385658a7)
            ;

            
        
    
        var marker_0da9a8bd5ba54f33a5ea97b8ef4db0a3 = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_d67a6cb72e5c4f85b33211cb6a76a0eb = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_0da9a8bd5ba54f33a5ea97b8ef4db0a3.setIcon(icon_d67a6cb72e5c4f85b33211cb6a76a0eb);
            
    
            var popup_5cff7b56af60407881f98fbf884d2d07 = L.popup({maxWidth: '300'
            
            });

            
                var html_02089781ef2f495989ed8669758b8c6b = $(`<div id="html_02089781ef2f495989ed8669758b8c6b" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_5cff7b56af60407881f98fbf884d2d07.setContent(html_02089781ef2f495989ed8669758b8c6b);
            

            marker_0da9a8bd5ba54f33a5ea97b8ef4db0a3.bindPopup(popup_5cff7b56af60407881f98fbf884d2d07)
            ;

            
        
    
        var marker_f6dcb9f6579c45b8ba2e41f7457f0748 = L.marker(
            [57.4175, -5.689],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_08612112d63949a9a6a33da5dcf23bfc = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f6dcb9f6579c45b8ba2e41f7457f0748.setIcon(icon_08612112d63949a9a6a33da5dcf23bfc);
            
    
            var popup_556513b514544a8893af32eaa94b1e54 = L.popup({maxWidth: '300'
            
            });

            
                var html_34c18117afd4440cb9686f19f413bbee = $(`<div id="html_34c18117afd4440cb9686f19f413bbee" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_556513b514544a8893af32eaa94b1e54.setContent(html_34c18117afd4440cb9686f19f413bbee);
            

            marker_f6dcb9f6579c45b8ba2e41f7457f0748.bindPopup(popup_556513b514544a8893af32eaa94b1e54)
            ;

            
        
    
        var marker_cb112d028e374e28b78ba6e83870a156 = L.marker(
            [50.218, -5.33],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_f23bff70902b49cdb62d9ee48653a37d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_cb112d028e374e28b78ba6e83870a156.setIcon(icon_f23bff70902b49cdb62d9ee48653a37d);
            
    
            var popup_e1ada2f58dfd43b59b01edf9e6a77e6e = L.popup({maxWidth: '300'
            
            });

            
                var html_9ed1f25991fc4f99a4bbb60f826cd76d = $(`<div id="html_9ed1f25991fc4f99a4bbb60f826cd76d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_e1ada2f58dfd43b59b01edf9e6a77e6e.setContent(html_9ed1f25991fc4f99a4bbb60f826cd76d);
            

            marker_cb112d028e374e28b78ba6e83870a156.bindPopup(popup_e1ada2f58dfd43b59b01edf9e6a77e6e)
            ;

            
        
    
        var marker_4c46a40d67f247639aaefcf974ec7ea9 = L.marker(
            [50.577, -1.297],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_28b02d0333bc4e9c9d8f383285376a35 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_4c46a40d67f247639aaefcf974ec7ea9.setIcon(icon_28b02d0333bc4e9c9d8f383285376a35);
            
    
            var popup_1fdd9690e6144e0f9ea2685fb486d25b = L.popup({maxWidth: '300'
            
            });

            
                var html_1b9c394eaebd473fac9489e86d7758fd = $(`<div id="html_1b9c394eaebd473fac9489e86d7758fd" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1fdd9690e6144e0f9ea2685fb486d25b.setContent(html_1b9c394eaebd473fac9489e86d7758fd);
            

            marker_4c46a40d67f247639aaefcf974ec7ea9.bindPopup(popup_1fdd9690e6144e0f9ea2685fb486d25b)
            ;

            
        
    
        var marker_32543a7ae94849d1a5e872ce00fc5de1 = L.marker(
            [50.815, -0.923],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_ec14f688b1ac47a081fe4a99d4fccf73 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_32543a7ae94849d1a5e872ce00fc5de1.setIcon(icon_ec14f688b1ac47a081fe4a99d4fccf73);
            
    
            var popup_6edc491993d24c21818e386801fbf129 = L.popup({maxWidth: '300'
            
            });

            
                var html_0e8c493da9624861a148d403d99e3c12 = $(`<div id="html_0e8c493da9624861a148d403d99e3c12" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_6edc491993d24c21818e386801fbf129.setContent(html_0e8c493da9624861a148d403d99e3c12);
            

            marker_32543a7ae94849d1a5e872ce00fc5de1.bindPopup(popup_6edc491993d24c21818e386801fbf129)
            ;

            
        
    
        var marker_08ba79cc95e1480398ea02b2e5072d48 = L.marker(
            [50.89, 0.319],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_17c1dfa7a22b4a6da436a4071a83b8d4 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_08ba79cc95e1480398ea02b2e5072d48.setIcon(icon_17c1dfa7a22b4a6da436a4071a83b8d4);
            
    
            var popup_c258371cc9634ff4a530b47b8c9bcba1 = L.popup({maxWidth: '300'
            
            });

            
                var html_3a1229ecc66f420bbc585b5bf1d60bc8 = $(`<div id="html_3a1229ecc66f420bbc585b5bf1d60bc8" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c258371cc9634ff4a530b47b8c9bcba1.setContent(html_3a1229ecc66f420bbc585b5bf1d60bc8);
            

            marker_08ba79cc95e1480398ea02b2e5072d48.bindPopup(popup_c258371cc9634ff4a530b47b8c9bcba1)
            ;

            
        
    
        var marker_25c8e30f128e43678f4c94bdb12b7620 = L.marker(
            [54.707, -7.577],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_fe9daec6bc2f460dbf230bbcff0b451d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_25c8e30f128e43678f4c94bdb12b7620.setIcon(icon_fe9daec6bc2f460dbf230bbcff0b451d);
            
    
            var popup_f2f832a10a514f758a625c5cc5ebd220 = L.popup({maxWidth: '300'
            
            });

            
                var html_81d7a94c449a490ab337ce8bc896ac6c = $(`<div id="html_81d7a94c449a490ab337ce8bc896ac6c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f2f832a10a514f758a625c5cc5ebd220.setContent(html_81d7a94c449a490ab337ce8bc896ac6c);
            

            marker_25c8e30f128e43678f4c94bdb12b7620.bindPopup(popup_f2f832a10a514f758a625c5cc5ebd220)
            ;

            
        
    
        var marker_850c89026a7949028101c6f11d9e169f = L.marker(
            [51.799, -8.25],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_cad55bfd82c1453cba7314e074e1493b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_850c89026a7949028101c6f11d9e169f.setIcon(icon_cad55bfd82c1453cba7314e074e1493b);
            
    
            var popup_797f035c0d604515a2ae387b73e477d1 = L.popup({maxWidth: '300'
            
            });

            
                var html_4f2b80f51c3d42aab0017ad0570d8dca = $(`<div id="html_4f2b80f51c3d42aab0017ad0570d8dca" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_797f035c0d604515a2ae387b73e477d1.setContent(html_4f2b80f51c3d42aab0017ad0570d8dca);
            

            marker_850c89026a7949028101c6f11d9e169f.bindPopup(popup_797f035c0d604515a2ae387b73e477d1)
            ;

            
        
    
        var marker_d1bbe46dc5bf426ea4b0e3c2ffffc83d = L.marker(
            [53.85, -2.467],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_184dbb0f1cb54db8b288dd44d78e8c70 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_d1bbe46dc5bf426ea4b0e3c2ffffc83d.setIcon(icon_184dbb0f1cb54db8b288dd44d78e8c70);
            
    
            var popup_ddd718ea71b746268b62a42062570c15 = L.popup({maxWidth: '300'
            
            });

            
                var html_290fa542b0a34e3abaaa06177b5aa13c = $(`<div id="html_290fa542b0a34e3abaaa06177b5aa13c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_ddd718ea71b746268b62a42062570c15.setContent(html_290fa542b0a34e3abaaa06177b5aa13c);
            

            marker_d1bbe46dc5bf426ea4b0e3c2ffffc83d.bindPopup(popup_ddd718ea71b746268b62a42062570c15)
            ;

            
        
    
        var marker_b74627fd480c4b10b3ec532d02e6868b = L.marker(
            [52.344, -3.947],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_ccdfca5b90364ff78ab8a2458a2ac561 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b74627fd480c4b10b3ec532d02e6868b.setIcon(icon_ccdfca5b90364ff78ab8a2458a2ac561);
            
    
            var popup_d4d27832356f4894b4fbc357f9846cd1 = L.popup({maxWidth: '300'
            
            });

            
                var html_4f0dc0a41e264fd7b12d8bb4c8c5a94f = $(`<div id="html_4f0dc0a41e264fd7b12d8bb4c8c5a94f" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_d4d27832356f4894b4fbc357f9846cd1.setContent(html_4f0dc0a41e264fd7b12d8bb4c8c5a94f);
            

            marker_b74627fd480c4b10b3ec532d02e6868b.bindPopup(popup_d4d27832356f4894b4fbc357f9846cd1)
            ;

            
        
    
        var marker_7d2157c16be14f1eaf577afdd95295d2 = L.marker(
            [52.063, -3.614],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_fb290d5dbc544304a292ec4255f4b5eb = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_7d2157c16be14f1eaf577afdd95295d2.setIcon(icon_fb290d5dbc544304a292ec4255f4b5eb);
            
    
            var popup_c1930536b14c481a8b0251637245e6bf = L.popup({maxWidth: '300'
            
            });

            
                var html_88025dc05eec4c85a93621c4fbbb7634 = $(`<div id="html_88025dc05eec4c85a93621c4fbbb7634" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c1930536b14c481a8b0251637245e6bf.setContent(html_88025dc05eec4c85a93621c4fbbb7634);
            

            marker_7d2157c16be14f1eaf577afdd95295d2.bindPopup(popup_c1930536b14c481a8b0251637245e6bf)
            ;

            
        
    
        var marker_f03d46e1981a43c2bdb26a467fa38b3c = L.marker(
            [51.758, -1.576],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_559b9c1514db4cdca40fb8faa5cf6893 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f03d46e1981a43c2bdb26a467fa38b3c.setIcon(icon_559b9c1514db4cdca40fb8faa5cf6893);
            
    
            var popup_088a2209a5fc448ba9c8a726acf7dc75 = L.popup({maxWidth: '300'
            
            });

            
                var html_feb35c13ca904d90a85792119cc697e7 = $(`<div id="html_feb35c13ca904d90a85792119cc697e7" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_088a2209a5fc448ba9c8a726acf7dc75.setContent(html_feb35c13ca904d90a85792119cc697e7);
            

            marker_f03d46e1981a43c2bdb26a467fa38b3c.bindPopup(popup_088a2209a5fc448ba9c8a726acf7dc75)
            ;

            
        
    
        var marker_eeffb39de3d04c8285710a242d5cbbd4 = L.marker(
            [51.548, -0.415],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_6371641696184473a37bdb9bccefc77b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_eeffb39de3d04c8285710a242d5cbbd4.setIcon(icon_6371641696184473a37bdb9bccefc77b);
            
    
            var popup_dba92b35fa694173a16e4105b350034b = L.popup({maxWidth: '300'
            
            });

            
                var html_afdce67d77c84bbea87b881ae291f076 = $(`<div id="html_afdce67d77c84bbea87b881ae291f076" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_dba92b35fa694173a16e4105b350034b.setContent(html_afdce67d77c84bbea87b881ae291f076);
            

            marker_eeffb39de3d04c8285710a242d5cbbd4.bindPopup(popup_dba92b35fa694173a16e4105b350034b)
            ;

            
        
    
        var marker_1004ea7315f6478694c4f54818e4bff9 = L.marker(
            [51.089, -4.149],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e734f1900fc346ae9b845cb51856bd26 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_1004ea7315f6478694c4f54818e4bff9.setIcon(icon_e734f1900fc346ae9b845cb51856bd26);
            
    
            var popup_351da055e5e24aebb1c86d1bb5c3d9c3 = L.popup({maxWidth: '300'
            
            });

            
                var html_e8479c98fe284781b1aef87e850c0889 = $(`<div id="html_e8479c98fe284781b1aef87e850c0889" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_351da055e5e24aebb1c86d1bb5c3d9c3.setContent(html_e8479c98fe284781b1aef87e850c0889);
            

            marker_1004ea7315f6478694c4f54818e4bff9.bindPopup(popup_351da055e5e24aebb1c86d1bb5c3d9c3)
            ;

            
        
    
        var marker_f3941846212c41cb9398854cc92fd812 = L.marker(
            [51.479, -0.449],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_ee826e76738e4d3db200a7f988f613d0 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f3941846212c41cb9398854cc92fd812.setIcon(icon_ee826e76738e4d3db200a7f988f613d0);
            
    
            var popup_1d4d35d0521244bfa611baef280b64db = L.popup({maxWidth: '300'
            
            });

            
                var html_25a68eec9d45452b936ff9edede93213 = $(`<div id="html_25a68eec9d45452b936ff9edede93213" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1d4d35d0521244bfa611baef280b64db.setContent(html_25a68eec9d45452b936ff9edede93213);
            

            marker_f3941846212c41cb9398854cc92fd812.bindPopup(popup_1d4d35d0521244bfa611baef280b64db)
            ;

            
        
    
        var marker_c8b73ccac9b84fadbd143df8ac52b150 = L.marker(
            [55.907, -4.533],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_cc8640dbe0914442ac8a67a25ca6e974 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c8b73ccac9b84fadbd143df8ac52b150.setIcon(icon_cc8640dbe0914442ac8a67a25ca6e974);
            
    
            var popup_57c4c5b35a6944598b97fe5eeed81b16 = L.popup({maxWidth: '300'
            
            });

            
                var html_385bb1cac47843b3b0fd1e4b0e6ce18b = $(`<div id="html_385bb1cac47843b3b0fd1e4b0e6ce18b" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_57c4c5b35a6944598b97fe5eeed81b16.setContent(html_385bb1cac47843b3b0fd1e4b0e6ce18b);
            

            marker_c8b73ccac9b84fadbd143df8ac52b150.bindPopup(popup_57c4c5b35a6944598b97fe5eeed81b16)
            ;

            
        
    
        var marker_5138ab17ba834362af1b16758f94faad = L.marker(
            [54.125, -3.257],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e178a1c532cc4f50b8fe0aefc2afc89a = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_5138ab17ba834362af1b16758f94faad.setIcon(icon_e178a1c532cc4f50b8fe0aefc2afc89a);
            
    
            var popup_2697694b99764cb7aa7f7016d5b75cb4 = L.popup({maxWidth: '300'
            
            });

            
                var html_d3079ace984541b4809deef318c3db2e = $(`<div id="html_d3079ace984541b4809deef318c3db2e" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2697694b99764cb7aa7f7016d5b75cb4.setContent(html_d3079ace984541b4809deef318c3db2e);
            

            marker_5138ab17ba834362af1b16758f94faad.bindPopup(popup_2697694b99764cb7aa7f7016d5b75cb4)
            ;

            
        
    
        var marker_6c419320d1b743768000665eff78d232 = L.marker(
            [54.501, -2.684],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_4471437a3b414c77a3f38258020bda42 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6c419320d1b743768000665eff78d232.setIcon(icon_4471437a3b414c77a3f38258020bda42);
            
    
            var popup_2e7298f4ddea43ce91986e58663ec817 = L.popup({maxWidth: '300'
            
            });

            
                var html_5cf9b910ef3f4548873f6e0440e7c1d5 = $(`<div id="html_5cf9b910ef3f4548873f6e0440e7c1d5" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2e7298f4ddea43ce91986e58663ec817.setContent(html_5cf9b910ef3f4548873f6e0440e7c1d5);
            

            marker_6c419320d1b743768000665eff78d232.bindPopup(popup_2e7298f4ddea43ce91986e58663ec817)
            ;

            
        
    
        var marker_4fccc2b2d06048c7a7dacebd575b999b = L.marker(
            [54.684, -2.45],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_5d412b125d2741bbb18b660c1426aa4d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_4fccc2b2d06048c7a7dacebd575b999b.setIcon(icon_5d412b125d2741bbb18b660c1426aa4d);
            
    
            var popup_2facc152dae44130ae704c06fbfd5e5f = L.popup({maxWidth: '300'
            
            });

            
                var html_a7c1ccb7f94c4b16abf54adfcd1e914d = $(`<div id="html_a7c1ccb7f94c4b16abf54adfcd1e914d" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2facc152dae44130ae704c06fbfd5e5f.setContent(html_a7c1ccb7f94c4b16abf54adfcd1e914d);
            

            marker_4fccc2b2d06048c7a7dacebd575b999b.bindPopup(popup_2facc152dae44130ae704c06fbfd5e5f)
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        var marker_2aa9f1cf4a5b4440aa02a01938fa3e2f = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_40c6f329d8bc4bbb93cd2dd854d17fef = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_2aa9f1cf4a5b4440aa02a01938fa3e2f.setIcon(icon_40c6f329d8bc4bbb93cd2dd854d17fef);
            
    
            var popup_47f479748db640999475b1a6b94c6d5c = L.popup({maxWidth: '300'
            
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                var html_97005731ca484749a924b8fea85dd3ea = $(`<div id="html_97005731ca484749a924b8fea85dd3ea" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_47f479748db640999475b1a6b94c6d5c.setContent(html_97005731ca484749a924b8fea85dd3ea);
            

            marker_2aa9f1cf4a5b4440aa02a01938fa3e2f.bindPopup(popup_47f479748db640999475b1a6b94c6d5c)
            ;

            
        
    
        var marker_ab79854777e94aa49ef2af4770f8fabd = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_a24971d171c44a6fb30f7906813731c9 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_ab79854777e94aa49ef2af4770f8fabd.setIcon(icon_a24971d171c44a6fb30f7906813731c9);
            
    
            var popup_f9ec3fc1c11c462fa4e170cd58806ee5 = L.popup({maxWidth: '300'
            
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                var html_9d96198534654f528adc24f42a061a40 = $(`<div id="html_9d96198534654f528adc24f42a061a40" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f9ec3fc1c11c462fa4e170cd58806ee5.setContent(html_9d96198534654f528adc24f42a061a40);
            

            marker_ab79854777e94aa49ef2af4770f8fabd.bindPopup(popup_f9ec3fc1c11c462fa4e170cd58806ee5)
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        var marker_a58952f411eb44599e07dc4a3e0419ca = L.marker(
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            {
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_a193f81d1e644369bcf8333546bf8901 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_a58952f411eb44599e07dc4a3e0419ca.setIcon(icon_a193f81d1e644369bcf8333546bf8901);
            
    
            var popup_4d13a166959c4430abe92ed894c9d1ad = L.popup({maxWidth: '300'
            
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                var html_58e95dec6cf04f129a97a2dceda53d50 = $(`<div id="html_58e95dec6cf04f129a97a2dceda53d50" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4d13a166959c4430abe92ed894c9d1ad.setContent(html_58e95dec6cf04f129a97a2dceda53d50);
            

            marker_a58952f411eb44599e07dc4a3e0419ca.bindPopup(popup_4d13a166959c4430abe92ed894c9d1ad)
            ;

            
        
    
        var marker_999b2d9f429641ea888f576dc30ea93a = L.marker(
            [50.737, -3.405],
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_731c9f4096074cd0a4882eb12ea13095 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_999b2d9f429641ea888f576dc30ea93a.setIcon(icon_731c9f4096074cd0a4882eb12ea13095);
            
    
            var popup_32d418a2edfa4809b00911d5d8043c1d = L.popup({maxWidth: '300'
            
            });

            
                var html_e85b24f7be254e149b45c6f975ff841a = $(`<div id="html_e85b24f7be254e149b45c6f975ff841a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_32d418a2edfa4809b00911d5d8043c1d.setContent(html_e85b24f7be254e149b45c6f975ff841a);
            

            marker_999b2d9f429641ea888f576dc30ea93a.bindPopup(popup_32d418a2edfa4809b00911d5d8043c1d)
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        var marker_dfb408759db2439180fbf5b856e77cce = L.marker(
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_5f656dfeb1754dbd826d35972003aba7 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_dfb408759db2439180fbf5b856e77cce.setIcon(icon_5f656dfeb1754dbd826d35972003aba7);
            
    
            var popup_398eb4867b2d4daeb116a1bd0414b24a = L.popup({maxWidth: '300'
            
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                var html_f6e4ab6654b641e1a1747946c0c69060 = $(`<div id="html_f6e4ab6654b641e1a1747946c0c69060" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_398eb4867b2d4daeb116a1bd0414b24a.setContent(html_f6e4ab6654b641e1a1747946c0c69060);
            

            marker_dfb408759db2439180fbf5b856e77cce.bindPopup(popup_398eb4867b2d4daeb116a1bd0414b24a)
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        var marker_7cfe63a820af4f78ae0596b9735ab2cc = L.marker(
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            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_3275913b068b4a8bab631b68627b99a6 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_7cfe63a820af4f78ae0596b9735ab2cc.setIcon(icon_3275913b068b4a8bab631b68627b99a6);
            
    
            var popup_44c0308da8b1452a8829d4e4584eb664 = L.popup({maxWidth: '300'
            
            });

            
                var html_a394ae5b737d442a9c3d83123ae6f99e = $(`<div id="html_a394ae5b737d442a9c3d83123ae6f99e" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_44c0308da8b1452a8829d4e4584eb664.setContent(html_a394ae5b737d442a9c3d83123ae6f99e);
            

            marker_7cfe63a820af4f78ae0596b9735ab2cc.bindPopup(popup_44c0308da8b1452a8829d4e4584eb664)
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        var marker_08d5e96fa38b4ca8ad047a8a28b6a614 = L.marker(
            [51.464, 0.314],
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                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_038ab408ddde46e19f75fef0881e0030 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_08d5e96fa38b4ca8ad047a8a28b6a614.setIcon(icon_038ab408ddde46e19f75fef0881e0030);
            
    
            var popup_9d203bca12cd4177beee41c8398845dd = L.popup({maxWidth: '300'
            
            });

            
                var html_b255a58cbb0a4fbf866aa42b80b6ba8a = $(`<div id="html_b255a58cbb0a4fbf866aa42b80b6ba8a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_9d203bca12cd4177beee41c8398845dd.setContent(html_b255a58cbb0a4fbf866aa42b80b6ba8a);
            

            marker_08d5e96fa38b4ca8ad047a8a28b6a614.bindPopup(popup_9d203bca12cd4177beee41c8398845dd)
            ;

            
        
    
        var marker_2f40fc1f32004c85a999dc1be1380302 = L.marker(
            [51.3422, 1.3461],
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                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_442d6b0dda104851b0edc15b0f0604d6 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
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                marker_2f40fc1f32004c85a999dc1be1380302.setIcon(icon_442d6b0dda104851b0edc15b0f0604d6);
            
    
            var popup_c8bef763b9c5432499654a3984f07712 = L.popup({maxWidth: '300'
            
            });

            
                var html_4c65c0df999840c4aeffda69b5ef7083 = $(`<div id="html_4c65c0df999840c4aeffda69b5ef7083" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_c8bef763b9c5432499654a3984f07712.setContent(html_4c65c0df999840c4aeffda69b5ef7083);
            

            marker_2f40fc1f32004c85a999dc1be1380302.bindPopup(popup_c8bef763b9c5432499654a3984f07712)
            ;

            
        
    
        var marker_de6ba8fe560848ca9d62fe200294c171 = L.marker(
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                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_46dbf13f3a384387a991381fb2730873 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_de6ba8fe560848ca9d62fe200294c171.setIcon(icon_46dbf13f3a384387a991381fb2730873);
            
    
            var popup_6022f6f35ef945829f753c78e1718e77 = L.popup({maxWidth: '300'
            
            });

            
                var html_7123ce3c73a74767a935f55fb90dc778 = $(`<div id="html_7123ce3c73a74767a935f55fb90dc778" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_6022f6f35ef945829f753c78e1718e77.setContent(html_7123ce3c73a74767a935f55fb90dc778);
            

            marker_de6ba8fe560848ca9d62fe200294c171.bindPopup(popup_6022f6f35ef945829f753c78e1718e77)
            ;

            
        
    
        var marker_10b94a41d6e2400cb8567c5fa0a91670 = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_31128c12d68f452d8d6620108d4494e7 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_10b94a41d6e2400cb8567c5fa0a91670.setIcon(icon_31128c12d68f452d8d6620108d4494e7);
            
    
            var popup_1606375b3531411bab4887046fa072d6 = L.popup({maxWidth: '300'
            
            });

            
                var html_b788c82d62a04efaa18df01ecd5ef4a4 = $(`<div id="html_b788c82d62a04efaa18df01ecd5ef4a4" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_1606375b3531411bab4887046fa072d6.setContent(html_b788c82d62a04efaa18df01ecd5ef4a4);
            

            marker_10b94a41d6e2400cb8567c5fa0a91670.bindPopup(popup_1606375b3531411bab4887046fa072d6)
            ;

            
        
    
        var marker_60c0cef6335442f2b6d1d408305b5f4f = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_03b46c7d9c2e40da9ae423407b81574b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_60c0cef6335442f2b6d1d408305b5f4f.setIcon(icon_03b46c7d9c2e40da9ae423407b81574b);
            
    
            var popup_8e1d29345cb74ff5b2a2114eec07e629 = L.popup({maxWidth: '300'
            
            });

            
                var html_ab6873afc2c14b6e8e8c9e34e0ea4c54 = $(`<div id="html_ab6873afc2c14b6e8e8c9e34e0ea4c54" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_8e1d29345cb74ff5b2a2114eec07e629.setContent(html_ab6873afc2c14b6e8e8c9e34e0ea4c54);
            

            marker_60c0cef6335442f2b6d1d408305b5f4f.bindPopup(popup_8e1d29345cb74ff5b2a2114eec07e629)
            ;

            
        
    
        var marker_773765ec70ae444896b9bb9654b2a78e = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c9c103fa94cf49e3b2266dec03925c0b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_773765ec70ae444896b9bb9654b2a78e.setIcon(icon_c9c103fa94cf49e3b2266dec03925c0b);
            
    
            var popup_f476e4aa1351476caa81062b4ed2c8f9 = L.popup({maxWidth: '300'
            
            });

            
                var html_a2f2142caedf43469d5ceaea9df8fd93 = $(`<div id="html_a2f2142caedf43469d5ceaea9df8fd93" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f476e4aa1351476caa81062b4ed2c8f9.setContent(html_a2f2142caedf43469d5ceaea9df8fd93);
            

            marker_773765ec70ae444896b9bb9654b2a78e.bindPopup(popup_f476e4aa1351476caa81062b4ed2c8f9)
            ;

            
        
    
        var marker_6c213a3dd6504ab9ae8c47803be21dd6 = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_dce258249966443281aabf406fccbb39 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6c213a3dd6504ab9ae8c47803be21dd6.setIcon(icon_dce258249966443281aabf406fccbb39);
            
    
            var popup_4a96c64dc30c4d318124ebd13c186b57 = L.popup({maxWidth: '300'
            
            });

            
                var html_f5ab8e29025947599060f4a2f8b29a91 = $(`<div id="html_f5ab8e29025947599060f4a2f8b29a91" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4a96c64dc30c4d318124ebd13c186b57.setContent(html_f5ab8e29025947599060f4a2f8b29a91);
            

            marker_6c213a3dd6504ab9ae8c47803be21dd6.bindPopup(popup_4a96c64dc30c4d318124ebd13c186b57)
            ;

            
        
    
        var marker_9c1c08e0c56e4679bfc1e268b22d420a = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_f9224f315cfb4d1d8a7bbb91c505273e = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_9c1c08e0c56e4679bfc1e268b22d420a.setIcon(icon_f9224f315cfb4d1d8a7bbb91c505273e);
            
    
            var popup_52b39f6fcb6940a39fab3b9fa47887a2 = L.popup({maxWidth: '300'
            
            });

            
                var html_c4c636cb9677406e887053e335c3f824 = $(`<div id="html_c4c636cb9677406e887053e335c3f824" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_52b39f6fcb6940a39fab3b9fa47887a2.setContent(html_c4c636cb9677406e887053e335c3f824);
            

            marker_9c1c08e0c56e4679bfc1e268b22d420a.bindPopup(popup_52b39f6fcb6940a39fab3b9fa47887a2)
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        var marker_ccd2db608e604c548b7de87cc09f8370 = L.marker(
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_1a1bddb93cb149bb9dc9551ebb6b3a43 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_ccd2db608e604c548b7de87cc09f8370.setIcon(icon_1a1bddb93cb149bb9dc9551ebb6b3a43);
            
    
            var popup_376a79973aa8434f89e03e11dfe47dbe = L.popup({maxWidth: '300'
            
            });

            
                var html_e99bf17ae87448e3b1c4f3bc7f540e26 = $(`<div id="html_e99bf17ae87448e3b1c4f3bc7f540e26" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_376a79973aa8434f89e03e11dfe47dbe.setContent(html_e99bf17ae87448e3b1c4f3bc7f540e26);
            

            marker_ccd2db608e604c548b7de87cc09f8370.bindPopup(popup_376a79973aa8434f89e03e11dfe47dbe)
            ;

            
        
    
        var marker_cfc9a98f47dd4851a76b9276d7e0dc62 = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_99fbc5bb82cd490f8808a4daaa9a3bf8 = L.AwesomeMarkers.icon({
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                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_cfc9a98f47dd4851a76b9276d7e0dc62.setIcon(icon_99fbc5bb82cd490f8808a4daaa9a3bf8);
            
    
            var popup_8981c62cbe3348e192b16744313315f6 = L.popup({maxWidth: '300'
            
            });

            
                var html_ba95a6a866f4416d87078bc6ff06d453 = $(`<div id="html_ba95a6a866f4416d87078bc6ff06d453" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_8981c62cbe3348e192b16744313315f6.setContent(html_ba95a6a866f4416d87078bc6ff06d453);
            

            marker_cfc9a98f47dd4851a76b9276d7e0dc62.bindPopup(popup_8981c62cbe3348e192b16744313315f6)
            ;

            
        
    
        var marker_d455f146e368448fbce8bbca2395732b = L.marker(
            [51.303, -0.09],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_f30d4eed27a74ab3b6b830780e337d7b = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_d455f146e368448fbce8bbca2395732b.setIcon(icon_f30d4eed27a74ab3b6b830780e337d7b);
            
    
            var popup_439175479e43409a81c972acdee08ee8 = L.popup({maxWidth: '300'
            
            });

            
                var html_3186e6a16156470897a3eb22da2d024a = $(`<div id="html_3186e6a16156470897a3eb22da2d024a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_439175479e43409a81c972acdee08ee8.setContent(html_3186e6a16156470897a3eb22da2d024a);
            

            marker_d455f146e368448fbce8bbca2395732b.bindPopup(popup_439175479e43409a81c972acdee08ee8)
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        var marker_fcdd6b559e4d4913873f2fbc985b2bad = L.marker(
            [49.44, -2.6],
            {
                icon: new L.Icon.Default()
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            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_e8e9f3fabc60494fa1313ab1b644f176 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_fcdd6b559e4d4913873f2fbc985b2bad.setIcon(icon_e8e9f3fabc60494fa1313ab1b644f176);
            
    
            var popup_d5d703e429ff48178dbb6e644c49c3e0 = L.popup({maxWidth: '300'
            
            });

            
                var html_1c4c08e2b94c490bbed41050a93e8fd7 = $(`<div id="html_1c4c08e2b94c490bbed41050a93e8fd7" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_d5d703e429ff48178dbb6e644c49c3e0.setContent(html_1c4c08e2b94c490bbed41050a93e8fd7);
            

            marker_fcdd6b559e4d4913873f2fbc985b2bad.bindPopup(popup_d5d703e429ff48178dbb6e644c49c3e0)
            ;

            
        
    
        var marker_b6fdbb63d5e646d78e586a4c556cb9a8 = L.marker(
            [54.664, -6.224],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_7223349bab2b4467b7b462c54787eeb8 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_b6fdbb63d5e646d78e586a4c556cb9a8.setIcon(icon_7223349bab2b4467b7b462c54787eeb8);
            
    
            var popup_d8132b5a5228408295c58010661b8df0 = L.popup({maxWidth: '300'
            
            });

            
                var html_45ae3a652b2448f4b434b32bb5476ead = $(`<div id="html_45ae3a652b2448f4b434b32bb5476ead" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_d8132b5a5228408295c58010661b8df0.setContent(html_45ae3a652b2448f4b434b32bb5476ead);
            

            marker_b6fdbb63d5e646d78e586a4c556cb9a8.bindPopup(popup_d8132b5a5228408295c58010661b8df0)
            ;

            
        
    
        var marker_5e8957e652d846169867c01498155a95 = L.marker(
            [52.123, 0.961],
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                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_2dffd2fde38b494ca9e8747cda4ab83a = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_5e8957e652d846169867c01498155a95.setIcon(icon_2dffd2fde38b494ca9e8747cda4ab83a);
            
    
            var popup_faca5ca105d342cb9090df82cc9ddc9e = L.popup({maxWidth: '300'
            
            });

            
                var html_ecf7ab955c914d588eb03a5f7b63e91a = $(`<div id="html_ecf7ab955c914d588eb03a5f7b63e91a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_faca5ca105d342cb9090df82cc9ddc9e.setContent(html_ecf7ab955c914d588eb03a5f7b63e91a);
            

            marker_5e8957e652d846169867c01498155a95.bindPopup(popup_faca5ca105d342cb9090df82cc9ddc9e)
            ;

            
        
    
        var marker_e247606b41b34d9f83b6157ec5c1b184 = L.marker(
            [51.565, -3.981],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_51927f5f571e40c8bd63ef095897cb3e = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_e247606b41b34d9f83b6157ec5c1b184.setIcon(icon_51927f5f571e40c8bd63ef095897cb3e);
            
    
            var popup_4f036d977cea45628bd7b06148c7da6b = L.popup({maxWidth: '300'
            
            });

            
                var html_b9d92fee8d934b3f92547a1e12d09b86 = $(`<div id="html_b9d92fee8d934b3f92547a1e12d09b86" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4f036d977cea45628bd7b06148c7da6b.setContent(html_b9d92fee8d934b3f92547a1e12d09b86);
            

            marker_e247606b41b34d9f83b6157ec5c1b184.bindPopup(popup_4f036d977cea45628bd7b06148c7da6b)
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        var marker_6ae3bbe96a9f402b80b8f1649348b77b = L.marker(
            [51.62, -1.097],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_96f9a636d1384278b5dde1663d05c0b0 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6ae3bbe96a9f402b80b8f1649348b77b.setIcon(icon_96f9a636d1384278b5dde1663d05c0b0);
            
    
            var popup_f13550494d1f45649ebcb88923ee14d3 = L.popup({maxWidth: '300'
            
            });

            
                var html_2953d52346d64136b6184f92415b5685 = $(`<div id="html_2953d52346d64136b6184f92415b5685" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_f13550494d1f45649ebcb88923ee14d3.setContent(html_2953d52346d64136b6184f92415b5685);
            

            marker_6ae3bbe96a9f402b80b8f1649348b77b.bindPopup(popup_f13550494d1f45649ebcb88923ee14d3)
            ;

            
        
    
        var marker_6920cccfd2e743f1b515b4f8c6ec5fa2 = L.marker(
            [56.326, -3.729],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c58869353609460cb01a13c305903811 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_6920cccfd2e743f1b515b4f8c6ec5fa2.setIcon(icon_c58869353609460cb01a13c305903811);
            
    
            var popup_b1bb6eaefe5e45fe81a4eb96e58f53de = L.popup({maxWidth: '300'
            
            });

            
                var html_a0e56a65eeae40488d6b65cd8f4381d8 = $(`<div id="html_a0e56a65eeae40488d6b65cd8f4381d8" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b1bb6eaefe5e45fe81a4eb96e58f53de.setContent(html_a0e56a65eeae40488d6b65cd8f4381d8);
            

            marker_6920cccfd2e743f1b515b4f8c6ec5fa2.bindPopup(popup_b1bb6eaefe5e45fe81a4eb96e58f53de)
            ;

            
        
    
        var marker_348f49322aeb4c70859549471296f0c0 = L.marker(
            [56.423, -4.32],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_11d51e7d84f9420a9a7a1cc012e14fb8 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_348f49322aeb4c70859549471296f0c0.setIcon(icon_11d51e7d84f9420a9a7a1cc012e14fb8);
            
    
            var popup_2b719e99f7954a7ca2bf8ac9b6cca3b9 = L.popup({maxWidth: '300'
            
            });

            
                var html_ed3380541dea415ca8cfca28b198ba1a = $(`<div id="html_ed3380541dea415ca8cfca28b198ba1a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2b719e99f7954a7ca2bf8ac9b6cca3b9.setContent(html_ed3380541dea415ca8cfca28b198ba1a);
            

            marker_348f49322aeb4c70859549471296f0c0.bindPopup(popup_2b719e99f7954a7ca2bf8ac9b6cca3b9)
            ;

            
        
    
        var marker_54351d96bd5f44d69e24faac7c74fced = L.marker(
            [54.0849, -4.6321],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_d754803932304968ba34b7dd9761e26d = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_54351d96bd5f44d69e24faac7c74fced.setIcon(icon_d754803932304968ba34b7dd9761e26d);
            
    
            var popup_4e435f4e10814e01b53895ada83b8718 = L.popup({maxWidth: '300'
            
            });

            
                var html_7a881f7c28834ec4a1871a65ee9c35c9 = $(`<div id="html_7a881f7c28834ec4a1871a65ee9c35c9" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_4e435f4e10814e01b53895ada83b8718.setContent(html_7a881f7c28834ec4a1871a65ee9c35c9);
            

            marker_54351d96bd5f44d69e24faac7c74fced.bindPopup(popup_4e435f4e10814e01b53895ada83b8718)
            ;

            
        
    
        var marker_31888deeaee5474688a1b16e65be3efb = L.marker(
            [55.421, -1.6],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_2634143118794076b764a197fb48b358 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_31888deeaee5474688a1b16e65be3efb.setIcon(icon_2634143118794076b764a197fb48b358);
            
    
            var popup_2b5a8b924e474a27acaa1c95e3fb610a = L.popup({maxWidth: '300'
            
            });

            
                var html_0efadb7bea064382b077943e93c5f477 = $(`<div id="html_0efadb7bea064382b077943e93c5f477" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_2b5a8b924e474a27acaa1c95e3fb610a.setContent(html_0efadb7bea064382b077943e93c5f477);
            

            marker_31888deeaee5474688a1b16e65be3efb.bindPopup(popup_2b5a8b924e474a27acaa1c95e3fb610a)
            ;

            
        
    
        var marker_f3e8bbcd94a24c91aa96bc03c800b036 = L.marker(
            [54.204, -1.39],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_594b541fd3e64b7498d1acc3a8c4f507 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f3e8bbcd94a24c91aa96bc03c800b036.setIcon(icon_594b541fd3e64b7498d1acc3a8c4f507);
            
    
            var popup_b4de2c2360c94289ab765b1210db0009 = L.popup({maxWidth: '300'
            
            });

            
                var html_b000eded83414f049bfba5943aedffbe = $(`<div id="html_b000eded83414f049bfba5943aedffbe" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_b4de2c2360c94289ab765b1210db0009.setContent(html_b000eded83414f049bfba5943aedffbe);
            

            marker_f3e8bbcd94a24c91aa96bc03c800b036.bindPopup(popup_b4de2c2360c94289ab765b1210db0009)
            ;

            
        
    
        var marker_20c3122b90e344e88a66a9d858edd515 = L.marker(
            [54.094, -0.174],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_3fe7463a5d84460799a77f6417f4f63c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_20c3122b90e344e88a66a9d858edd515.setIcon(icon_3fe7463a5d84460799a77f6417f4f63c);
            
    
            var popup_63d6db6ac11a42af81f4c67f12e7a063 = L.popup({maxWidth: '300'
            
            });

            
                var html_96542339c0024396b3581db0950b5a55 = $(`<div id="html_96542339c0024396b3581db0950b5a55" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_63d6db6ac11a42af81f4c67f12e7a063.setContent(html_96542339c0024396b3581db0950b5a55);
            

            marker_20c3122b90e344e88a66a9d858edd515.bindPopup(popup_63d6db6ac11a42af81f4c67f12e7a063)
            ;

            
        
    
        var marker_ced5e5c61ba04d29bee6a8c6c00e1c99 = L.marker(
            [53.259, -3.509],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_330930730b254f91817d85c71c43b155 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_ced5e5c61ba04d29bee6a8c6c00e1c99.setIcon(icon_330930730b254f91817d85c71c43b155);
            
    
            var popup_e56077212ce64ae893e59549e4f4c3cf = L.popup({maxWidth: '300'
            
            });

            
                var html_120b47ada74c4dadb65fcc49a2994683 = $(`<div id="html_120b47ada74c4dadb65fcc49a2994683" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_e56077212ce64ae893e59549e4f4c3cf.setContent(html_120b47ada74c4dadb65fcc49a2994683);
            

            marker_ced5e5c61ba04d29bee6a8c6c00e1c99.bindPopup(popup_e56077212ce64ae893e59549e4f4c3cf)
            ;

            
        
    
        var marker_bf1a1b8a73164e908dfd5865fb801eae = L.marker(
            [53.174, -2.986],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_5d4ed8dc0e3946d6b17c035eb412eb87 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_bf1a1b8a73164e908dfd5865fb801eae.setIcon(icon_5d4ed8dc0e3946d6b17c035eb412eb87);
            
    
            var popup_51db8c39106c4326856a02e8d38c91ca = L.popup({maxWidth: '300'
            
            });

            
                var html_168b62f0089c496288324a9e8efc4d9c = $(`<div id="html_168b62f0089c496288324a9e8efc4d9c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_51db8c39106c4326856a02e8d38c91ca.setContent(html_168b62f0089c496288324a9e8efc4d9c);
            

            marker_bf1a1b8a73164e908dfd5865fb801eae.bindPopup(popup_51db8c39106c4326856a02e8d38c91ca)
            ;

            
        
    
        var marker_a182110e484a43229dc4d679d7529c39 = L.marker(
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            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_c1a720b1e64f4202bf3a08614a67842e = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_a182110e484a43229dc4d679d7529c39.setIcon(icon_c1a720b1e64f4202bf3a08614a67842e);
            
    
            var popup_ce18322298644592aac1c7e61773249f = L.popup({maxWidth: '300'
            
            });

            
                var html_2e39def95ac74a0cac5a247e67d168c3 = $(`<div id="html_2e39def95ac74a0cac5a247e67d168c3" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_ce18322298644592aac1c7e61773249f.setContent(html_2e39def95ac74a0cac5a247e67d168c3);
            

            marker_a182110e484a43229dc4d679d7529c39.bindPopup(popup_ce18322298644592aac1c7e61773249f)
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        var marker_f4c8110818fb4e7891c9ed7d93a81dbb = L.marker(
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            {
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                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_798f7f8331bd43e69a2499321d78ba28 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f4c8110818fb4e7891c9ed7d93a81dbb.setIcon(icon_798f7f8331bd43e69a2499321d78ba28);
            
    
            var popup_a655d4515c14417e8a5093c5478b5e07 = L.popup({maxWidth: '300'
            
            });

            
                var html_6407dc80164c432bb96515fe4bb89406 = $(`<div id="html_6407dc80164c432bb96515fe4bb89406" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_a655d4515c14417e8a5093c5478b5e07.setContent(html_6407dc80164c432bb96515fe4bb89406);
            

            marker_f4c8110818fb4e7891c9ed7d93a81dbb.bindPopup(popup_a655d4515c14417e8a5093c5478b5e07)
            ;

            
        
    
        var marker_fa5c8f8b98f94308b28a385fe02276c9 = L.marker(
            [53.473, 0.154],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_203c2384d4f447e5a6f908932b3b57c1 = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_fa5c8f8b98f94308b28a385fe02276c9.setIcon(icon_203c2384d4f447e5a6f908932b3b57c1);
            
    
            var popup_84f54b09db594122aa3078700522ecb4 = L.popup({maxWidth: '300'
            
            });

            
                var html_8f22851af35b41b5959f91083a58286a = $(`<div id="html_8f22851af35b41b5959f91083a58286a" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_84f54b09db594122aa3078700522ecb4.setContent(html_8f22851af35b41b5959f91083a58286a);
            

            marker_fa5c8f8b98f94308b28a385fe02276c9.bindPopup(popup_84f54b09db594122aa3078700522ecb4)
            ;

            
        
    
        var marker_f626653fc4d64e99970a84d3403a378d = L.marker(
            [53.094, -0.171],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_42dd0f3d40b64ca5bba5f7248c1c340a = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_f626653fc4d64e99970a84d3403a378d.setIcon(icon_42dd0f3d40b64ca5bba5f7248c1c340a);
            
    
            var popup_5d59e4e70554440390c7641eed414cd1 = L.popup({maxWidth: '300'
            
            });

            
                var html_dab26b28f3d3474e86b19c0e58934e99 = $(`<div id="html_dab26b28f3d3474e86b19c0e58934e99" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_5d59e4e70554440390c7641eed414cd1.setContent(html_dab26b28f3d3474e86b19c0e58934e99);
            

            marker_f626653fc4d64e99970a84d3403a378d.bindPopup(popup_5d59e4e70554440390c7641eed414cd1)
            ;

            
        
    
        var marker_c2d295fc792e4bbaa598ec932150ea7a = L.marker(
            [54.273, -0.421],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_17435bfcec614070a7e70b9e7d639c5c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c2d295fc792e4bbaa598ec932150ea7a.setIcon(icon_17435bfcec614070a7e70b9e7d639c5c);
            
    
            var popup_a84d13a64034465e8fa3e70d591c5747 = L.popup({maxWidth: '300'
            
            });

            
                var html_2f1eab7a0e9a4711832150d710347d5c = $(`<div id="html_2f1eab7a0e9a4711832150d710347d5c" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_a84d13a64034465e8fa3e70d591c5747.setContent(html_2f1eab7a0e9a4711832150d710347d5c);
            

            marker_c2d295fc792e4bbaa598ec932150ea7a.bindPopup(popup_a84d13a64034465e8fa3e70d591c5747)
            ;

            
        
    
        var marker_c8ae84cc7ad64a2985df0e1e3e3e3199 = L.marker(
            [50.7366, -3.40458],
            {
                icon: new L.Icon.Default()
                }
            ).addTo(map_b9013e89b7d141b896b137b749eff7f6);
        
    

                var icon_2f8ca65a16784e4ebfb63b48969b1a3c = L.AwesomeMarkers.icon({
                    icon: 'cloud',
                    iconColor: 'white',
                    markerColor: 'green',
                    prefix: 'glyphicon',
                    extraClasses: 'fa-rotate-0'
                    });
                marker_c8ae84cc7ad64a2985df0e1e3e3e3199.setIcon(icon_2f8ca65a16784e4ebfb63b48969b1a3c);
            
    
            var popup_7d9e97872a5d4979bdcd1362bfea6634 = L.popup({maxWidth: '300'
            
            });

            
                var html_a52aeae6ea9d41398016e1a337b616e3 = $(`<div id="html_a52aeae6ea9d41398016e1a337b616e3" style="width: 100.0%; height: 100.0%;">weather station</div>`)[0];
                popup_7d9e97872a5d4979bdcd1362bfea6634.setContent(html_a52aeae6ea9d41398016e1a337b616e3);
            

            marker_c8ae84cc7ad64a2985df0e1e3e3e3199.bindPopup(popup_7d9e97872a5d4979bdcd1362bfea6634)
            ;

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x12049b940>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MAP_COORDINATES = (51.5113, -0.1160) \n",
    "\n",
    "m = folium.Map(location=MAP_COORDINATES, zoom_start=8, tiles=\"Stamen Toner\")\n",
    "\n",
    "for index, loc in site_df.iterrows():\n",
    "    # And now add a marker\n",
    "    folium.Marker((loc['latitude'], loc['longitude']), icon=folium.Icon(color='green',icon='cloud'), \n",
    "              popup = 'weather station'\n",
    "             ).add_to(m)\n",
    "m # Print the map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Zoom out, and what did you see there?**\n",
    "\n",
    "The weather station are located across the whole UK, not just in London."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use spatial join to find out all stations in GLA, but not there yet. Lets use the key word 'unitaryAuthArea' to query out stations in 'Greater London'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets find out the weather station in the Greater London area by querying a key word\n",
    "site_df_london = site_df.loc[(site_df.unitaryAuthArea =='Greater London')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe 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style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x120eaecf8>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MAP_COORDINATES = (51.5113, -0.1160) \n",
    "\n",
    "m = folium.Map(location=MAP_COORDINATES, zoom_start=10, tiles=\"Stamen Toner\")\n",
    "\n",
    "for index, loc in site_df_london.iterrows():\n",
    "    # And now add a marker\n",
    "    folium.Marker((loc['latitude'], loc['longitude']), icon=folium.Icon(color='green',icon='cloud'), \n",
    "              popup= loc['unitaryAuthArea']\n",
    "             ).add_to(m)\n",
    "m # Print the map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 6: Obtaining Weather Data in London\n",
    "\n",
    "The next step in this process is a bit more complicated because weather data is a bit more complicated than a list of locations...\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Here, the MetOffice has _not_ made our lives very easy because the data is packaged in a way that doesn't allow us to easily load it into pandas. If you search online, you'll find plenty of people complaining about how the MetOffice API works. Or doesn't work, if you prefer.\n",
    "\n",
    "So we're not going to ask you to sort this out for yourselves. Instead, we're going to provide you with a function (!) to take the observation data and convert it into a data frame.\n",
    "\n",
    "Well, you should at least know how to use a function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta\n",
    "def processMetOfficeObservations(loc): \n",
    "    \"\"\"\n",
    "    Process a series of 'reports' for a single\n",
    "    location using the datetime object as the \n",
    "    reference time against which to build the \n",
    "    timedelta (i.e. we start from midnight and \n",
    "    the timedelta is the number of minutes past \n",
    "    midnight)\n",
    "    \"\"\"\n",
    "    observations = {} # Stores results\n",
    "    \n",
    "    for d in loc['Period']: # d for day\n",
    "        if 'value' not in d or 'Rep' not in d:\n",
    "            # print 'no \"value\" or \"Rep\" key, skip'\n",
    "            continue\n",
    "            \n",
    "        dt = datetime.strptime(d['value'],'%Y-%m-%dZ')# Convert date to datetime object \n",
    "        \n",
    "        # Now deal with the actual observations (i.e. 'Reports')\n",
    "        the_type = type(d['Rep'])\n",
    "        if the_type is dict:\n",
    "            reports = [d['Rep']]\n",
    "        elif the_type is list:\n",
    "            reports = d['Rep']\n",
    "        else:\n",
    "            print (\"***warning: d['Rep'] type: \", the_type, \" not support\")\n",
    "            continue\n",
    "        \n",
    "        for report in d['Rep']:\n",
    "                \n",
    "            # Find the timestampe and add it to the date\n",
    "            minutes_after_midnight = int(report['$'])\n",
    "            ts = dt + timedelta(minutes=minutes_after_midnight)\n",
    "            \n",
    "            # For each of the possible values, set a default value\n",
    "            # if the weather station doesn't actually collect that\n",
    "            # parameter... can you see a problem with our defaults?\n",
    "            if 'ts' not in observations:\n",
    "                observations['ts'] = []\n",
    "            observations['ts'].append(str(ts))\n",
    "            for key in ['D','Pt']:\n",
    "                if key not in report:\n",
    "                    report[key] = u\"\"\n",
    "                if key not in observations:\n",
    "                    observations[key] = []\n",
    "                observations[key].append(report[key])\n",
    "            for key in ['W','V','S','G']:\n",
    "                if key not in report or report[key] == \"\":\n",
    "                    report[key] = 0\n",
    "                if key not in observations:\n",
    "                    observations[key] = []\n",
    "                observations[key].append(report[key])\n",
    "            for key in ['T','Dp','H']:\n",
    "                if key not in report or report[key] == \"\":\n",
    "                    report[key] = 0.0\n",
    "                if key not in observations:\n",
    "                    observations[key] = []\n",
    "                observations[key].append(report[key])\n",
    "    \n",
    "    return observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "First, just in case you want to only run this section again (and not revisit the content above), I'd suggest saving a copy of your API key here as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "api_key = \"75038866-617b-4f32-b7a1-2af56d36fe63\" # Here you need to replace this with your unique API key"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start from a simple task. - querying weather data at one weather station. And we choose one located in London."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3672, 3772])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "london_ids = (site_df_london.id).unique()\n",
    "london_ids  \n",
    "\n",
    "# how many stations with hourly updated data in London? You have got the answer from your map."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like what we did before for querying site locations. Here, we just added one small parameter - location id.\n",
    "\n",
    "**if you are unsure where to add it, go to check data point [API](https://www.metoffice.gov.uk/datapoint/support/api-reference)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "import json, requests # Libraries we need\n",
    "\n",
    "api_url  = \"http://datapoint.metoffice.gov.uk/public/data/\" # Base URL\n",
    "obs_json= \"val/wxobs/all/json/\" # Observations URL\n",
    "\n",
    "station = str(3772)  #3772 # This is heathrow airport weather station\n",
    "\n",
    "payload = {'res': 'hourly', 'key': api_key} # Dictionary to hold request parameters\n",
    "\n",
    "# pay attention here, station id added\n",
    "r = requests.get(api_url + obs_json + station, params=payload)\n",
    "\n",
    "#print(r.url)\n",
    "\n",
    "weather = r.json() # Capture the reply\n",
    "\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'SiteRep': {'Wx': {'Param': [{'name': 'G', 'units': 'mph', '$': 'Wind Gust'}, {'name': 'T', 'units': 'C', '$': 'Temperature'}, {'name': 'V', 'units': 'm', '$': 'Visibility'}, {'name': 'D', 'units': 'compass', '$': 'Wind Direction'}, {'name': 'S', 'units': 'mph', '$': 'Wind Speed'}, {'name': 'W', 'units': '', '$': 'Weather Type'}, {'name': 'P', 'units': 'hpa', '$': 'Pressure'}, {'name': 'Pt', 'units': 'Pa/s', '$': 'Pressure Tendency'}, {'name': 'Dp', 'units': 'C', '$': 'Dew Point'}, {'name': 'H', 'units': '%', '$': 'Screen Relative Humidity'}]}, 'DV': {'dataDate': '2019-01-21T10:00:00Z', 'type': 'Obs', 'Location': {'i': '3772', 'lat': '51.479', 'lon': '-0.449', 'name': 'HEATHROW', 'country': 'ENGLAND', 'continent': 'EUROPE', 'elevation': '25.0', 'Period': [{'type': 'Day', 'value': '2019-01-20Z', 'Rep': [{'D': 'N', 'H': '83.9', 'P': '1017', 'S': '3', 'T': '1.8', 'V': '11000', 'W': '7', 'Pt': 'R', 'Dp': '-0.6', '$': '600'}, {'D': 'NNE', 'H': '78.2', 'P': '1018', 'S': '5', 'T': '3.3', 'V': '11000', 'W': '1', 'Pt': 'R', 'Dp': '-0.1', '$': '660'}, {'D': 'NE', 'H': '70.0', 'P': '1018', 'S': '6', 'T': '4.3', 'V': '16000', 'W': '1', 'Pt': 'R', 'Dp': '-0.6', '$': '720'}, {'D': 'NNE', 'H': '64.7', 'P': '1018', 'S': '5', 'T': '5.1', 'V': '14000', 'W': '1', 'Pt': 'R', 'Dp': '-0.9', '$': '780'}, {'D': 'NNE', 'H': '60.2', 'P': '1018', 'S': '5', 'T': '5.6', 'V': '17000', 'W': '1', 'Pt': 'R', 'Dp': '-1.4', '$': '840'}, {'D': 'N', 'H': '54.5', 'P': '1019', 'S': '6', 'T': '5.4', 'V': '21000', 'W': '1', 'Pt': 'R', 'Dp': '-2.9', '$': '900'}, {'D': 'N', 'H': '60.5', 'P': '1020', 'S': '5', 'T': '4.9', 'V': '21000', 'W': '1', 'Pt': 'R', 'Dp': '-2.0', '$': '960'}, {'D': 'N', 'H': '68.3', 'P': '1021', 'S': '3', 'T': '3.3', 'V': '15000', 'W': '0', 'Pt': 'R', 'Dp': '-1.9', '$': '1020'}, {'D': 'NNE', 'H': '73.4', 'P': '1021', 'S': '3', 'T': '2.3', 'V': '14000', 'W': '0', 'Pt': 'R', 'Dp': '-1.9', '$': '1080'}, {'D': 'NNE', 'H': '77.8', 'P': '1022', 'S': '3', 'T': '1.6', 'V': '11000', 'W': '0', 'Pt': 'R', 'Dp': '-1.8', '$': '1140'}, {'D': 'N', 'H': '82.5', 'P': '1022', 'S': '2', 'T': '1.1', 'V': '8000', 'W': '0', 'Pt': 'R', 'Dp': '-1.5', '$': '1200'}, {'D': 'NNW', 'H': '84.7', 'P': '1023', 'S': '3', 'T': '0.1', 'V': '6000', 'W': '0', 'Pt': 'R', 'Dp': '-1.9', '$': '1260'}, {'D': 'N', 'H': '85.4', 'P': '1024', 'S': '3', 'T': '0.1', 'V': '7000', 'W': '2', 'Pt': 'R', 'Dp': '-1.8', '$': '1320'}, {'D': 'NNE', 'H': '87.6', 'P': '1024', 'S': '2', 'T': '0.2', 'V': '7000', 'W': '7', 'Pt': 'R', 'Dp': '-1.4', '$': '1380'}]}, {'type': 'Day', 'value': '2019-01-21Z', 'Rep': [{'D': 'WNW', 'H': '87.7', 'P': '1024', 'S': '1', 'T': '-1.4', 'V': '5000', 'W': '0', 'Pt': 'R', 'Dp': '-2.8', '$': '0'}, {'D': 'NNW', 'H': '91.8', 'P': '1024', 'S': '2', 'T': '-1.8', 'V': '4400', 'W': '5', 'Pt': 'R', 'Dp': '-2.6', '$': '60'}, {'D': 'NW', 'H': '93.4', 'P': '1025', 'S': '1', 'T': '-1.9', 'V': '4200', 'W': '5', 'Pt': 'R', 'Dp': '-2.5', '$': '120'}, {'D': 'ESE', 'H': '92.2', 'P': '1024', 'S': '1', 'T': '-2.0', 'V': '4200', 'W': '5', 'Pt': 'R', 'Dp': '-2.7', '$': '180'}, {'D': 'SSW', 'H': '91.8', 'P': '1024', 'S': '1', 'T': '-1.8', 'V': '5000', 'W': '5', 'Pt': 'F', 'Dp': '-2.6', '$': '240'}, {'D': 'W', 'H': '94.5', 'P': '1024', 'S': '1', 'T': '-1.6', 'V': '4800', 'W': '5', 'Pt': 'F', 'Dp': '-2.1', '$': '300'}, {'D': 'ESE', 'H': '93.8', 'P': '1024', 'S': '5', 'T': '-1.4', 'V': '4100', 'W': '5', 'Pt': 'S', 'Dp': '-2.0', '$': '360'}, {'D': 'SSE', 'H': '92.2', 'P': '1024', 'S': '3', 'T': '-0.5', 'V': '6000', 'W': '5', 'Pt': 'R', 'Dp': '-1.4', '$': '420'}, {'D': 'WSW', 'H': '91.3', 'P': '1024', 'S': '2', 'T': '0.2', 'V': '6000', 'W': '8', 'Pt': 'R', 'Dp': '-0.9', '$': '480'}, {'D': 'WNW', 'H': '88.9', 'P': '1024', 'S': '2', 'T': '1.2', 'V': '6000', 'W': '8', 'Pt': 'R', 'Dp': '-0.4', '$': '540'}, {'D': 'SW', 'H': '89.1', 'P': '1025', 'S': '5', 'T': '2.4', 'V': '6000', 'W': '8', 'Pt': 'R', 'Dp': '0.8', '$': '600'}]}]}}}}\n"
     ]
    }
   ],
   "source": [
    "print(weather)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#using the function\n",
    "data = processMetOfficeObservations(weather['SiteRep']['DV']['Location'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts</th>\n",
       "      <th>D</th>\n",
       "      <th>Pt</th>\n",
       "      <th>W</th>\n",
       "      <th>V</th>\n",
       "      <th>S</th>\n",
       "      <th>G</th>\n",
       "      <th>T</th>\n",
       "      <th>Dp</th>\n",
       "      <th>H</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>11000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>83.9</td>\n",
       "      <td>3772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>78.2</td>\n",
       "      <td>3772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>NE</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>16000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>70.0</td>\n",
       "      <td>3772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>14000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>64.7</td>\n",
       "      <td>3772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    ts    D Pt  W      V  S  G    T    Dp     H    id\n",
       "0  2019-01-20 10:00:00    N  R  7  11000  3  0  1.8  -0.6  83.9  3772\n",
       "1  2019-01-20 11:00:00  NNE  R  1  11000  5  0  3.3  -0.1  78.2  3772\n",
       "2  2019-01-20 12:00:00   NE  R  1  16000  6  0  4.3  -0.6  70.0  3772\n",
       "3  2019-01-20 13:00:00  NNE  R  1  14000  5  0  5.1  -0.9  64.7  3772"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = pd.DataFrame.from_dict( data )\n",
    "# add one more parameter to indicate the station id - say, where the data from\n",
    "df3['id'] = station\n",
    "df3.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 7: Obtaining Weather Data in the UK ( its your turn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here you are going to repeat what has been done in Task 6. But instead of querying only 1 station, you need to write a loop to query all weather station in the UK and put the data into a DataFrame called weather_df.\n",
    "\n",
    "Hints: first you get all unique ids of weather stations; then you write a loop to iterate all station ids; Each time you request data of one station, you convert the JSON into a new DataFrame; then you join the new dataframe to the weather_df (not sure what operation to use, then check [FROM HERE](https://pandas.pydata.org/pandas-docs/stable/merging.html)); After you gather all data from all station, rename the columns to make it easy understood and reset index to make it ready for query. That's it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts</th>\n",
       "      <th>D</th>\n",
       "      <th>Pt</th>\n",
       "      <th>W</th>\n",
       "      <th>V</th>\n",
       "      <th>S</th>\n",
       "      <th>G</th>\n",
       "      <th>T</th>\n",
       "      <th>Dp</th>\n",
       "      <th>H</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [ts, D, Pt, W, V, S, G, T, Dp, H, id]\n",
       "Index: []"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df = df3.iloc[0:0] # so the big container is prepared for you, you just have to fill it with data.\n",
    "weather_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get station ids here\n",
    "uk_ids = site_df.id.unique()\n",
    "len(uk_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the answer should be something like 148 (data updates all the time as we are using streaming data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "weather station id is 3066\n",
      "weather station id is 3068\n",
      "weather station id is 3075\n",
      "weather station id is 3002\n",
      "weather station id is 3005\n",
      "weather station id is 3008\n",
      "weather station id is 3034\n",
      "weather station id is 3044\n",
      "weather station id is 3047\n",
      "weather station id is 3796\n",
      "weather station id is 3803\n",
      "weather station id is 3857\n",
      "weather station id is 3876\n",
      "weather station id is 3895\n",
      "weather station id is 3911\n",
      "weather station id is 3916\n",
      "weather station id is 3953\n",
      "weather station id is 99081\n",
      "weather station id is 3520\n",
      "weather station id is 3522\n",
      "weather station id is 3535\n",
      "weather station id is 3560\n",
      "weather station id is 3605\n",
      "weather station id is 3647\n",
      "weather station id is 3660\n",
      "weather station id is 3684\n",
      "weather station id is 3716\n",
      "weather station id is 3740\n",
      "weather station id is 3768\n",
      "weather station id is 3153\n",
      "weather station id is 3155\n",
      "weather station id is 3162\n",
      "weather station id is 3166\n",
      "weather station id is 3226\n",
      "weather station id is 3230\n",
      "weather station id is 3238\n",
      "weather station id is 3257\n",
      "weather station id is 3266\n",
      "weather station id is 3462\n",
      "weather station id is 3482\n",
      "weather station id is 3907\n",
      "weather station id is 3063\n",
      "weather station id is 3100\n",
      "weather station id is 3809\n",
      "weather station id is 3840\n",
      "weather station id is 3862\n",
      "weather station id is 3976\n",
      "weather station id is 3710\n",
      "weather station id is 3743\n",
      "weather station id is 3746\n",
      "weather station id is 3769\n",
      "weather station id is 3171\n",
      "weather station id is 3281\n",
      "weather station id is 3302\n",
      "weather station id is 3344\n",
      "weather station id is 3379\n",
      "weather station id is 3392\n",
      "weather station id is 3414\n",
      "weather station id is 3065\n",
      "weather station id is 3091\n",
      "weather station id is 3105\n",
      "weather station id is 3010\n",
      "weather station id is 3853\n",
      "weather station id is 3980\n",
      "weather station id is 99057\n",
      "weather station id is 3529\n",
      "weather station id is 3604\n",
      "weather station id is 3693\n",
      "weather station id is 3749\n",
      "weather station id is 3761\n",
      "weather station id is 3132\n",
      "weather station id is 3136\n",
      "weather station id is 3158\n",
      "weather station id is 3210\n",
      "weather station id is 3212\n",
      "weather station id is 3220\n",
      "weather station id is 3224\n",
      "weather station id is 3316\n",
      "weather station id is 3377\n",
      "weather station id is 3410\n",
      "weather station id is 3488\n",
      "weather station id is 3351\n",
      "weather station id is 3680\n",
      "weather station id is 3080\n",
      "weather station id is 3088\n",
      "weather station id is 3111\n",
      "weather station id is 3026\n",
      "weather station id is 3031\n",
      "weather station id is 3039\n",
      "weather station id is 3808\n",
      "weather station id is 3866\n",
      "weather station id is 3872\n",
      "weather station id is 3882\n",
      "weather station id is 3904\n",
      "weather station id is 3952\n",
      "weather station id is 99060\n",
      "weather station id is 3503\n",
      "weather station id is 3507\n",
      "weather station id is 3649\n",
      "weather station id is 3672\n",
      "weather station id is 3707\n",
      "weather station id is 3772\n",
      "weather station id is 3134\n",
      "weather station id is 3214\n",
      "weather station id is 3225\n",
      "weather station id is 3227\n",
      "weather station id is 3330\n",
      "weather station id is 3373\n",
      "weather station id is 3405\n",
      "weather station id is 3023\n",
      "weather station id is 3041\n",
      "weather station id is 3797\n",
      "weather station id is 3827\n",
      "weather station id is 3923\n",
      "weather station id is 3502\n",
      "weather station id is 3544\n",
      "weather station id is 3275\n",
      "weather station id is 3305\n",
      "weather station id is 3469\n",
      "weather station id is 3017\n",
      "weather station id is 3781\n",
      "weather station id is 3894\n",
      "weather station id is 3917\n",
      "weather station id is 3590\n",
      "weather station id is 3609\n",
      "weather station id is 3658\n",
      "weather station id is 3144\n",
      "weather station id is 3148\n",
      "weather station id is 3204\n",
      "weather station id is 3240\n",
      "weather station id is 3265\n",
      "weather station id is 3292\n",
      "weather station id is 3313\n",
      "weather station id is 3321\n",
      "weather station id is 3354\n",
      "weather station id is 3382\n",
      "weather station id is 3385\n",
      "weather station id is 3391\n",
      "weather station id is 99142\n",
      "weather station id is 3844\n"
     ]
    }
   ],
   "source": [
    "# loop here\n",
    "for stn in uk_ids:\n",
    "    station = str(stn)\n",
    "    r = requests.get(api_url + obs_json + station, params=payload)\n",
    "    weather = r.json() # Capture the reply    \n",
    "    if 'Location' not in weather['SiteRep']['DV']: # if there is no keyword - location, means no data coming in\n",
    "        continue\n",
    "    else:\n",
    "        print('weather station id is %s' %(station) )\n",
    "        test = processMetOfficeObservations(weather['SiteRep']['DV']['Location'])\n",
    "        df3_new = pd.DataFrame.from_dict(test)\n",
    "        df3_new['id'] = station \n",
    "        weather_df = weather_df.append(df3_new)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#change column names here. \n",
    "cnames = {'D' : 'WindDirection', \n",
    "          'G' : 'WindGust', \n",
    "          'Dp': 'DewPoint', \n",
    "          'H' : 'Humidity', \n",
    "          'P' : 'PressureTendency', \n",
    "          'S' : 'WindSpeed', \n",
    "          'T' : 'Temperature', \n",
    "          'W' : 'WeatherType', \n",
    "          'V' : 'Visibility', \n",
    "          'Pt': 'PressureTendency',\n",
    "          'id': 'id',\n",
    "          'ts': 'DateTime'\n",
    "         }\n",
    "\n",
    "weather_df.rename(columns=cnames, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>WindDirection</th>\n",
       "      <th>PressureTendency</th>\n",
       "      <th>WeatherType</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>WindGust</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>6000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>93.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>35000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>86.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>14</td>\n",
       "      <td>9000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>35000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>85.2</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>45000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>27000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.2</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>27000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>84.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>77.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>77.9</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>76.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>81.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>77.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>77.8</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>75.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>76.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>45000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>50000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>73.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>74.9</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>73.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>30000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>84.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>78.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>84.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>81.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>82.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.5</td>\n",
       "      <td>91.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>83.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>82.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>81.9</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>78.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>83.1</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>77.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-3.8</td>\n",
       "      <td>78.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>79.5</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>50000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>50000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>82.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>80.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>78.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>78.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>16000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>93.8</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>27000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>6000</td>\n",
       "      <td>25</td>\n",
       "      <td>38</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>35000</td>\n",
       "      <td>14</td>\n",
       "      <td>29</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>28000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>93.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>21000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>92.3</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>88.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>35000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>89.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>88.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>35000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>88.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.4</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>86.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>84.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>26000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>81.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>89.9</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.2</td>\n",
       "      <td>89.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>8000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.7</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>28000</td>\n",
       "      <td>24</td>\n",
       "      <td>33</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.4</td>\n",
       "      <td>90.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>24</td>\n",
       "      <td>43</td>\n",
       "      <td>5.3</td>\n",
       "      <td>2.2</td>\n",
       "      <td>80.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>26</td>\n",
       "      <td>36</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.9</td>\n",
       "      <td>80.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>84.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>24000</td>\n",
       "      <td>25</td>\n",
       "      <td>38</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>78.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>14000</td>\n",
       "      <td>22</td>\n",
       "      <td>34</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>23</td>\n",
       "      <td>32</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>66.7</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>22000</td>\n",
       "      <td>21</td>\n",
       "      <td>31</td>\n",
       "      <td>4.2</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>71.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>24000</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>66.5</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>30</td>\n",
       "      <td>4.5</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>67.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>25000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>66.7</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>7000</td>\n",
       "      <td>21</td>\n",
       "      <td>32</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>84.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>27000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>77.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>25000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>25000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.2</td>\n",
       "      <td>89.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>19000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>91.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>21000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>28000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>92.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>45000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>16000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.6</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>17000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>91.3</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>9000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.6</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>16000</td>\n",
       "      <td>21</td>\n",
       "      <td>34</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>24000</td>\n",
       "      <td>16</td>\n",
       "      <td>31</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>79.6</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74.6</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>30000</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.1</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>75.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>19</td>\n",
       "      <td>31</td>\n",
       "      <td>3.8</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>73.2</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>29</td>\n",
       "      <td>3.3</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>74.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>35000</td>\n",
       "      <td>18</td>\n",
       "      <td>30</td>\n",
       "      <td>3.2</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>77.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>72.7</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>73.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>69.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>66.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>76.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>29000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>82.4</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.9</td>\n",
       "      <td>81.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.9</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>19000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>23000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>87.4</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>88.1</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>7000</td>\n",
       "      <td>19</td>\n",
       "      <td>32</td>\n",
       "      <td>5.4</td>\n",
       "      <td>4.2</td>\n",
       "      <td>92.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>11</td>\n",
       "      <td>9000</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>5.6</td>\n",
       "      <td>3.5</td>\n",
       "      <td>86.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>76.5</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>17</td>\n",
       "      <td>44</td>\n",
       "      <td>5.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>76.9</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>24</td>\n",
       "      <td>37</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>70.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>7000</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>77.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>18</td>\n",
       "      <td>43</td>\n",
       "      <td>3.6</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>72.2</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>24</td>\n",
       "      <td>38</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>74.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>28000</td>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>75.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>13</td>\n",
       "      <td>14000</td>\n",
       "      <td>25</td>\n",
       "      <td>41</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>81.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>36</td>\n",
       "      <td>5.3</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>63.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>17000</td>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.1</td>\n",
       "      <td>72.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>35000</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>65.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>61.6</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>29000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>68.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>18000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>1.8</td>\n",
       "      <td>77.9</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.7</td>\n",
       "      <td>80.1</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>82.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>22000</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>87.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>13000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>84.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>16000</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.5</td>\n",
       "      <td>81.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>26000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>80.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>22000</td>\n",
       "      <td>22</td>\n",
       "      <td>29</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>81.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>4900</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>7000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>91.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>11</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>87.9</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4100</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>89.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>3300</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.9</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3200</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4100</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>92.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>10000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.9</td>\n",
       "      <td>90.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>8000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>11000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>13000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>NE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>11000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>87.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>9000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>88.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>95.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3300</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>3600</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>95.1</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>3400</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>95.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3900</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>93.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3500</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>97.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>6000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.9</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.1</td>\n",
       "      <td>82.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>78.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>1.1</td>\n",
       "      <td>80.0</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>82.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3900</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.4</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>2800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>95.1</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>89.2</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.6</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>15000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.3</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>S</td>\n",
       "      <td>9</td>\n",
       "      <td>13000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>89.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3500</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>92.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>4100</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>94.6</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>8000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>96.1</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>500</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>98.0</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2900</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>99.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>8000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>92.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>14000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>77.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>21000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.3</td>\n",
       "      <td>67.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>22000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>64.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>20000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>67.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>16000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>74.3</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>83.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>93.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.4</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>S</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>95.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.3</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>21000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.5</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>17000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>93.6</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>9000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.9</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>21000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>9000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>96.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>93.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>8000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>83.6</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>15000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>69.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>65.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>68.0</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>15000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>75.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>83.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>85.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>86.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>86.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>8000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>89.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.2</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.1</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>94.3</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>2200</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>4000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>98.6</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>95.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>94.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>93.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.9</td>\n",
       "      <td>93.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>90.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.6</td>\n",
       "      <td>91.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>96.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>95.0</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>88.0</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>87.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.4</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.8</td>\n",
       "      <td>93.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>90.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>91.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>89.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.6</td>\n",
       "      <td>95.2</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>94.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>93.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>89.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>89.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>89.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>91.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>90.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>14000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>85.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>13000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>4.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>15000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4.7</td>\n",
       "      <td>85.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>12000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>4.2</td>\n",
       "      <td>88.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>4.2</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>4.1</td>\n",
       "      <td>88.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>88.6</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.8</td>\n",
       "      <td>89.3</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>7000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.8</td>\n",
       "      <td>95.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3900</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3800</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>97.8</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>98.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>2800</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>ESE</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>3800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>98.6</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>97.1</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>99.4</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>99.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>200</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1.1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3499 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               DateTime WindDirection PressureTendency WeatherType Visibility  \\\n",
       "0   2019-01-20 10:00:00           WSW                R          12       6000   \n",
       "1   2019-01-20 11:00:00            SW                R           8      45000   \n",
       "2   2019-01-20 12:00:00           WSW                R          10      40000   \n",
       "3   2019-01-20 13:00:00             W                R           8      35000   \n",
       "4   2019-01-20 14:00:00             W                R          14       9000   \n",
       "5   2019-01-20 15:00:00             W                R           1      35000   \n",
       "6   2019-01-20 16:00:00           WSW                R           2      45000   \n",
       "7   2019-01-20 17:00:00             W                R           7      28000   \n",
       "8   2019-01-20 18:00:00           WSW                R           0      27000   \n",
       "9   2019-01-20 19:00:00            SW                R           0      27000   \n",
       "10  2019-01-20 20:00:00           WSW                R           0      30000   \n",
       "11  2019-01-20 21:00:00           WSW                R           0      40000   \n",
       "12  2019-01-20 22:00:00            SW                R           0      40000   \n",
       "13  2019-01-20 23:00:00           SSW                R           0      45000   \n",
       "14  2019-01-21 00:00:00           SSW                R           0      40000   \n",
       "15  2019-01-21 01:00:00           SSW                F           0      40000   \n",
       "16  2019-01-21 02:00:00           SSW                F           0      40000   \n",
       "17  2019-01-21 03:00:00           SSW                F           0      45000   \n",
       "18  2019-01-21 04:00:00             S                F           0      50000   \n",
       "19  2019-01-21 05:00:00             S                F           2      40000   \n",
       "20  2019-01-21 06:00:00             S                F           2      50000   \n",
       "21  2019-01-21 07:00:00           SSW                F           7      45000   \n",
       "22  2019-01-21 08:00:00             S                F           8      50000   \n",
       "23  2019-01-21 09:00:00           SSW                F           8      45000   \n",
       "24  2019-01-21 10:00:00           SSW                F           8      40000   \n",
       "0   2019-01-20 10:00:00           WSW                R          12      30000   \n",
       "1   2019-01-20 11:00:00           WSW                R           7      25000   \n",
       "2   2019-01-20 12:00:00           WSW                R           7      30000   \n",
       "3   2019-01-20 13:00:00             W                R           7      30000   \n",
       "4   2019-01-20 14:00:00             W                R           7      30000   \n",
       "5   2019-01-20 15:00:00             W                R           3      30000   \n",
       "6   2019-01-20 16:00:00             W                R           9      30000   \n",
       "7   2019-01-20 17:00:00             W                R           2      30000   \n",
       "8   2019-01-20 18:00:00           WSW                R           2      30000   \n",
       "9   2019-01-20 19:00:00            SW                R           2      40000   \n",
       "10  2019-01-20 20:00:00             W                R           2      40000   \n",
       "11  2019-01-20 21:00:00            SW                R           0      40000   \n",
       "12  2019-01-20 22:00:00            SW                R           0      40000   \n",
       "13  2019-01-20 23:00:00           WSW                R           0      40000   \n",
       "14  2019-01-21 00:00:00           WSW                R           0      40000   \n",
       "15  2019-01-21 01:00:00           WSW                F           0      40000   \n",
       "16  2019-01-21 02:00:00            SW                F           0      40000   \n",
       "17  2019-01-21 03:00:00           SSW                F           0      40000   \n",
       "18  2019-01-21 04:00:00            SW                F           2      40000   \n",
       "19  2019-01-21 05:00:00             S                F           2      50000   \n",
       "20  2019-01-21 06:00:00             S                F           7      50000   \n",
       "21  2019-01-21 07:00:00             S                F           7      50000   \n",
       "22  2019-01-21 08:00:00             S                F           7      40000   \n",
       "23  2019-01-21 09:00:00             S                F           7      40000   \n",
       "24  2019-01-21 10:00:00             S                F           7      40000   \n",
       "0   2019-01-20 10:00:00             W                R          12      16000   \n",
       "1   2019-01-20 11:00:00             W                R           8      20000   \n",
       "2   2019-01-20 12:00:00             W                R           8      27000   \n",
       "3   2019-01-20 13:00:00           WNW                R           3      40000   \n",
       "4   2019-01-20 14:00:00             W                R          10       6000   \n",
       "5   2019-01-20 15:00:00             W                R           1      35000   \n",
       "6   2019-01-20 16:00:00             W                R           2      28000   \n",
       "7   2019-01-20 17:00:00             W                R           7      21000   \n",
       "8   2019-01-20 18:00:00           WSW                R           0      30000   \n",
       "9   2019-01-20 19:00:00             W                R           2      30000   \n",
       "10  2019-01-20 20:00:00             W                R           2      35000   \n",
       "11  2019-01-20 21:00:00           WSW                R           0      30000   \n",
       "12  2019-01-20 22:00:00           WSW                R           0      35000   \n",
       "13  2019-01-20 23:00:00           WSW                R           7      35000   \n",
       "14  2019-01-21 00:00:00           WSW                R           7      35000   \n",
       "15  2019-01-21 01:00:00           WSW                F           0      45000   \n",
       "16  2019-01-21 02:00:00           SSW                F           7      40000   \n",
       "17  2019-01-21 03:00:00            SW                F           2      50000   \n",
       "18  2019-01-21 04:00:00             S                F           2      40000   \n",
       "19  2019-01-21 05:00:00             S                F           2      40000   \n",
       "20  2019-01-21 06:00:00           SSW                F           7      30000   \n",
       "21  2019-01-21 07:00:00             S                F           7      30000   \n",
       "22  2019-01-21 08:00:00             S                F           8      30000   \n",
       "23  2019-01-21 09:00:00             S                F           8      26000   \n",
       "24  2019-01-21 10:00:00             S                F           8      30000   \n",
       "0   2019-01-20 10:00:00           SSW                F           7      40000   \n",
       "1   2019-01-20 11:00:00           SSW                F           7      35000   \n",
       "2   2019-01-20 12:00:00           SSW                F          10       8000   \n",
       "3   2019-01-20 13:00:00           WNW                F          12      28000   \n",
       "4   2019-01-20 14:00:00           WNW                R           7      26000   \n",
       "5   2019-01-20 15:00:00           WNW                R           7      30000   \n",
       "6   2019-01-20 16:00:00            NW                R           7      25000   \n",
       "7   2019-01-20 17:00:00           WNW                R           8      24000   \n",
       "8   2019-01-20 18:00:00            NW                R           9      14000   \n",
       "9   2019-01-20 19:00:00           WNW                R           2      30000   \n",
       "10  2019-01-20 20:00:00           WNW                R           2      22000   \n",
       "11  2019-01-20 21:00:00           WNW                R           2      24000   \n",
       "12  2019-01-20 22:00:00           WNW                R           2      23000   \n",
       "13  2019-01-20 23:00:00           WNW                R           0      45000   \n",
       "14  2019-01-21 00:00:00           WNW                R           2      25000   \n",
       "15  2019-01-21 01:00:00             W                R           9       7000   \n",
       "16  2019-01-21 02:00:00             W                R           7      27000   \n",
       "17  2019-01-21 03:00:00           WSW                F           8      25000   \n",
       "18  2019-01-21 04:00:00           SSW                F           8      25000   \n",
       "19  2019-01-21 05:00:00           SSW                F           8      19000   \n",
       "20  2019-01-21 06:00:00           SSW                F           7      28000   \n",
       "21  2019-01-21 07:00:00           SSW                F           0      21000   \n",
       "22  2019-01-21 08:00:00           SSW                F           2      28000   \n",
       "23  2019-01-21 09:00:00           SSW                F           7      45000   \n",
       "24  2019-01-21 10:00:00             S                F          10      16000   \n",
       "0   2019-01-20 10:00:00           SSW                F           7      17000   \n",
       "1   2019-01-20 11:00:00           SSW                F          12       9000   \n",
       "2   2019-01-20 12:00:00           WNW                F          12      16000   \n",
       "3   2019-01-20 13:00:00           WNW                R           7      24000   \n",
       "4   2019-01-20 14:00:00           WNW                R           7      30000   \n",
       "5   2019-01-20 15:00:00           WNW                R          10      30000   \n",
       "6   2019-01-20 16:00:00           WNW                R           7      28000   \n",
       "7   2019-01-20 17:00:00           WNW                R           7      30000   \n",
       "8   2019-01-20 18:00:00           WNW                R           7      30000   \n",
       "9   2019-01-20 19:00:00           WNW                R           2      30000   \n",
       "10  2019-01-20 20:00:00           WNW                R           0      35000   \n",
       "11  2019-01-20 21:00:00           WNW                R           0      30000   \n",
       "12  2019-01-20 22:00:00             W                R           7      25000   \n",
       "13  2019-01-20 23:00:00           WNW                R           2      30000   \n",
       "14  2019-01-21 00:00:00           WNW                R           2      30000   \n",
       "15  2019-01-21 01:00:00             W                R           7      30000   \n",
       "16  2019-01-21 02:00:00             W                F           7      28000   \n",
       "17  2019-01-21 03:00:00           WSW                F           7      29000   \n",
       "18  2019-01-21 04:00:00            SW                F           7      26000   \n",
       "19  2019-01-21 05:00:00           WSW                F           2      45000   \n",
       "20  2019-01-21 06:00:00           SSW                F           9      40000   \n",
       "21  2019-01-21 07:00:00            SW                F           8      10000   \n",
       "22  2019-01-21 08:00:00           SSW                F           9      19000   \n",
       "23  2019-01-21 09:00:00            SW                F           8      20000   \n",
       "24  2019-01-21 10:00:00           SSW                F           8      23000   \n",
       "0   2019-01-20 10:00:00           SSW                R           7      40000   \n",
       "1   2019-01-20 11:00:00           WSW                R          12       7000   \n",
       "2   2019-01-20 12:00:00           WNW                R          11       9000   \n",
       "3   2019-01-20 13:00:00           WNW                R           7      26000   \n",
       "4   2019-01-20 14:00:00           WNW                R           3      30000   \n",
       "5   2019-01-20 15:00:00           WNW                R           3      30000   \n",
       "6   2019-01-20 16:00:00            NW                R           9       7000   \n",
       "7   2019-01-20 17:00:00            NW                R           2      40000   \n",
       "8   2019-01-20 18:00:00             W                R           7      26000   \n",
       "9   2019-01-20 19:00:00           WNW                R           0      28000   \n",
       "10  2019-01-20 20:00:00           WNW                R          13      14000   \n",
       "11  2019-01-20 21:00:00           WNW                R           2      23000   \n",
       "12  2019-01-20 22:00:00           WNW                R           9      17000   \n",
       "13  2019-01-20 23:00:00           WNW                R           2      35000   \n",
       "14  2019-01-21 00:00:00             W                R           0      30000   \n",
       "15  2019-01-21 01:00:00             W                R           2      29000   \n",
       "16  2019-01-21 02:00:00             W                F           7      18000   \n",
       "17  2019-01-21 03:00:00           WSW                F           7      28000   \n",
       "18  2019-01-21 04:00:00            SW                F           7      23000   \n",
       "19  2019-01-21 05:00:00            SW                F           2      22000   \n",
       "20  2019-01-21 06:00:00            SW                F           7      30000   \n",
       "21  2019-01-21 07:00:00            SW                F           7      13000   \n",
       "22  2019-01-21 08:00:00            SW                F           2      16000   \n",
       "23  2019-01-21 09:00:00           SSW                F           8      26000   \n",
       "24  2019-01-21 10:00:00           SSW                F           3      22000   \n",
       "..                  ...           ...              ...         ...        ...   \n",
       "0   2019-01-20 10:00:00             E                R           5       4900   \n",
       "1   2019-01-20 11:00:00             S                R           8       7000   \n",
       "2   2019-01-20 12:00:00            SW                R          11       5000   \n",
       "3   2019-01-20 13:00:00            SW                R           8       6000   \n",
       "4   2019-01-20 14:00:00           WSW                R           8       6000   \n",
       "5   2019-01-20 15:00:00             W                R           8       4100   \n",
       "6   2019-01-20 16:00:00           WSW                R           8       3300   \n",
       "7   2019-01-20 17:00:00             W                R           7       3200   \n",
       "8   2019-01-20 18:00:00            NW                R           8       4100   \n",
       "9   2019-01-20 19:00:00           WNW                R           0       6000   \n",
       "10  2019-01-20 20:00:00           WNW                R           0      10000   \n",
       "11  2019-01-20 21:00:00           WNW                R           2       8000   \n",
       "12  2019-01-20 22:00:00           NNW                R           7      11000   \n",
       "13  2019-01-20 23:00:00            NW                R           8      13000   \n",
       "14  2019-01-21 00:00:00            NE                R           8      11000   \n",
       "15  2019-01-21 01:00:00           WNW                R           8      10000   \n",
       "16  2019-01-21 02:00:00            NW                R           8      10000   \n",
       "17  2019-01-21 03:00:00           WNW                R           7       9000   \n",
       "18  2019-01-21 04:00:00            NW                F           8       8000   \n",
       "19  2019-01-21 05:00:00           NNW                F           9       5000   \n",
       "20  2019-01-21 06:00:00             W                F           8       5000   \n",
       "21  2019-01-21 07:00:00           WSW                F           5       3300   \n",
       "22  2019-01-21 08:00:00           WSW                F          12       3600   \n",
       "23  2019-01-21 09:00:00           WSW                F           8       3400   \n",
       "24  2019-01-21 10:00:00            SW                F           5       3900   \n",
       "0   2019-01-20 10:00:00             S                R           5       3500   \n",
       "1   2019-01-20 11:00:00            SW                R           5       6000   \n",
       "2   2019-01-20 12:00:00             S                R           8       9000   \n",
       "3   2019-01-20 13:00:00           SSW                R           8      10000   \n",
       "4   2019-01-20 14:00:00           WSW                R           8       9000   \n",
       "5   2019-01-20 15:00:00           WSW                R           8       9000   \n",
       "6   2019-01-20 16:00:00           WSW                R           7       5000   \n",
       "7   2019-01-20 17:00:00             W                R           7       3900   \n",
       "8   2019-01-20 18:00:00             W                R           5       3000   \n",
       "9   2019-01-20 19:00:00            SW                R           5       2800   \n",
       "10  2019-01-20 20:00:00           WNW                R           5       3000   \n",
       "11  2019-01-20 21:00:00             W                R           7       5000   \n",
       "12  2019-01-20 22:00:00            NW                R           8       9000   \n",
       "13  2019-01-20 23:00:00           WNW                R           7       7000   \n",
       "14  2019-01-21 00:00:00           WNW                R           7      10000   \n",
       "15  2019-01-21 01:00:00            NW                R           8      12000   \n",
       "16  2019-01-21 02:00:00            NW                R           8      15000   \n",
       "17  2019-01-21 03:00:00            NW                R           2      11000   \n",
       "18  2019-01-21 04:00:00           NNW                S           9      13000   \n",
       "19  2019-01-21 05:00:00             W                F           2       5000   \n",
       "20  2019-01-21 06:00:00           WSW                F           5       3500   \n",
       "21  2019-01-21 07:00:00           WSW                F           5       4100   \n",
       "22  2019-01-21 08:00:00             W                F           5       8000   \n",
       "23  2019-01-21 09:00:00             W                F           6        500   \n",
       "24  2019-01-21 10:00:00             S                F           7       2900   \n",
       "0   2019-01-20 10:00:00           WSW                R           1      11000   \n",
       "1   2019-01-20 11:00:00           WSW                R           1       8000   \n",
       "2   2019-01-20 12:00:00           SSW                R           1      14000   \n",
       "3   2019-01-20 13:00:00             S                R           1      21000   \n",
       "4   2019-01-20 14:00:00             S                R           1      22000   \n",
       "5   2019-01-20 15:00:00            SW                R           7      20000   \n",
       "6   2019-01-20 16:00:00            SW                R           7      16000   \n",
       "7   2019-01-20 17:00:00            SW                R           8      12000   \n",
       "8   2019-01-20 18:00:00            SW                R           8      10000   \n",
       "9   2019-01-20 19:00:00            SW                R           8       8000   \n",
       "10  2019-01-20 20:00:00           SSW                R           8       8000   \n",
       "11  2019-01-20 21:00:00           WSW                R           7       7000   \n",
       "12  2019-01-20 22:00:00             W                R           8       6000   \n",
       "13  2019-01-20 23:00:00             W                R           8       6000   \n",
       "14  2019-01-21 00:00:00             W                R           8       8000   \n",
       "15  2019-01-21 01:00:00             W                R           8       9000   \n",
       "16  2019-01-21 02:00:00           WNW                R           8       9000   \n",
       "17  2019-01-21 03:00:00           WNW                R           8       9000   \n",
       "18  2019-01-21 04:00:00           WNW                S           8       8000   \n",
       "19  2019-01-21 05:00:00           NNW                F           8      20000   \n",
       "20  2019-01-21 06:00:00            NW                F           7      21000   \n",
       "21  2019-01-21 07:00:00           WSW                F           0      17000   \n",
       "22  2019-01-21 08:00:00           WSW                F           1       9000   \n",
       "23  2019-01-21 09:00:00           WSW                F           1      21000   \n",
       "24  2019-01-21 10:00:00            SW                F           1       9000   \n",
       "0   2019-01-20 10:00:00           NNW                R           3       5000   \n",
       "1   2019-01-20 11:00:00           WNW                R           3       8000   \n",
       "2   2019-01-20 12:00:00             W                R           1      10000   \n",
       "3   2019-01-20 13:00:00            SW                R           1      15000   \n",
       "4   2019-01-20 14:00:00           SSW                R           1      20000   \n",
       "5   2019-01-20 15:00:00             W                R           1      20000   \n",
       "6   2019-01-20 16:00:00             W                R           3      15000   \n",
       "7   2019-01-20 17:00:00            SW                R           7      12000   \n",
       "8   2019-01-20 18:00:00           SSW                R           7      12000   \n",
       "9   2019-01-20 19:00:00            SW                R           7      10000   \n",
       "10  2019-01-20 20:00:00           WSW                R           7      10000   \n",
       "11  2019-01-20 21:00:00             W                R           7       8000   \n",
       "12  2019-01-20 22:00:00           WSW                R           7       7000   \n",
       "13  2019-01-20 23:00:00             W                R           7       6000   \n",
       "14  2019-01-21 00:00:00            NW                R           7       6000   \n",
       "15  2019-01-21 01:00:00            NW                R           7       5000   \n",
       "16  2019-01-21 02:00:00           WNW                R           7       5000   \n",
       "17  2019-01-21 03:00:00            NW                R           7       6000   \n",
       "18  2019-01-21 04:00:00            NW                F           7       6000   \n",
       "19  2019-01-21 05:00:00            NW                F           7       6000   \n",
       "20  2019-01-21 06:00:00           NNW                F          12       5000   \n",
       "21  2019-01-21 07:00:00             N                F           2       5000   \n",
       "22  2019-01-21 08:00:00             W                F           7       2000   \n",
       "23  2019-01-21 09:00:00             W                F           5       2200   \n",
       "24  2019-01-21 10:00:00             W                F           5       4000   \n",
       "0   2019-01-20 10:00:00                                          0          0   \n",
       "1   2019-01-20 11:00:00                                          0          0   \n",
       "2   2019-01-20 12:00:00                                          0          0   \n",
       "3   2019-01-20 13:00:00                                          0          0   \n",
       "4   2019-01-20 14:00:00                                          0          0   \n",
       "5   2019-01-20 15:00:00                                          0          0   \n",
       "6   2019-01-20 16:00:00                                          0          0   \n",
       "7   2019-01-20 17:00:00                                          0          0   \n",
       "8   2019-01-20 18:00:00                                          0          0   \n",
       "9   2019-01-20 19:00:00                                          0          0   \n",
       "10  2019-01-20 20:00:00                                          0          0   \n",
       "11  2019-01-20 21:00:00                                          0          0   \n",
       "12  2019-01-20 22:00:00                                          0          0   \n",
       "13  2019-01-20 23:00:00                                          0          0   \n",
       "14  2019-01-21 00:00:00                                          0          0   \n",
       "15  2019-01-21 01:00:00                                          0          0   \n",
       "16  2019-01-21 02:00:00                                          0          0   \n",
       "17  2019-01-21 03:00:00                                          0          0   \n",
       "18  2019-01-21 04:00:00                                          0          0   \n",
       "19  2019-01-21 05:00:00                                          0          0   \n",
       "20  2019-01-21 06:00:00                                          0          0   \n",
       "21  2019-01-21 07:00:00                                          0          0   \n",
       "22  2019-01-21 08:00:00                                          0          0   \n",
       "23  2019-01-21 09:00:00                                          0          0   \n",
       "24  2019-01-21 10:00:00                                          0          0   \n",
       "0   2019-01-20 10:00:00           ENE                R           8       9000   \n",
       "1   2019-01-20 11:00:00           NNE                R           8      10000   \n",
       "2   2019-01-20 12:00:00           NNE                R           8      11000   \n",
       "3   2019-01-20 13:00:00             N                R           8      14000   \n",
       "4   2019-01-20 14:00:00           NNE                R           8      13000   \n",
       "5   2019-01-20 15:00:00           NNW                R           8      15000   \n",
       "6   2019-01-20 16:00:00           NNE                R           3      12000   \n",
       "7   2019-01-20 17:00:00           NNE                R           7      12000   \n",
       "8   2019-01-20 18:00:00           NNE                R           8      10000   \n",
       "9   2019-01-20 19:00:00           NNW                R           7      10000   \n",
       "10  2019-01-20 20:00:00           NNE                R           8       8000   \n",
       "11  2019-01-20 21:00:00             N                R           8       8000   \n",
       "12  2019-01-20 22:00:00             N                R           8       8000   \n",
       "13  2019-01-20 23:00:00           WNW                R           2       7000   \n",
       "14  2019-01-21 00:00:00             E                R           7       3900   \n",
       "15  2019-01-21 01:00:00             E                R           7       3800   \n",
       "16  2019-01-21 02:00:00             N                R           8       4300   \n",
       "17  2019-01-21 03:00:00             E                R           8       2800   \n",
       "18  2019-01-21 04:00:00           ESE                F           8       3800   \n",
       "19  2019-01-21 05:00:00           NNE                F           7       2800   \n",
       "20  2019-01-21 06:00:00           WNW                F           0        100   \n",
       "21  2019-01-21 07:00:00             E                F           0         80   \n",
       "22  2019-01-21 08:00:00           ENE                R           0        100   \n",
       "23  2019-01-21 09:00:00           NNE                R           0        100   \n",
       "24  2019-01-21 10:00:00           ENE                F           0        200   \n",
       "\n",
       "   WindSpeed WindGust Temperature DewPoint Humidity     id  \n",
       "0         10        0         2.1      1.2     93.7   3066  \n",
       "1         10        0         2.8      2.0     94.5   3066  \n",
       "2         11        0         3.6      2.2     90.4   3066  \n",
       "3         13        0         4.2      2.2     86.7   3066  \n",
       "4         17        0         3.9      2.2     88.5   3066  \n",
       "5         15        0         3.6      1.4     85.2   3066  \n",
       "6          8        0         2.4      0.5     87.1   3066  \n",
       "7         13        0         2.3      0.7     89.0   3066  \n",
       "8         14        0         2.2      0.0     85.2   3066  \n",
       "9          6        0         0.9     -1.4     84.4   3066  \n",
       "10        11        0         2.3     -1.2     77.3   3066  \n",
       "11        11        0         2.1     -1.3     77.9   3066  \n",
       "12        10        0         1.8     -1.8     76.7   3066  \n",
       "13         9        0         0.8     -1.8     81.1   3066  \n",
       "14         8        0         1.7     -1.8     77.3   3066  \n",
       "15        10        0         2.0     -1.4     77.8   3066  \n",
       "16         9        0         1.7     -2.0     76.1   3066  \n",
       "17         9        0         2.3     -1.4     76.1   3066  \n",
       "18         8        0         2.3     -1.4     76.1   3066  \n",
       "19         9        0         2.3     -1.5     75.7   3066  \n",
       "20         7        0         2.4     -1.3     76.3   3066  \n",
       "21        13        0         3.1     -0.9     74.7   3066  \n",
       "22         9        0         3.7     -0.5     73.7   3066  \n",
       "23        13        0         4.0      0.0     74.9   3066  \n",
       "24        13        0         4.5      0.2     73.4   3066  \n",
       "0         13        0         2.0      1.1     93.6   3068  \n",
       "1         11        0         2.9      2.4     96.4   3068  \n",
       "2         14        0         3.3      2.3     93.2   3068  \n",
       "3         15        0         4.7      2.3     84.2   3068  \n",
       "4         16        0         4.7      1.3     78.3   3068  \n",
       "5         11        0         3.1      0.7     84.0   3068  \n",
       "6         11        0         4.1      1.3     81.7   3068  \n",
       "7         14        0         3.2      0.5     82.2   3068  \n",
       "8         10        0         1.7      0.5     91.6   3068  \n",
       "9          8        0         1.0     -0.8     87.5   3068  \n",
       "10        14        0         1.5     -1.0     83.3   3068  \n",
       "11         9        0         0.7     -1.6     83.0   3068  \n",
       "12        10        0         0.4     -1.9     82.7   3068  \n",
       "13        11        0         1.1     -1.6     81.9   3068  \n",
       "14        15        0         1.8     -1.5     78.3   3068  \n",
       "15        10        0         0.0     -2.2     83.1   3068  \n",
       "16         9        0         1.0     -2.2     77.2   3068  \n",
       "17         6        0        -1.1     -3.8     78.7   3068  \n",
       "18         8        0         0.6     -2.2     79.5   3068  \n",
       "19         5        0         0.5     -1.9     82.0   3068  \n",
       "20         6        0        -0.1     -1.9     85.8   3068  \n",
       "21         3        0         1.3     -1.3     82.6   3068  \n",
       "22         8        0         2.2     -0.8     80.3   3068  \n",
       "23        10        0         2.8     -0.5     78.7   3068  \n",
       "24         8        0         3.4      0.0     78.2   3068  \n",
       "0         16        0         3.3      2.5     94.4   3075  \n",
       "1         13        0         3.2      2.3     93.8   3075  \n",
       "2         17        0         3.8      2.5     91.1   3075  \n",
       "3         13        0         4.0      2.2     87.9   3075  \n",
       "4         25       38         2.5      1.5     93.2   3075  \n",
       "5         14       29         2.5      1.4     92.5   3075  \n",
       "6         13        0         1.7      0.7     93.1   3075  \n",
       "7         13        0         2.1      1.0     92.3   3075  \n",
       "8         11        0         1.4     -0.1     89.6   3075  \n",
       "9          9        0         0.8     -0.8     88.9   3075  \n",
       "10        10        0         1.0     -0.5     89.5   3075  \n",
       "11         6        0         0.6     -1.1     88.2   3075  \n",
       "12         9        0         0.9     -0.8     88.2   3075  \n",
       "13        10        0         1.5      0.0     89.6   3075  \n",
       "14         9        0         1.8      0.4     90.2   3075  \n",
       "15        11        0         1.6      0.0     88.9   3075  \n",
       "16         7        0         1.8     -0.1     87.1   3075  \n",
       "17        10        0         1.4     -0.1     89.6   3075  \n",
       "18         8        0         2.4      0.0     84.0   3075  \n",
       "19         8        0         2.2      0.2     86.5   3075  \n",
       "20         2        0         1.9     -0.4     84.5   3075  \n",
       "21         9        0         2.8      0.9     87.1   3075  \n",
       "22        14        0         3.5      1.8     88.5   3075  \n",
       "23        16        0         4.1      2.0     86.1   3075  \n",
       "24        16        0         4.4      1.5     81.2   3075  \n",
       "0         13        0         4.0      2.5     89.9   3002  \n",
       "1         16        0         4.8      3.2     89.4   3002  \n",
       "2         19        0         4.7      3.7     93.2   3002  \n",
       "3         24       33         4.9      3.4     90.1   3002  \n",
       "4         24       43         5.3      2.2     80.2   3002  \n",
       "5         26       36         3.9      0.9     80.6   3002  \n",
       "6         16       34         4.4      2.1     84.8   3002  \n",
       "7         25       38         4.1      0.7     78.4   3002  \n",
       "8         22       34         4.1      0.8     78.9   3002  \n",
       "9         23       32         4.3     -1.3     66.7   3002  \n",
       "10        21       31         4.2     -0.5     71.2   3002  \n",
       "11        17       30         4.0     -1.6     66.5   3002  \n",
       "12        19       30         4.5     -1.0     67.1   3002  \n",
       "13        19        0         4.3     -2.2     62.2   3002  \n",
       "14        17        0         4.4     -1.2     66.7   3002  \n",
       "15        21       32         3.3      1.0     84.8   3002  \n",
       "16        13        0         3.7      0.2     77.6   3002  \n",
       "17         8        0         2.7      1.0     88.5   3002  \n",
       "18         9        0         2.7      1.2     89.8   3002  \n",
       "19         9        0         2.9      1.7     91.6   3002  \n",
       "20        11        0         3.4      2.2     91.8   3002  \n",
       "21        13        0         3.4      2.0     90.4   3002  \n",
       "22        15        0         3.8      2.7     92.4   3002  \n",
       "23        17        0         4.3      3.0     91.1   3002  \n",
       "24        17        0         4.9      3.6     91.2   3002  \n",
       "0         15        0         4.0      2.7     91.3   3005  \n",
       "1         15        0         4.6      3.6     93.2   3005  \n",
       "2         21       34         4.4      2.7     88.5   3005  \n",
       "3         16       31         5.1      1.9     79.6   3005  \n",
       "4         16        0         5.1      1.0     74.6   3005  \n",
       "5         18       29         4.4      1.1     78.9   3005  \n",
       "6         19       39         4.4      0.5     75.5   3005  \n",
       "7         19        0         3.5      0.2     78.9   3005  \n",
       "8         19       31         3.8     -0.5     73.2   3005  \n",
       "9         15       29         3.3     -0.7     74.8   3005  \n",
       "10        18       30         3.2     -0.4     77.1   3005  \n",
       "11        10        0         2.9      0.0     81.0   3005  \n",
       "12        15        0         3.8     -0.6     72.7   3005  \n",
       "13        14        0         3.4     -0.9     73.1   3005  \n",
       "14        15        0         3.6     -1.4     69.5   3005  \n",
       "15        11        0         4.4     -1.3     66.1   3005  \n",
       "16        10        0         4.0      0.2     76.0   3005  \n",
       "17        13        0         4.3      1.6     82.4   3005  \n",
       "18        13        0         3.9      2.2     88.5   3005  \n",
       "19        10        0         3.7      0.9     81.8   3005  \n",
       "20         9       29         2.9      1.9     93.0   3005  \n",
       "21        17        0         3.5      2.4     92.5   3005  \n",
       "22        14        0         4.2      3.0     91.8   3005  \n",
       "23        19        0         4.6      3.1     90.0   3005  \n",
       "24        17        0         4.9      3.0     87.4   3005  \n",
       "0         15        0         5.7      3.9     88.1   3008  \n",
       "1         19       32         5.4      4.2     92.0   3008  \n",
       "2         22       36         5.6      3.5     86.3   3008  \n",
       "3         22       36         6.0      2.2     76.5   3008  \n",
       "4         17       44         5.6      1.9     76.9   3008  \n",
       "5         24       37         5.6      0.6     70.0   3008  \n",
       "6         19       37         4.6      1.0     77.4   3008  \n",
       "7         18       43         3.6     -0.9     72.2   3008  \n",
       "8         24       38         4.4      0.3     74.3   3008  \n",
       "9         17       32         4.5      0.6     75.4   3008  \n",
       "10        25       41         4.0      1.2     81.8   3008  \n",
       "11        19       36         5.3     -1.1     63.0   3008  \n",
       "12        19       34         4.6      0.1     72.3   3008  \n",
       "13        18        0         5.5     -0.4     65.3   3008  \n",
       "14        16        0         5.8     -0.9     61.6   3008  \n",
       "15        15        0         5.6      0.3     68.4   3008  \n",
       "16        17        0         5.3      1.8     77.9   3008  \n",
       "17        15        0         4.8      1.7     80.1   3008  \n",
       "18        19        0         5.0      2.3     82.4   3008  \n",
       "19        21        0         4.7      2.8     87.4   3008  \n",
       "20        15        0         4.9      2.9     86.8   3008  \n",
       "21        17        0         5.4      3.0     84.4   3008  \n",
       "22        18        0         5.4      2.5     81.4   3008  \n",
       "23        19        0         5.6      2.6     80.8   3008  \n",
       "24        22       29         5.7      2.8     81.4   3008  \n",
       "..       ...      ...         ...      ...      ...    ...  \n",
       "0          3        0         2.5      1.7     94.5   3354  \n",
       "1          1        0         3.0      1.7     91.0   3354  \n",
       "2          2        0         3.4      1.6     87.8   3354  \n",
       "3          2        0         3.5      1.7     87.9   3354  \n",
       "4          3        0         3.9      2.0     87.3   3354  \n",
       "5          6        0         3.9      2.4     89.7   3354  \n",
       "6          3        0         4.1      2.9     91.8   3354  \n",
       "7          3        0         3.7      2.6     92.5   3354  \n",
       "8          5        0         3.6      2.6     93.0   3354  \n",
       "9          5        0         2.7      1.6     92.3   3354  \n",
       "10         6        0         2.3      0.9     90.3   3354  \n",
       "11         7        0         2.1      0.6     89.6   3354  \n",
       "12         3        0         2.6      0.7     87.1   3354  \n",
       "13         5        0         2.8      0.7     85.8   3354  \n",
       "14         1        0         2.2      0.3     87.0   3354  \n",
       "15         3        0         2.5      0.8     88.5   3354  \n",
       "16         5        0         2.4      1.0     90.4   3354  \n",
       "17         3        0         2.4      0.7     88.4   3354  \n",
       "18         5        0         2.5      1.3     91.7   3354  \n",
       "19         2        0         2.8      1.8     93.0   3354  \n",
       "20         3        0         3.0      2.3     95.0   3354  \n",
       "21         1        0         2.8      2.0     94.4   3354  \n",
       "22         3        0         2.5      1.8     95.1   3354  \n",
       "23         2        0         2.7      2.1     95.8   3354  \n",
       "24         7        0         3.0      2.1     93.7   3354  \n",
       "0          2        0        -0.2     -0.5     97.3   3382  \n",
       "1          2        0         2.4      1.9     96.4   3382  \n",
       "2          5        0         3.8      1.1     82.3   3382  \n",
       "3          6        0         4.0      0.7     78.8   3382  \n",
       "4          5        0         4.2      1.1     80.0   3382  \n",
       "5          5        0         4.1      1.4     82.3   3382  \n",
       "6          5        0         3.3      1.6     88.5   3382  \n",
       "7          3        0         2.2      1.4     94.4   3382  \n",
       "8          2        0         2.6      1.8     94.4   3382  \n",
       "9          1        0         2.7      2.0     95.1   3382  \n",
       "10         5        0         2.9      2.4     96.4   3382  \n",
       "11         3        0         3.7      2.6     92.5   3382  \n",
       "12         3        0         4.3      2.7     89.2   3382  \n",
       "13         5        0         4.6      2.6     86.8   3382  \n",
       "14         3        0         4.6      2.6     86.8   3382  \n",
       "15         5        0         4.4      2.6     87.8   3382  \n",
       "16         3        0         4.0      2.2     87.8   3382  \n",
       "17         5        0         2.6      1.3     90.9   3382  \n",
       "18         6        0         3.8      2.3     89.8   3382  \n",
       "19         2        0         1.5      0.2     90.9   3382  \n",
       "20         2        0        -0.7     -1.5     92.8   3382  \n",
       "21         2        0        -1.3     -1.8     94.6   3382  \n",
       "22         6        0        -1.6     -1.9     96.1   3382  \n",
       "23         3        0        -0.3     -0.5     98.0   3382  \n",
       "24         2        0         1.3      1.2     99.3   3382  \n",
       "0          5        0         0.5      0.0     96.2   3385  \n",
       "1          3        0         1.9      0.8     92.2   3385  \n",
       "2          5        0         4.5      0.9     77.1   3385  \n",
       "3          5        0         5.8      0.3     67.5   3385  \n",
       "4          3        0         5.8     -0.4     64.0   3385  \n",
       "5          3        0         4.9     -0.6     67.1   3385  \n",
       "6          2        0         4.0     -0.1     74.3   3385  \n",
       "7          5        0         3.1      0.6     83.5   3385  \n",
       "8          5        0         2.8      0.7     85.8   3385  \n",
       "9          5        0         2.5      0.7     87.8   3385  \n",
       "10         6        0         1.9      0.3     89.0   3385  \n",
       "11         5        0         1.8      0.5     90.9   3385  \n",
       "12         6        0         2.5      1.5     93.2   3385  \n",
       "13         7        0         3.1      2.1     93.1   3385  \n",
       "14         7        0         3.5      2.2     91.1   3385  \n",
       "15         7        0         3.6      2.2     90.4   3385  \n",
       "16         9        0         3.7      2.4     91.2   3385  \n",
       "17         8        0         4.0      2.9     92.5   3385  \n",
       "18         9        0         3.7      3.0     95.2   3385  \n",
       "19        10        0         4.3      3.3     93.0   3385  \n",
       "20         9        0         3.7      2.5     91.8   3385  \n",
       "21         5        0         1.9      1.0     93.6   3385  \n",
       "22         7        0         1.4      0.9     96.4   3385  \n",
       "23         5        0         2.2      1.9     97.9   3385  \n",
       "24         6        0         1.2      0.7     96.5   3385  \n",
       "0          3        0        -0.2     -1.0     93.4   3391  \n",
       "1          2        0         2.2      0.8     90.4   3391  \n",
       "2          3        0         3.5      1.0     83.6   3391  \n",
       "3          2        0         4.8     -0.2     69.7   3391  \n",
       "4          3        0         5.2     -0.7     65.2   3391  \n",
       "5          6        0         4.6     -0.7     68.0   3391  \n",
       "6          2        0         3.1     -0.7     75.8   3391  \n",
       "7          1        0         1.7     -0.7     83.8   3391  \n",
       "8          1        0         2.0     -0.2     85.1   3391  \n",
       "9          3        0         2.1      0.1     86.4   3391  \n",
       "10         2        0         2.7      0.7     86.4   3391  \n",
       "11         3        0         2.5      0.9     89.2   3391  \n",
       "12         2        0         2.6      1.2     90.2   3391  \n",
       "13         3        0         2.5      1.3     91.7   3391  \n",
       "14         5        0         3.2      1.8     90.2   3391  \n",
       "15         3        0         3.2      1.9     90.9   3391  \n",
       "16         3        0         3.2      2.0     91.8   3391  \n",
       "17         5        0         3.3      2.0     91.1   3391  \n",
       "18         7        0         3.3      2.0     91.1   3391  \n",
       "19         6        0         3.3      2.1     91.7   3391  \n",
       "20         6        0         3.1      2.3     94.4   3391  \n",
       "21         3        0         2.7      1.9     94.3   3391  \n",
       "22         6        0         0.6      0.2     97.0   3391  \n",
       "23         7        0        -0.6     -1.2     94.5   3391  \n",
       "24         2        0         2.5      2.3     98.6   3391  \n",
       "0          0        0         1.9      1.3     95.7  99142  \n",
       "1          0        0         2.3      1.5     94.3  99142  \n",
       "2          0        0         2.6      1.7     93.8  99142  \n",
       "3          0        0         2.9      1.9     93.1  99142  \n",
       "4          0        0         3.0      1.6     90.5  99142  \n",
       "5          0        0         2.9      1.6     91.1  99142  \n",
       "6          0        0         2.0      1.5     96.5  99142  \n",
       "7          0        0         2.4      1.7     95.0  99142  \n",
       "8          0        0         3.3      1.5     88.0  99142  \n",
       "9          0        0         3.7      1.9     87.9  99142  \n",
       "10         0        0         4.0      2.0     86.8  99142  \n",
       "11         0        0         4.1      2.2     87.4  99142  \n",
       "12         0        0         3.8      2.8     93.3  99142  \n",
       "13         0        0         4.0      2.6     90.7  99142  \n",
       "14         0        0         3.6      2.4     91.9  99142  \n",
       "15         0        0         3.6      2.1     89.9  99142  \n",
       "16         0        0         3.3      2.6     95.2  99142  \n",
       "17         0        0         2.7      1.9     94.5  99142  \n",
       "18         0        0         2.0      1.0     93.1  99142  \n",
       "19         0        0         0.9     -0.3     91.7  99142  \n",
       "20         0        0         1.1      0.0     92.3  99142  \n",
       "21         0        0         1.4     -0.2     89.1  99142  \n",
       "22         0        0         1.2     -0.3     89.8  99142  \n",
       "23         0        0         1.3     -0.3     89.1  99142  \n",
       "24         0        0         1.5      0.3     91.8  99142  \n",
       "0          2        0         5.2      4.2     93.2   3844  \n",
       "1          3        0         5.6      4.2     90.5   3844  \n",
       "2          5        0         6.0      4.1     87.5   3844  \n",
       "3          5        0         6.5      4.2     85.0   3844  \n",
       "4          3        0         6.7      4.6     86.3   3844  \n",
       "5          3        0         6.9      4.7     85.7   3844  \n",
       "6          3        0         5.9      4.2     88.7   3844  \n",
       "7          5        0         6.1      4.2     87.5   3844  \n",
       "8          5        0         5.8      4.1     88.7   3844  \n",
       "9          5        0         5.7      4.0     88.6   3844  \n",
       "10         1        0         5.4      3.8     89.3   3844  \n",
       "11         0        0         5.0      3.7     91.2   3844  \n",
       "12         2        0         5.1      3.8     91.1   3844  \n",
       "13         2        0         4.5      3.8     95.0   3844  \n",
       "14         2        0         2.8      2.5     97.9   3844  \n",
       "15         2        0         3.2      2.9     97.8   3844  \n",
       "16         0        0         3.8      3.6     98.5   3844  \n",
       "17         2        0         3.7      3.4     98.0   3844  \n",
       "18         1        0         3.7      3.5     98.6   3844  \n",
       "19         1        0         2.9      2.5     97.1   3844  \n",
       "20         3        0         1.3      1.0     97.9   3844  \n",
       "21         1        0         0.8      0.7     99.4   3844  \n",
       "22         2        0         0.9      0.8     99.2   3844  \n",
       "23         1        0         0.3      0.3    100.0   3844  \n",
       "24         2        0         1.1      1.1    100.0   3844  \n",
       "\n",
       "[3499 rows x 11 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check you data, see if it makes sense\n",
    "weather_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did you notice that the row index is not with unique numbers? Why? This is a common issue when combining DataFrame together and may cause problems when we index data. We just need to reset the index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>WindDirection</th>\n",
       "      <th>PressureTendency</th>\n",
       "      <th>WeatherType</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>WindGust</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>6000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>93.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>35000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>86.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>14</td>\n",
       "      <td>9000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>35000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>85.2</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>45000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>27000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.2</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>27000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>84.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>77.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>77.9</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>76.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>81.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>77.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>77.8</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>76.1</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>75.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>76.3</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>45000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>74.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>50000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>73.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>74.9</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>73.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>30000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>93.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>84.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>78.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>84.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>81.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>82.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.5</td>\n",
       "      <td>91.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>83.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>82.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>81.9</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>78.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>83.1</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>77.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>40000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-3.8</td>\n",
       "      <td>78.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>79.5</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>50000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>50000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>82.6</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>80.3</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>78.7</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>78.2</td>\n",
       "      <td>3068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>16000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>93.8</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>27000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>6000</td>\n",
       "      <td>25</td>\n",
       "      <td>38</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>35000</td>\n",
       "      <td>14</td>\n",
       "      <td>29</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>28000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>93.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>21000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>92.3</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>88.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>35000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>89.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>88.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>35000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>88.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.4</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.9</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>50000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>86.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>84.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>26000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.1</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>81.2</td>\n",
       "      <td>3075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>89.9</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>35000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.2</td>\n",
       "      <td>89.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>8000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.7</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>28000</td>\n",
       "      <td>24</td>\n",
       "      <td>33</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.4</td>\n",
       "      <td>90.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>24</td>\n",
       "      <td>43</td>\n",
       "      <td>5.3</td>\n",
       "      <td>2.2</td>\n",
       "      <td>80.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>26</td>\n",
       "      <td>36</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.9</td>\n",
       "      <td>80.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>84.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>24000</td>\n",
       "      <td>25</td>\n",
       "      <td>38</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>78.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>14000</td>\n",
       "      <td>22</td>\n",
       "      <td>34</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>23</td>\n",
       "      <td>32</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>66.7</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>22000</td>\n",
       "      <td>21</td>\n",
       "      <td>31</td>\n",
       "      <td>4.2</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>71.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>24000</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>66.5</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>30</td>\n",
       "      <td>4.5</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>67.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>45000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>25000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>66.7</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>7000</td>\n",
       "      <td>21</td>\n",
       "      <td>32</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>84.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>27000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>77.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>25000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>25000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.2</td>\n",
       "      <td>89.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>19000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>91.6</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>21000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>28000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>92.4</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>45000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>10</td>\n",
       "      <td>16000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.6</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>17000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>91.3</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>9000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.6</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>16000</td>\n",
       "      <td>21</td>\n",
       "      <td>34</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>24000</td>\n",
       "      <td>16</td>\n",
       "      <td>31</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>79.6</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74.6</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>30000</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.1</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>75.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>78.9</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>19</td>\n",
       "      <td>31</td>\n",
       "      <td>3.8</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>73.2</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>29</td>\n",
       "      <td>3.3</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>74.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>35000</td>\n",
       "      <td>18</td>\n",
       "      <td>30</td>\n",
       "      <td>3.2</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>77.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>25000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>72.7</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>73.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>69.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>66.1</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>76.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>29000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>82.4</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.9</td>\n",
       "      <td>81.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>40000</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.9</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>19000</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>23000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>87.4</td>\n",
       "      <td>3005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>40000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>88.1</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>7000</td>\n",
       "      <td>19</td>\n",
       "      <td>32</td>\n",
       "      <td>5.4</td>\n",
       "      <td>4.2</td>\n",
       "      <td>92.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>11</td>\n",
       "      <td>9000</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>5.6</td>\n",
       "      <td>3.5</td>\n",
       "      <td>86.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>76.5</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>17</td>\n",
       "      <td>44</td>\n",
       "      <td>5.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>76.9</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>30000</td>\n",
       "      <td>24</td>\n",
       "      <td>37</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>70.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>7000</td>\n",
       "      <td>19</td>\n",
       "      <td>37</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>77.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>18</td>\n",
       "      <td>43</td>\n",
       "      <td>3.6</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>72.2</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>26000</td>\n",
       "      <td>24</td>\n",
       "      <td>38</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>74.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>28000</td>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>75.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>13</td>\n",
       "      <td>14000</td>\n",
       "      <td>25</td>\n",
       "      <td>41</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>81.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>36</td>\n",
       "      <td>5.3</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>63.0</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>9</td>\n",
       "      <td>17000</td>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "      <td>4.6</td>\n",
       "      <td>0.1</td>\n",
       "      <td>72.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>35000</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>65.3</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>30000</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>61.6</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>29000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>68.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>18000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>1.8</td>\n",
       "      <td>77.9</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>28000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.7</td>\n",
       "      <td>80.1</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>23000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>82.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>22000</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>87.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>30000</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>13000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>84.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>16000</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.5</td>\n",
       "      <td>81.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>26000</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>80.8</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>22000</td>\n",
       "      <td>22</td>\n",
       "      <td>29</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>81.4</td>\n",
       "      <td>3008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3349</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>4900</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3350</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>7000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>91.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3351</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>11</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3352</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>87.9</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3353</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>87.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3354</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4100</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>89.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3355</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>3300</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.9</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3356</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3200</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3357</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4100</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3358</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>92.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3359</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>10000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.9</td>\n",
       "      <td>90.3</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3360</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>8000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>89.6</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3361</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>11000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>87.1</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3362</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>13000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3363</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>NE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>11000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>87.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3364</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3365</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3366</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>9000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>88.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3367</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3368</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>9</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3369</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>95.0</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3370</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3300</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3371</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>3600</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>95.1</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3372</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>3400</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>95.8</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3373</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3900</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>93.7</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3374</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3500</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>97.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3375</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>6000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.9</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3376</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.1</td>\n",
       "      <td>82.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3377</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>78.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>1.1</td>\n",
       "      <td>80.0</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3379</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>82.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3380</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>88.5</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3381</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3900</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.4</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3382</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3383</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>2800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>95.1</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>5</td>\n",
       "      <td>3000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3385</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3386</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>89.2</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3387</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3388</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>86.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3389</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.6</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3390</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>15000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3391</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.3</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3392</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>S</td>\n",
       "      <td>9</td>\n",
       "      <td>13000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>89.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3393</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3394</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>3500</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>92.8</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3395</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>4100</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>94.6</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3396</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>8000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>-1.9</td>\n",
       "      <td>96.1</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3397</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>6</td>\n",
       "      <td>500</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>98.0</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3398</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2900</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>99.3</td>\n",
       "      <td>3382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3399</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3400</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>8000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>92.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3401</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>14000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>77.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3402</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>21000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>0.3</td>\n",
       "      <td>67.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3403</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>S</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>22000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>64.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3404</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>20000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>67.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3405</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>16000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>74.3</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3406</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>83.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>85.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>87.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3411</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3412</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>6000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>93.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3413</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3414</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3415</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.4</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3416</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>92.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3417</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>S</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>95.2</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3418</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>20000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.3</td>\n",
       "      <td>93.0</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3419</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>21000</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>2.5</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3420</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>17000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>93.6</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3421</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>9000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.9</td>\n",
       "      <td>96.4</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3422</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>21000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3423</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>9000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>96.5</td>\n",
       "      <td>3385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3424</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>93.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3425</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>8000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3426</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>83.6</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3427</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>15000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>69.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3428</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>65.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3429</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>68.0</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3430</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>15000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>75.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3431</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>83.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3432</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>85.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3433</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>86.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3434</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>86.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3435</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>8000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.9</td>\n",
       "      <td>89.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3436</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>7000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.2</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3437</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3438</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>90.2</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3439</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>90.9</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3440</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.8</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3441</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3442</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3443</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NW</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.1</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3444</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>F</td>\n",
       "      <td>12</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>94.4</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3445</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>94.3</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3446</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2000</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3447</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>2200</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3448</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>F</td>\n",
       "      <td>5</td>\n",
       "      <td>4000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>98.6</td>\n",
       "      <td>3391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3449</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>95.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3450</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>94.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3451</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>93.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3452</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.9</td>\n",
       "      <td>93.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3453</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>90.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3454</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.6</td>\n",
       "      <td>91.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3455</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>96.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3456</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>95.0</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3457</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>88.0</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3458</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>87.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3459</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>86.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3460</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>87.4</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3461</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>2.8</td>\n",
       "      <td>93.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3462</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>90.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3463</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>91.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3464</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>89.9</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3465</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>2.6</td>\n",
       "      <td>95.2</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3466</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>94.5</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3467</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>93.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3468</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>91.7</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3469</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.3</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3470</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>89.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3471</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>89.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3472</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>89.1</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3473</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>91.8</td>\n",
       "      <td>99142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3474</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>9000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>93.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3475</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>90.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3476</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>11000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3477</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>14000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>85.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3478</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>13000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>4.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3479</th>\n",
       "      <td>2019-01-20 15:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>15000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4.7</td>\n",
       "      <td>85.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3480</th>\n",
       "      <td>2019-01-20 16:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>3</td>\n",
       "      <td>12000</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>4.2</td>\n",
       "      <td>88.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3481</th>\n",
       "      <td>2019-01-20 17:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>12000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>4.2</td>\n",
       "      <td>87.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3482</th>\n",
       "      <td>2019-01-20 18:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>4.1</td>\n",
       "      <td>88.7</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3483</th>\n",
       "      <td>2019-01-20 19:00:00</td>\n",
       "      <td>NNW</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>10000</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>88.6</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3484</th>\n",
       "      <td>2019-01-20 20:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.8</td>\n",
       "      <td>89.3</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3485</th>\n",
       "      <td>2019-01-20 21:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>91.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3486</th>\n",
       "      <td>2019-01-20 22:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>8000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>91.1</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3487</th>\n",
       "      <td>2019-01-20 23:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>R</td>\n",
       "      <td>2</td>\n",
       "      <td>7000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.8</td>\n",
       "      <td>95.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3488</th>\n",
       "      <td>2019-01-21 00:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3900</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3489</th>\n",
       "      <td>2019-01-21 01:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>7</td>\n",
       "      <td>3800</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>97.8</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3490</th>\n",
       "      <td>2019-01-21 02:00:00</td>\n",
       "      <td>N</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>4300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>98.5</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3491</th>\n",
       "      <td>2019-01-21 03:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>2800</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3492</th>\n",
       "      <td>2019-01-21 04:00:00</td>\n",
       "      <td>ESE</td>\n",
       "      <td>F</td>\n",
       "      <td>8</td>\n",
       "      <td>3800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>98.6</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3493</th>\n",
       "      <td>2019-01-21 05:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>F</td>\n",
       "      <td>7</td>\n",
       "      <td>2800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>97.1</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3494</th>\n",
       "      <td>2019-01-21 06:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>97.9</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3495</th>\n",
       "      <td>2019-01-21 07:00:00</td>\n",
       "      <td>E</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>99.4</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3496</th>\n",
       "      <td>2019-01-21 08:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>99.2</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3497</th>\n",
       "      <td>2019-01-21 09:00:00</td>\n",
       "      <td>NNE</td>\n",
       "      <td>R</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3498</th>\n",
       "      <td>2019-01-21 10:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>200</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>1.1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>3844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3499 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 DateTime WindDirection PressureTendency WeatherType  \\\n",
       "0     2019-01-20 10:00:00           WSW                R          12   \n",
       "1     2019-01-20 11:00:00            SW                R           8   \n",
       "2     2019-01-20 12:00:00           WSW                R          10   \n",
       "3     2019-01-20 13:00:00             W                R           8   \n",
       "4     2019-01-20 14:00:00             W                R          14   \n",
       "5     2019-01-20 15:00:00             W                R           1   \n",
       "6     2019-01-20 16:00:00           WSW                R           2   \n",
       "7     2019-01-20 17:00:00             W                R           7   \n",
       "8     2019-01-20 18:00:00           WSW                R           0   \n",
       "9     2019-01-20 19:00:00            SW                R           0   \n",
       "10    2019-01-20 20:00:00           WSW                R           0   \n",
       "11    2019-01-20 21:00:00           WSW                R           0   \n",
       "12    2019-01-20 22:00:00            SW                R           0   \n",
       "13    2019-01-20 23:00:00           SSW                R           0   \n",
       "14    2019-01-21 00:00:00           SSW                R           0   \n",
       "15    2019-01-21 01:00:00           SSW                F           0   \n",
       "16    2019-01-21 02:00:00           SSW                F           0   \n",
       "17    2019-01-21 03:00:00           SSW                F           0   \n",
       "18    2019-01-21 04:00:00             S                F           0   \n",
       "19    2019-01-21 05:00:00             S                F           2   \n",
       "20    2019-01-21 06:00:00             S                F           2   \n",
       "21    2019-01-21 07:00:00           SSW                F           7   \n",
       "22    2019-01-21 08:00:00             S                F           8   \n",
       "23    2019-01-21 09:00:00           SSW                F           8   \n",
       "24    2019-01-21 10:00:00           SSW                F           8   \n",
       "25    2019-01-20 10:00:00           WSW                R          12   \n",
       "26    2019-01-20 11:00:00           WSW                R           7   \n",
       "27    2019-01-20 12:00:00           WSW                R           7   \n",
       "28    2019-01-20 13:00:00             W                R           7   \n",
       "29    2019-01-20 14:00:00             W                R           7   \n",
       "30    2019-01-20 15:00:00             W                R           3   \n",
       "31    2019-01-20 16:00:00             W                R           9   \n",
       "32    2019-01-20 17:00:00             W                R           2   \n",
       "33    2019-01-20 18:00:00           WSW                R           2   \n",
       "34    2019-01-20 19:00:00            SW                R           2   \n",
       "35    2019-01-20 20:00:00             W                R           2   \n",
       "36    2019-01-20 21:00:00            SW                R           0   \n",
       "37    2019-01-20 22:00:00            SW                R           0   \n",
       "38    2019-01-20 23:00:00           WSW                R           0   \n",
       "39    2019-01-21 00:00:00           WSW                R           0   \n",
       "40    2019-01-21 01:00:00           WSW                F           0   \n",
       "41    2019-01-21 02:00:00            SW                F           0   \n",
       "42    2019-01-21 03:00:00           SSW                F           0   \n",
       "43    2019-01-21 04:00:00            SW                F           2   \n",
       "44    2019-01-21 05:00:00             S                F           2   \n",
       "45    2019-01-21 06:00:00             S                F           7   \n",
       "46    2019-01-21 07:00:00             S                F           7   \n",
       "47    2019-01-21 08:00:00             S                F           7   \n",
       "48    2019-01-21 09:00:00             S                F           7   \n",
       "49    2019-01-21 10:00:00             S                F           7   \n",
       "50    2019-01-20 10:00:00             W                R          12   \n",
       "51    2019-01-20 11:00:00             W                R           8   \n",
       "52    2019-01-20 12:00:00             W                R           8   \n",
       "53    2019-01-20 13:00:00           WNW                R           3   \n",
       "54    2019-01-20 14:00:00             W                R          10   \n",
       "55    2019-01-20 15:00:00             W                R           1   \n",
       "56    2019-01-20 16:00:00             W                R           2   \n",
       "57    2019-01-20 17:00:00             W                R           7   \n",
       "58    2019-01-20 18:00:00           WSW                R           0   \n",
       "59    2019-01-20 19:00:00             W                R           2   \n",
       "60    2019-01-20 20:00:00             W                R           2   \n",
       "61    2019-01-20 21:00:00           WSW                R           0   \n",
       "62    2019-01-20 22:00:00           WSW                R           0   \n",
       "63    2019-01-20 23:00:00           WSW                R           7   \n",
       "64    2019-01-21 00:00:00           WSW                R           7   \n",
       "65    2019-01-21 01:00:00           WSW                F           0   \n",
       "66    2019-01-21 02:00:00           SSW                F           7   \n",
       "67    2019-01-21 03:00:00            SW                F           2   \n",
       "68    2019-01-21 04:00:00             S                F           2   \n",
       "69    2019-01-21 05:00:00             S                F           2   \n",
       "70    2019-01-21 06:00:00           SSW                F           7   \n",
       "71    2019-01-21 07:00:00             S                F           7   \n",
       "72    2019-01-21 08:00:00             S                F           8   \n",
       "73    2019-01-21 09:00:00             S                F           8   \n",
       "74    2019-01-21 10:00:00             S                F           8   \n",
       "75    2019-01-20 10:00:00           SSW                F           7   \n",
       "76    2019-01-20 11:00:00           SSW                F           7   \n",
       "77    2019-01-20 12:00:00           SSW                F          10   \n",
       "78    2019-01-20 13:00:00           WNW                F          12   \n",
       "79    2019-01-20 14:00:00           WNW                R           7   \n",
       "80    2019-01-20 15:00:00           WNW                R           7   \n",
       "81    2019-01-20 16:00:00            NW                R           7   \n",
       "82    2019-01-20 17:00:00           WNW                R           8   \n",
       "83    2019-01-20 18:00:00            NW                R           9   \n",
       "84    2019-01-20 19:00:00           WNW                R           2   \n",
       "85    2019-01-20 20:00:00           WNW                R           2   \n",
       "86    2019-01-20 21:00:00           WNW                R           2   \n",
       "87    2019-01-20 22:00:00           WNW                R           2   \n",
       "88    2019-01-20 23:00:00           WNW                R           0   \n",
       "89    2019-01-21 00:00:00           WNW                R           2   \n",
       "90    2019-01-21 01:00:00             W                R           9   \n",
       "91    2019-01-21 02:00:00             W                R           7   \n",
       "92    2019-01-21 03:00:00           WSW                F           8   \n",
       "93    2019-01-21 04:00:00           SSW                F           8   \n",
       "94    2019-01-21 05:00:00           SSW                F           8   \n",
       "95    2019-01-21 06:00:00           SSW                F           7   \n",
       "96    2019-01-21 07:00:00           SSW                F           0   \n",
       "97    2019-01-21 08:00:00           SSW                F           2   \n",
       "98    2019-01-21 09:00:00           SSW                F           7   \n",
       "99    2019-01-21 10:00:00             S                F          10   \n",
       "100   2019-01-20 10:00:00           SSW                F           7   \n",
       "101   2019-01-20 11:00:00           SSW                F          12   \n",
       "102   2019-01-20 12:00:00           WNW                F          12   \n",
       "103   2019-01-20 13:00:00           WNW                R           7   \n",
       "104   2019-01-20 14:00:00           WNW                R           7   \n",
       "105   2019-01-20 15:00:00           WNW                R          10   \n",
       "106   2019-01-20 16:00:00           WNW                R           7   \n",
       "107   2019-01-20 17:00:00           WNW                R           7   \n",
       "108   2019-01-20 18:00:00           WNW                R           7   \n",
       "109   2019-01-20 19:00:00           WNW                R           2   \n",
       "110   2019-01-20 20:00:00           WNW                R           0   \n",
       "111   2019-01-20 21:00:00           WNW                R           0   \n",
       "112   2019-01-20 22:00:00             W                R           7   \n",
       "113   2019-01-20 23:00:00           WNW                R           2   \n",
       "114   2019-01-21 00:00:00           WNW                R           2   \n",
       "115   2019-01-21 01:00:00             W                R           7   \n",
       "116   2019-01-21 02:00:00             W                F           7   \n",
       "117   2019-01-21 03:00:00           WSW                F           7   \n",
       "118   2019-01-21 04:00:00            SW                F           7   \n",
       "119   2019-01-21 05:00:00           WSW                F           2   \n",
       "120   2019-01-21 06:00:00           SSW                F           9   \n",
       "121   2019-01-21 07:00:00            SW                F           8   \n",
       "122   2019-01-21 08:00:00           SSW                F           9   \n",
       "123   2019-01-21 09:00:00            SW                F           8   \n",
       "124   2019-01-21 10:00:00           SSW                F           8   \n",
       "125   2019-01-20 10:00:00           SSW                R           7   \n",
       "126   2019-01-20 11:00:00           WSW                R          12   \n",
       "127   2019-01-20 12:00:00           WNW                R          11   \n",
       "128   2019-01-20 13:00:00           WNW                R           7   \n",
       "129   2019-01-20 14:00:00           WNW                R           3   \n",
       "130   2019-01-20 15:00:00           WNW                R           3   \n",
       "131   2019-01-20 16:00:00            NW                R           9   \n",
       "132   2019-01-20 17:00:00            NW                R           2   \n",
       "133   2019-01-20 18:00:00             W                R           7   \n",
       "134   2019-01-20 19:00:00           WNW                R           0   \n",
       "135   2019-01-20 20:00:00           WNW                R          13   \n",
       "136   2019-01-20 21:00:00           WNW                R           2   \n",
       "137   2019-01-20 22:00:00           WNW                R           9   \n",
       "138   2019-01-20 23:00:00           WNW                R           2   \n",
       "139   2019-01-21 00:00:00             W                R           0   \n",
       "140   2019-01-21 01:00:00             W                R           2   \n",
       "141   2019-01-21 02:00:00             W                F           7   \n",
       "142   2019-01-21 03:00:00           WSW                F           7   \n",
       "143   2019-01-21 04:00:00            SW                F           7   \n",
       "144   2019-01-21 05:00:00            SW                F           2   \n",
       "145   2019-01-21 06:00:00            SW                F           7   \n",
       "146   2019-01-21 07:00:00            SW                F           7   \n",
       "147   2019-01-21 08:00:00            SW                F           2   \n",
       "148   2019-01-21 09:00:00           SSW                F           8   \n",
       "149   2019-01-21 10:00:00           SSW                F           3   \n",
       "...                   ...           ...              ...         ...   \n",
       "3349  2019-01-20 10:00:00             E                R           5   \n",
       "3350  2019-01-20 11:00:00             S                R           8   \n",
       "3351  2019-01-20 12:00:00            SW                R          11   \n",
       "3352  2019-01-20 13:00:00            SW                R           8   \n",
       "3353  2019-01-20 14:00:00           WSW                R           8   \n",
       "3354  2019-01-20 15:00:00             W                R           8   \n",
       "3355  2019-01-20 16:00:00           WSW                R           8   \n",
       "3356  2019-01-20 17:00:00             W                R           7   \n",
       "3357  2019-01-20 18:00:00            NW                R           8   \n",
       "3358  2019-01-20 19:00:00           WNW                R           0   \n",
       "3359  2019-01-20 20:00:00           WNW                R           0   \n",
       "3360  2019-01-20 21:00:00           WNW                R           2   \n",
       "3361  2019-01-20 22:00:00           NNW                R           7   \n",
       "3362  2019-01-20 23:00:00            NW                R           8   \n",
       "3363  2019-01-21 00:00:00            NE                R           8   \n",
       "3364  2019-01-21 01:00:00           WNW                R           8   \n",
       "3365  2019-01-21 02:00:00            NW                R           8   \n",
       "3366  2019-01-21 03:00:00           WNW                R           7   \n",
       "3367  2019-01-21 04:00:00            NW                F           8   \n",
       "3368  2019-01-21 05:00:00           NNW                F           9   \n",
       "3369  2019-01-21 06:00:00             W                F           8   \n",
       "3370  2019-01-21 07:00:00           WSW                F           5   \n",
       "3371  2019-01-21 08:00:00           WSW                F          12   \n",
       "3372  2019-01-21 09:00:00           WSW                F           8   \n",
       "3373  2019-01-21 10:00:00            SW                F           5   \n",
       "3374  2019-01-20 10:00:00             S                R           5   \n",
       "3375  2019-01-20 11:00:00            SW                R           5   \n",
       "3376  2019-01-20 12:00:00             S                R           8   \n",
       "3377  2019-01-20 13:00:00           SSW                R           8   \n",
       "3378  2019-01-20 14:00:00           WSW                R           8   \n",
       "3379  2019-01-20 15:00:00           WSW                R           8   \n",
       "3380  2019-01-20 16:00:00           WSW                R           7   \n",
       "3381  2019-01-20 17:00:00             W                R           7   \n",
       "3382  2019-01-20 18:00:00             W                R           5   \n",
       "3383  2019-01-20 19:00:00            SW                R           5   \n",
       "3384  2019-01-20 20:00:00           WNW                R           5   \n",
       "3385  2019-01-20 21:00:00             W                R           7   \n",
       "3386  2019-01-20 22:00:00            NW                R           8   \n",
       "3387  2019-01-20 23:00:00           WNW                R           7   \n",
       "3388  2019-01-21 00:00:00           WNW                R           7   \n",
       "3389  2019-01-21 01:00:00            NW                R           8   \n",
       "3390  2019-01-21 02:00:00            NW                R           8   \n",
       "3391  2019-01-21 03:00:00            NW                R           2   \n",
       "3392  2019-01-21 04:00:00           NNW                S           9   \n",
       "3393  2019-01-21 05:00:00             W                F           2   \n",
       "3394  2019-01-21 06:00:00           WSW                F           5   \n",
       "3395  2019-01-21 07:00:00           WSW                F           5   \n",
       "3396  2019-01-21 08:00:00             W                F           5   \n",
       "3397  2019-01-21 09:00:00             W                F           6   \n",
       "3398  2019-01-21 10:00:00             S                F           7   \n",
       "3399  2019-01-20 10:00:00           WSW                R           1   \n",
       "3400  2019-01-20 11:00:00           WSW                R           1   \n",
       "3401  2019-01-20 12:00:00           SSW                R           1   \n",
       "3402  2019-01-20 13:00:00             S                R           1   \n",
       "3403  2019-01-20 14:00:00             S                R           1   \n",
       "3404  2019-01-20 15:00:00            SW                R           7   \n",
       "3405  2019-01-20 16:00:00            SW                R           7   \n",
       "3406  2019-01-20 17:00:00            SW                R           8   \n",
       "3407  2019-01-20 18:00:00            SW                R           8   \n",
       "3408  2019-01-20 19:00:00            SW                R           8   \n",
       "3409  2019-01-20 20:00:00           SSW                R           8   \n",
       "3410  2019-01-20 21:00:00           WSW                R           7   \n",
       "3411  2019-01-20 22:00:00             W                R           8   \n",
       "3412  2019-01-20 23:00:00             W                R           8   \n",
       "3413  2019-01-21 00:00:00             W                R           8   \n",
       "3414  2019-01-21 01:00:00             W                R           8   \n",
       "3415  2019-01-21 02:00:00           WNW                R           8   \n",
       "3416  2019-01-21 03:00:00           WNW                R           8   \n",
       "3417  2019-01-21 04:00:00           WNW                S           8   \n",
       "3418  2019-01-21 05:00:00           NNW                F           8   \n",
       "3419  2019-01-21 06:00:00            NW                F           7   \n",
       "3420  2019-01-21 07:00:00           WSW                F           0   \n",
       "3421  2019-01-21 08:00:00           WSW                F           1   \n",
       "3422  2019-01-21 09:00:00           WSW                F           1   \n",
       "3423  2019-01-21 10:00:00            SW                F           1   \n",
       "3424  2019-01-20 10:00:00           NNW                R           3   \n",
       "3425  2019-01-20 11:00:00           WNW                R           3   \n",
       "3426  2019-01-20 12:00:00             W                R           1   \n",
       "3427  2019-01-20 13:00:00            SW                R           1   \n",
       "3428  2019-01-20 14:00:00           SSW                R           1   \n",
       "3429  2019-01-20 15:00:00             W                R           1   \n",
       "3430  2019-01-20 16:00:00             W                R           3   \n",
       "3431  2019-01-20 17:00:00            SW                R           7   \n",
       "3432  2019-01-20 18:00:00           SSW                R           7   \n",
       "3433  2019-01-20 19:00:00            SW                R           7   \n",
       "3434  2019-01-20 20:00:00           WSW                R           7   \n",
       "3435  2019-01-20 21:00:00             W                R           7   \n",
       "3436  2019-01-20 22:00:00           WSW                R           7   \n",
       "3437  2019-01-20 23:00:00             W                R           7   \n",
       "3438  2019-01-21 00:00:00            NW                R           7   \n",
       "3439  2019-01-21 01:00:00            NW                R           7   \n",
       "3440  2019-01-21 02:00:00           WNW                R           7   \n",
       "3441  2019-01-21 03:00:00            NW                R           7   \n",
       "3442  2019-01-21 04:00:00            NW                F           7   \n",
       "3443  2019-01-21 05:00:00            NW                F           7   \n",
       "3444  2019-01-21 06:00:00           NNW                F          12   \n",
       "3445  2019-01-21 07:00:00             N                F           2   \n",
       "3446  2019-01-21 08:00:00             W                F           7   \n",
       "3447  2019-01-21 09:00:00             W                F           5   \n",
       "3448  2019-01-21 10:00:00             W                F           5   \n",
       "3449  2019-01-20 10:00:00                                          0   \n",
       "3450  2019-01-20 11:00:00                                          0   \n",
       "3451  2019-01-20 12:00:00                                          0   \n",
       "3452  2019-01-20 13:00:00                                          0   \n",
       "3453  2019-01-20 14:00:00                                          0   \n",
       "3454  2019-01-20 15:00:00                                          0   \n",
       "3455  2019-01-20 16:00:00                                          0   \n",
       "3456  2019-01-20 17:00:00                                          0   \n",
       "3457  2019-01-20 18:00:00                                          0   \n",
       "3458  2019-01-20 19:00:00                                          0   \n",
       "3459  2019-01-20 20:00:00                                          0   \n",
       "3460  2019-01-20 21:00:00                                          0   \n",
       "3461  2019-01-20 22:00:00                                          0   \n",
       "3462  2019-01-20 23:00:00                                          0   \n",
       "3463  2019-01-21 00:00:00                                          0   \n",
       "3464  2019-01-21 01:00:00                                          0   \n",
       "3465  2019-01-21 02:00:00                                          0   \n",
       "3466  2019-01-21 03:00:00                                          0   \n",
       "3467  2019-01-21 04:00:00                                          0   \n",
       "3468  2019-01-21 05:00:00                                          0   \n",
       "3469  2019-01-21 06:00:00                                          0   \n",
       "3470  2019-01-21 07:00:00                                          0   \n",
       "3471  2019-01-21 08:00:00                                          0   \n",
       "3472  2019-01-21 09:00:00                                          0   \n",
       "3473  2019-01-21 10:00:00                                          0   \n",
       "3474  2019-01-20 10:00:00           ENE                R           8   \n",
       "3475  2019-01-20 11:00:00           NNE                R           8   \n",
       "3476  2019-01-20 12:00:00           NNE                R           8   \n",
       "3477  2019-01-20 13:00:00             N                R           8   \n",
       "3478  2019-01-20 14:00:00           NNE                R           8   \n",
       "3479  2019-01-20 15:00:00           NNW                R           8   \n",
       "3480  2019-01-20 16:00:00           NNE                R           3   \n",
       "3481  2019-01-20 17:00:00           NNE                R           7   \n",
       "3482  2019-01-20 18:00:00           NNE                R           8   \n",
       "3483  2019-01-20 19:00:00           NNW                R           7   \n",
       "3484  2019-01-20 20:00:00           NNE                R           8   \n",
       "3485  2019-01-20 21:00:00             N                R           8   \n",
       "3486  2019-01-20 22:00:00             N                R           8   \n",
       "3487  2019-01-20 23:00:00           WNW                R           2   \n",
       "3488  2019-01-21 00:00:00             E                R           7   \n",
       "3489  2019-01-21 01:00:00             E                R           7   \n",
       "3490  2019-01-21 02:00:00             N                R           8   \n",
       "3491  2019-01-21 03:00:00             E                R           8   \n",
       "3492  2019-01-21 04:00:00           ESE                F           8   \n",
       "3493  2019-01-21 05:00:00           NNE                F           7   \n",
       "3494  2019-01-21 06:00:00           WNW                F           0   \n",
       "3495  2019-01-21 07:00:00             E                F           0   \n",
       "3496  2019-01-21 08:00:00           ENE                R           0   \n",
       "3497  2019-01-21 09:00:00           NNE                R           0   \n",
       "3498  2019-01-21 10:00:00           ENE                F           0   \n",
       "\n",
       "     Visibility WindSpeed WindGust Temperature DewPoint Humidity     id  \n",
       "0          6000        10        0         2.1      1.2     93.7   3066  \n",
       "1         45000        10        0         2.8      2.0     94.5   3066  \n",
       "2         40000        11        0         3.6      2.2     90.4   3066  \n",
       "3         35000        13        0         4.2      2.2     86.7   3066  \n",
       "4          9000        17        0         3.9      2.2     88.5   3066  \n",
       "5         35000        15        0         3.6      1.4     85.2   3066  \n",
       "6         45000         8        0         2.4      0.5     87.1   3066  \n",
       "7         28000        13        0         2.3      0.7     89.0   3066  \n",
       "8         27000        14        0         2.2      0.0     85.2   3066  \n",
       "9         27000         6        0         0.9     -1.4     84.4   3066  \n",
       "10        30000        11        0         2.3     -1.2     77.3   3066  \n",
       "11        40000        11        0         2.1     -1.3     77.9   3066  \n",
       "12        40000        10        0         1.8     -1.8     76.7   3066  \n",
       "13        45000         9        0         0.8     -1.8     81.1   3066  \n",
       "14        40000         8        0         1.7     -1.8     77.3   3066  \n",
       "15        40000        10        0         2.0     -1.4     77.8   3066  \n",
       "16        40000         9        0         1.7     -2.0     76.1   3066  \n",
       "17        45000         9        0         2.3     -1.4     76.1   3066  \n",
       "18        50000         8        0         2.3     -1.4     76.1   3066  \n",
       "19        40000         9        0         2.3     -1.5     75.7   3066  \n",
       "20        50000         7        0         2.4     -1.3     76.3   3066  \n",
       "21        45000        13        0         3.1     -0.9     74.7   3066  \n",
       "22        50000         9        0         3.7     -0.5     73.7   3066  \n",
       "23        45000        13        0         4.0      0.0     74.9   3066  \n",
       "24        40000        13        0         4.5      0.2     73.4   3066  \n",
       "25        30000        13        0         2.0      1.1     93.6   3068  \n",
       "26        25000        11        0         2.9      2.4     96.4   3068  \n",
       "27        30000        14        0         3.3      2.3     93.2   3068  \n",
       "28        30000        15        0         4.7      2.3     84.2   3068  \n",
       "29        30000        16        0         4.7      1.3     78.3   3068  \n",
       "30        30000        11        0         3.1      0.7     84.0   3068  \n",
       "31        30000        11        0         4.1      1.3     81.7   3068  \n",
       "32        30000        14        0         3.2      0.5     82.2   3068  \n",
       "33        30000        10        0         1.7      0.5     91.6   3068  \n",
       "34        40000         8        0         1.0     -0.8     87.5   3068  \n",
       "35        40000        14        0         1.5     -1.0     83.3   3068  \n",
       "36        40000         9        0         0.7     -1.6     83.0   3068  \n",
       "37        40000        10        0         0.4     -1.9     82.7   3068  \n",
       "38        40000        11        0         1.1     -1.6     81.9   3068  \n",
       "39        40000        15        0         1.8     -1.5     78.3   3068  \n",
       "40        40000        10        0         0.0     -2.2     83.1   3068  \n",
       "41        40000         9        0         1.0     -2.2     77.2   3068  \n",
       "42        40000         6        0        -1.1     -3.8     78.7   3068  \n",
       "43        40000         8        0         0.6     -2.2     79.5   3068  \n",
       "44        50000         5        0         0.5     -1.9     82.0   3068  \n",
       "45        50000         6        0        -0.1     -1.9     85.8   3068  \n",
       "46        50000         3        0         1.3     -1.3     82.6   3068  \n",
       "47        40000         8        0         2.2     -0.8     80.3   3068  \n",
       "48        40000        10        0         2.8     -0.5     78.7   3068  \n",
       "49        40000         8        0         3.4      0.0     78.2   3068  \n",
       "50        16000        16        0         3.3      2.5     94.4   3075  \n",
       "51        20000        13        0         3.2      2.3     93.8   3075  \n",
       "52        27000        17        0         3.8      2.5     91.1   3075  \n",
       "53        40000        13        0         4.0      2.2     87.9   3075  \n",
       "54         6000        25       38         2.5      1.5     93.2   3075  \n",
       "55        35000        14       29         2.5      1.4     92.5   3075  \n",
       "56        28000        13        0         1.7      0.7     93.1   3075  \n",
       "57        21000        13        0         2.1      1.0     92.3   3075  \n",
       "58        30000        11        0         1.4     -0.1     89.6   3075  \n",
       "59        30000         9        0         0.8     -0.8     88.9   3075  \n",
       "60        35000        10        0         1.0     -0.5     89.5   3075  \n",
       "61        30000         6        0         0.6     -1.1     88.2   3075  \n",
       "62        35000         9        0         0.9     -0.8     88.2   3075  \n",
       "63        35000        10        0         1.5      0.0     89.6   3075  \n",
       "64        35000         9        0         1.8      0.4     90.2   3075  \n",
       "65        45000        11        0         1.6      0.0     88.9   3075  \n",
       "66        40000         7        0         1.8     -0.1     87.1   3075  \n",
       "67        50000        10        0         1.4     -0.1     89.6   3075  \n",
       "68        40000         8        0         2.4      0.0     84.0   3075  \n",
       "69        40000         8        0         2.2      0.2     86.5   3075  \n",
       "70        30000         2        0         1.9     -0.4     84.5   3075  \n",
       "71        30000         9        0         2.8      0.9     87.1   3075  \n",
       "72        30000        14        0         3.5      1.8     88.5   3075  \n",
       "73        26000        16        0         4.1      2.0     86.1   3075  \n",
       "74        30000        16        0         4.4      1.5     81.2   3075  \n",
       "75        40000        13        0         4.0      2.5     89.9   3002  \n",
       "76        35000        16        0         4.8      3.2     89.4   3002  \n",
       "77         8000        19        0         4.7      3.7     93.2   3002  \n",
       "78        28000        24       33         4.9      3.4     90.1   3002  \n",
       "79        26000        24       43         5.3      2.2     80.2   3002  \n",
       "80        30000        26       36         3.9      0.9     80.6   3002  \n",
       "81        25000        16       34         4.4      2.1     84.8   3002  \n",
       "82        24000        25       38         4.1      0.7     78.4   3002  \n",
       "83        14000        22       34         4.1      0.8     78.9   3002  \n",
       "84        30000        23       32         4.3     -1.3     66.7   3002  \n",
       "85        22000        21       31         4.2     -0.5     71.2   3002  \n",
       "86        24000        17       30         4.0     -1.6     66.5   3002  \n",
       "87        23000        19       30         4.5     -1.0     67.1   3002  \n",
       "88        45000        19        0         4.3     -2.2     62.2   3002  \n",
       "89        25000        17        0         4.4     -1.2     66.7   3002  \n",
       "90         7000        21       32         3.3      1.0     84.8   3002  \n",
       "91        27000        13        0         3.7      0.2     77.6   3002  \n",
       "92        25000         8        0         2.7      1.0     88.5   3002  \n",
       "93        25000         9        0         2.7      1.2     89.8   3002  \n",
       "94        19000         9        0         2.9      1.7     91.6   3002  \n",
       "95        28000        11        0         3.4      2.2     91.8   3002  \n",
       "96        21000        13        0         3.4      2.0     90.4   3002  \n",
       "97        28000        15        0         3.8      2.7     92.4   3002  \n",
       "98        45000        17        0         4.3      3.0     91.1   3002  \n",
       "99        16000        17        0         4.9      3.6     91.2   3002  \n",
       "100       17000        15        0         4.0      2.7     91.3   3005  \n",
       "101        9000        15        0         4.6      3.6     93.2   3005  \n",
       "102       16000        21       34         4.4      2.7     88.5   3005  \n",
       "103       24000        16       31         5.1      1.9     79.6   3005  \n",
       "104       30000        16        0         5.1      1.0     74.6   3005  \n",
       "105       30000        18       29         4.4      1.1     78.9   3005  \n",
       "106       28000        19       39         4.4      0.5     75.5   3005  \n",
       "107       30000        19        0         3.5      0.2     78.9   3005  \n",
       "108       30000        19       31         3.8     -0.5     73.2   3005  \n",
       "109       30000        15       29         3.3     -0.7     74.8   3005  \n",
       "110       35000        18       30         3.2     -0.4     77.1   3005  \n",
       "111       30000        10        0         2.9      0.0     81.0   3005  \n",
       "112       25000        15        0         3.8     -0.6     72.7   3005  \n",
       "113       30000        14        0         3.4     -0.9     73.1   3005  \n",
       "114       30000        15        0         3.6     -1.4     69.5   3005  \n",
       "115       30000        11        0         4.4     -1.3     66.1   3005  \n",
       "116       28000        10        0         4.0      0.2     76.0   3005  \n",
       "117       29000        13        0         4.3      1.6     82.4   3005  \n",
       "118       26000        13        0         3.9      2.2     88.5   3005  \n",
       "119       45000        10        0         3.7      0.9     81.8   3005  \n",
       "120       40000         9       29         2.9      1.9     93.0   3005  \n",
       "121       10000        17        0         3.5      2.4     92.5   3005  \n",
       "122       19000        14        0         4.2      3.0     91.8   3005  \n",
       "123       20000        19        0         4.6      3.1     90.0   3005  \n",
       "124       23000        17        0         4.9      3.0     87.4   3005  \n",
       "125       40000        15        0         5.7      3.9     88.1   3008  \n",
       "126        7000        19       32         5.4      4.2     92.0   3008  \n",
       "127        9000        22       36         5.6      3.5     86.3   3008  \n",
       "128       26000        22       36         6.0      2.2     76.5   3008  \n",
       "129       30000        17       44         5.6      1.9     76.9   3008  \n",
       "130       30000        24       37         5.6      0.6     70.0   3008  \n",
       "131        7000        19       37         4.6      1.0     77.4   3008  \n",
       "132       40000        18       43         3.6     -0.9     72.2   3008  \n",
       "133       26000        24       38         4.4      0.3     74.3   3008  \n",
       "134       28000        17       32         4.5      0.6     75.4   3008  \n",
       "135       14000        25       41         4.0      1.2     81.8   3008  \n",
       "136       23000        19       36         5.3     -1.1     63.0   3008  \n",
       "137       17000        19       34         4.6      0.1     72.3   3008  \n",
       "138       35000        18        0         5.5     -0.4     65.3   3008  \n",
       "139       30000        16        0         5.8     -0.9     61.6   3008  \n",
       "140       29000        15        0         5.6      0.3     68.4   3008  \n",
       "141       18000        17        0         5.3      1.8     77.9   3008  \n",
       "142       28000        15        0         4.8      1.7     80.1   3008  \n",
       "143       23000        19        0         5.0      2.3     82.4   3008  \n",
       "144       22000        21        0         4.7      2.8     87.4   3008  \n",
       "145       30000        15        0         4.9      2.9     86.8   3008  \n",
       "146       13000        17        0         5.4      3.0     84.4   3008  \n",
       "147       16000        18        0         5.4      2.5     81.4   3008  \n",
       "148       26000        19        0         5.6      2.6     80.8   3008  \n",
       "149       22000        22       29         5.7      2.8     81.4   3008  \n",
       "...         ...       ...      ...         ...      ...      ...    ...  \n",
       "3349       4900         3        0         2.5      1.7     94.5   3354  \n",
       "3350       7000         1        0         3.0      1.7     91.0   3354  \n",
       "3351       5000         2        0         3.4      1.6     87.8   3354  \n",
       "3352       6000         2        0         3.5      1.7     87.9   3354  \n",
       "3353       6000         3        0         3.9      2.0     87.3   3354  \n",
       "3354       4100         6        0         3.9      2.4     89.7   3354  \n",
       "3355       3300         3        0         4.1      2.9     91.8   3354  \n",
       "3356       3200         3        0         3.7      2.6     92.5   3354  \n",
       "3357       4100         5        0         3.6      2.6     93.0   3354  \n",
       "3358       6000         5        0         2.7      1.6     92.3   3354  \n",
       "3359      10000         6        0         2.3      0.9     90.3   3354  \n",
       "3360       8000         7        0         2.1      0.6     89.6   3354  \n",
       "3361      11000         3        0         2.6      0.7     87.1   3354  \n",
       "3362      13000         5        0         2.8      0.7     85.8   3354  \n",
       "3363      11000         1        0         2.2      0.3     87.0   3354  \n",
       "3364      10000         3        0         2.5      0.8     88.5   3354  \n",
       "3365      10000         5        0         2.4      1.0     90.4   3354  \n",
       "3366       9000         3        0         2.4      0.7     88.4   3354  \n",
       "3367       8000         5        0         2.5      1.3     91.7   3354  \n",
       "3368       5000         2        0         2.8      1.8     93.0   3354  \n",
       "3369       5000         3        0         3.0      2.3     95.0   3354  \n",
       "3370       3300         1        0         2.8      2.0     94.4   3354  \n",
       "3371       3600         3        0         2.5      1.8     95.1   3354  \n",
       "3372       3400         2        0         2.7      2.1     95.8   3354  \n",
       "3373       3900         7        0         3.0      2.1     93.7   3354  \n",
       "3374       3500         2        0        -0.2     -0.5     97.3   3382  \n",
       "3375       6000         2        0         2.4      1.9     96.4   3382  \n",
       "3376       9000         5        0         3.8      1.1     82.3   3382  \n",
       "3377      10000         6        0         4.0      0.7     78.8   3382  \n",
       "3378       9000         5        0         4.2      1.1     80.0   3382  \n",
       "3379       9000         5        0         4.1      1.4     82.3   3382  \n",
       "3380       5000         5        0         3.3      1.6     88.5   3382  \n",
       "3381       3900         3        0         2.2      1.4     94.4   3382  \n",
       "3382       3000         2        0         2.6      1.8     94.4   3382  \n",
       "3383       2800         1        0         2.7      2.0     95.1   3382  \n",
       "3384       3000         5        0         2.9      2.4     96.4   3382  \n",
       "3385       5000         3        0         3.7      2.6     92.5   3382  \n",
       "3386       9000         3        0         4.3      2.7     89.2   3382  \n",
       "3387       7000         5        0         4.6      2.6     86.8   3382  \n",
       "3388      10000         3        0         4.6      2.6     86.8   3382  \n",
       "3389      12000         5        0         4.4      2.6     87.8   3382  \n",
       "3390      15000         3        0         4.0      2.2     87.8   3382  \n",
       "3391      11000         5        0         2.6      1.3     90.9   3382  \n",
       "3392      13000         6        0         3.8      2.3     89.8   3382  \n",
       "3393       5000         2        0         1.5      0.2     90.9   3382  \n",
       "3394       3500         2        0        -0.7     -1.5     92.8   3382  \n",
       "3395       4100         2        0        -1.3     -1.8     94.6   3382  \n",
       "3396       8000         6        0        -1.6     -1.9     96.1   3382  \n",
       "3397        500         3        0        -0.3     -0.5     98.0   3382  \n",
       "3398       2900         2        0         1.3      1.2     99.3   3382  \n",
       "3399      11000         5        0         0.5      0.0     96.2   3385  \n",
       "3400       8000         3        0         1.9      0.8     92.2   3385  \n",
       "3401      14000         5        0         4.5      0.9     77.1   3385  \n",
       "3402      21000         5        0         5.8      0.3     67.5   3385  \n",
       "3403      22000         3        0         5.8     -0.4     64.0   3385  \n",
       "3404      20000         3        0         4.9     -0.6     67.1   3385  \n",
       "3405      16000         2        0         4.0     -0.1     74.3   3385  \n",
       "3406      12000         5        0         3.1      0.6     83.5   3385  \n",
       "3407      10000         5        0         2.8      0.7     85.8   3385  \n",
       "3408       8000         5        0         2.5      0.7     87.8   3385  \n",
       "3409       8000         6        0         1.9      0.3     89.0   3385  \n",
       "3410       7000         5        0         1.8      0.5     90.9   3385  \n",
       "3411       6000         6        0         2.5      1.5     93.2   3385  \n",
       "3412       6000         7        0         3.1      2.1     93.1   3385  \n",
       "3413       8000         7        0         3.5      2.2     91.1   3385  \n",
       "3414       9000         7        0         3.6      2.2     90.4   3385  \n",
       "3415       9000         9        0         3.7      2.4     91.2   3385  \n",
       "3416       9000         8        0         4.0      2.9     92.5   3385  \n",
       "3417       8000         9        0         3.7      3.0     95.2   3385  \n",
       "3418      20000        10        0         4.3      3.3     93.0   3385  \n",
       "3419      21000         9        0         3.7      2.5     91.8   3385  \n",
       "3420      17000         5        0         1.9      1.0     93.6   3385  \n",
       "3421       9000         7        0         1.4      0.9     96.4   3385  \n",
       "3422      21000         5        0         2.2      1.9     97.9   3385  \n",
       "3423       9000         6        0         1.2      0.7     96.5   3385  \n",
       "3424       5000         3        0        -0.2     -1.0     93.4   3391  \n",
       "3425       8000         2        0         2.2      0.8     90.4   3391  \n",
       "3426      10000         3        0         3.5      1.0     83.6   3391  \n",
       "3427      15000         2        0         4.8     -0.2     69.7   3391  \n",
       "3428      20000         3        0         5.2     -0.7     65.2   3391  \n",
       "3429      20000         6        0         4.6     -0.7     68.0   3391  \n",
       "3430      15000         2        0         3.1     -0.7     75.8   3391  \n",
       "3431      12000         1        0         1.7     -0.7     83.8   3391  \n",
       "3432      12000         1        0         2.0     -0.2     85.1   3391  \n",
       "3433      10000         3        0         2.1      0.1     86.4   3391  \n",
       "3434      10000         2        0         2.7      0.7     86.4   3391  \n",
       "3435       8000         3        0         2.5      0.9     89.2   3391  \n",
       "3436       7000         2        0         2.6      1.2     90.2   3391  \n",
       "3437       6000         3        0         2.5      1.3     91.7   3391  \n",
       "3438       6000         5        0         3.2      1.8     90.2   3391  \n",
       "3439       5000         3        0         3.2      1.9     90.9   3391  \n",
       "3440       5000         3        0         3.2      2.0     91.8   3391  \n",
       "3441       6000         5        0         3.3      2.0     91.1   3391  \n",
       "3442       6000         7        0         3.3      2.0     91.1   3391  \n",
       "3443       6000         6        0         3.3      2.1     91.7   3391  \n",
       "3444       5000         6        0         3.1      2.3     94.4   3391  \n",
       "3445       5000         3        0         2.7      1.9     94.3   3391  \n",
       "3446       2000         6        0         0.6      0.2     97.0   3391  \n",
       "3447       2200         7        0        -0.6     -1.2     94.5   3391  \n",
       "3448       4000         2        0         2.5      2.3     98.6   3391  \n",
       "3449          0         0        0         1.9      1.3     95.7  99142  \n",
       "3450          0         0        0         2.3      1.5     94.3  99142  \n",
       "3451          0         0        0         2.6      1.7     93.8  99142  \n",
       "3452          0         0        0         2.9      1.9     93.1  99142  \n",
       "3453          0         0        0         3.0      1.6     90.5  99142  \n",
       "3454          0         0        0         2.9      1.6     91.1  99142  \n",
       "3455          0         0        0         2.0      1.5     96.5  99142  \n",
       "3456          0         0        0         2.4      1.7     95.0  99142  \n",
       "3457          0         0        0         3.3      1.5     88.0  99142  \n",
       "3458          0         0        0         3.7      1.9     87.9  99142  \n",
       "3459          0         0        0         4.0      2.0     86.8  99142  \n",
       "3460          0         0        0         4.1      2.2     87.4  99142  \n",
       "3461          0         0        0         3.8      2.8     93.3  99142  \n",
       "3462          0         0        0         4.0      2.6     90.7  99142  \n",
       "3463          0         0        0         3.6      2.4     91.9  99142  \n",
       "3464          0         0        0         3.6      2.1     89.9  99142  \n",
       "3465          0         0        0         3.3      2.6     95.2  99142  \n",
       "3466          0         0        0         2.7      1.9     94.5  99142  \n",
       "3467          0         0        0         2.0      1.0     93.1  99142  \n",
       "3468          0         0        0         0.9     -0.3     91.7  99142  \n",
       "3469          0         0        0         1.1      0.0     92.3  99142  \n",
       "3470          0         0        0         1.4     -0.2     89.1  99142  \n",
       "3471          0         0        0         1.2     -0.3     89.8  99142  \n",
       "3472          0         0        0         1.3     -0.3     89.1  99142  \n",
       "3473          0         0        0         1.5      0.3     91.8  99142  \n",
       "3474       9000         2        0         5.2      4.2     93.2   3844  \n",
       "3475      10000         3        0         5.6      4.2     90.5   3844  \n",
       "3476      11000         5        0         6.0      4.1     87.5   3844  \n",
       "3477      14000         5        0         6.5      4.2     85.0   3844  \n",
       "3478      13000         3        0         6.7      4.6     86.3   3844  \n",
       "3479      15000         3        0         6.9      4.7     85.7   3844  \n",
       "3480      12000         3        0         5.9      4.2     88.7   3844  \n",
       "3481      12000         5        0         6.1      4.2     87.5   3844  \n",
       "3482      10000         5        0         5.8      4.1     88.7   3844  \n",
       "3483      10000         5        0         5.7      4.0     88.6   3844  \n",
       "3484       8000         1        0         5.4      3.8     89.3   3844  \n",
       "3485       8000         0        0         5.0      3.7     91.2   3844  \n",
       "3486       8000         2        0         5.1      3.8     91.1   3844  \n",
       "3487       7000         2        0         4.5      3.8     95.0   3844  \n",
       "3488       3900         2        0         2.8      2.5     97.9   3844  \n",
       "3489       3800         2        0         3.2      2.9     97.8   3844  \n",
       "3490       4300         0        0         3.8      3.6     98.5   3844  \n",
       "3491       2800         2        0         3.7      3.4     98.0   3844  \n",
       "3492       3800         1        0         3.7      3.5     98.6   3844  \n",
       "3493       2800         1        0         2.9      2.5     97.1   3844  \n",
       "3494        100         3        0         1.3      1.0     97.9   3844  \n",
       "3495         80         1        0         0.8      0.7     99.4   3844  \n",
       "3496        100         2        0         0.9      0.8     99.2   3844  \n",
       "3497        100         1        0         0.3      0.3    100.0   3844  \n",
       "3498        200         2        0         1.1      1.1    100.0   3844  \n",
       "\n",
       "[3499 rows x 11 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df = weather_df.reset_index(drop=True)\n",
    "weather_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3499"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#how many records you got? \n",
    "len(weather_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "you should get an answer around 3499. Again number changes slightly as we are using streaming data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 8: Join Weather Data (weather_df) with Site Data (df2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The weather data we get does not have location tag. You can just use the weather station id and always go back the site location table to find the coordinates. It is a good strategy for data storage, especially for large data sets. And it is probably a bad idea to combine them into one, as in such case both station id and timetag cannot be used as index any more.  \n",
    "\n",
    "But (just) for practice, let's combine them into one to create a spatial file for later use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>WindDirection</th>\n",
       "      <th>PressureTendency</th>\n",
       "      <th>WeatherType</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>WindGust</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>6000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>93.7</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>94.5</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>90.4</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              DateTime WindDirection PressureTendency WeatherType Visibility  \\\n",
       "0  2019-01-20 10:00:00           WSW                R          12       6000   \n",
       "1  2019-01-20 11:00:00            SW                R           8      45000   \n",
       "2  2019-01-20 12:00:00           WSW                R          10      40000   \n",
       "\n",
       "  WindSpeed WindGust Temperature DewPoint Humidity    id  \n",
       "0        10        0         2.1      1.2     93.7  3066  \n",
       "1        10        0         2.8      2.0     94.5  3066  \n",
       "2        11        0         3.6      2.2     90.4  3066  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>elevation</th>\n",
       "      <th>id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>nationalPark</th>\n",
       "      <th>obsSource</th>\n",
       "      <th>region</th>\n",
       "      <th>unitaryAuthArea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.0000</td>\n",
       "      <td>3066</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.0000</td>\n",
       "      <td>3068</td>\n",
       "      <td>57.7120</td>\n",
       "      <td>-3.3220</td>\n",
       "      <td>Lossiemouth</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LNDSYN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0000</td>\n",
       "      <td>3075</td>\n",
       "      <td>58.4540</td>\n",
       "      <td>-3.0890</td>\n",
       "      <td>Wick John O Groats Airport</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LNDSYN</td>\n",
       "      <td>he</td>\n",
       "      <td>Highland</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   elevation    id  latitude  longitude                        name  \\\n",
       "0     7.0000  3066   57.6494    -3.5606                     Kinloss   \n",
       "1     6.0000  3068   57.7120    -3.3220                 Lossiemouth   \n",
       "2    36.0000  3075   58.4540    -3.0890  Wick John O Groats Airport   \n",
       "\n",
       "  nationalPark obsSource region unitaryAuthArea  \n",
       "0          NaN       NaN     gr           Moray  \n",
       "1          NaN    LNDSYN     gr           Moray  \n",
       "2          NaN    LNDSYN     he        Highland  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**What is the common key word for joining two tables?**\n",
    "\n",
    "**What sort of join should we perform? inner? outter? left? or right?**\n",
    "\n",
    "**You can also do it use merge, if you forgot, go to geocomputation week 6 - practical**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For your convinience, read more about merge [here](http://pandas.pydata.org/pandas-docs/stable/merging.html). \n",
    "\n",
    "![Illustration of the Pandas merge function](http://pandas.pydata.org/pandas-docs/stable/_images/merging_merge_on_key.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-ed757f392f17>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf_in_one\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mweather_df\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msite_df\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mon\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'id'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhow\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'left'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/anaconda3/envs/gsa2018/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36mmerge\u001b[0;34m(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)\u001b[0m\n\u001b[1;32m     59\u001b[0m                          \u001b[0mright_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msuffixes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msuffixes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m                          \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindicator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindicator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m                          validate=validate)\n\u001b[0m\u001b[1;32m     62\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     63\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda3/envs/gsa2018/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, left, right, how, on, left_on, right_on, axis, left_index, right_index, sort, suffixes, copy, indicator, validate)\u001b[0m\n\u001b[1;32m    553\u001b[0m         \u001b[0;31m# validate the merge keys dtypes. We may need to coerce\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    554\u001b[0m         \u001b[0;31m# to avoid incompat dtypes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 555\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_coerce_merge_keys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    556\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    557\u001b[0m         \u001b[0;31m# If argument passed to validate,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda3/envs/gsa2018/lib/python3.6/site-packages/pandas/core/reshape/merge.py\u001b[0m in \u001b[0;36m_maybe_coerce_merge_keys\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    984\u001b[0m             elif (not is_numeric_dtype(lk)\n\u001b[1;32m    985\u001b[0m                     and (is_numeric_dtype(rk) and not is_bool_dtype(rk))):\n\u001b[0;32m--> 986\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    987\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mis_datetimelike\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlk\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_datetimelike\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    988\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat"
     ]
    }
   ],
   "source": [
    "df_in_one = pd.merge(weather_df, site_df, on = 'id', how = 'left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may get a ValueError:You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat.\n",
    "\n",
    "Why??? Think really hard about that before you raise your hand to get an answer from us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "elevation          float64\n",
       "id                   int64\n",
       "latitude           float64\n",
       "longitude          float64\n",
       "name                object\n",
       "nationalPark        object\n",
       "obsSource           object\n",
       "region              object\n",
       "unitaryAuthArea     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DateTime            object\n",
       "WindDirection       object\n",
       "PressureTendency    object\n",
       "WeatherType         object\n",
       "Visibility          object\n",
       "WindSpeed           object\n",
       "WindGust            object\n",
       "Temperature         object\n",
       "DewPoint            object\n",
       "Humidity            object\n",
       "id                  object\n",
       "dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df.dtypes # check the data types for weather_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in ['WindDirection','PressureTendency']:\n",
    "    weather_df[c] = weather_df[c].astype('str')\n",
    "for c in ['DewPoint','WindGust','Humidity','WindSpeed','Temperature','Visibility','WeatherType']:\n",
    "    weather_df[c] = pd.to_numeric(weather_df[c], errors='coerce') # change numeric data into integar and float types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DateTime             object\n",
       "WindDirection        object\n",
       "PressureTendency     object\n",
       "WeatherType           int64\n",
       "Visibility            int64\n",
       "WindSpeed             int64\n",
       "WindGust              int64\n",
       "Temperature         float64\n",
       "DewPoint            float64\n",
       "Humidity            float64\n",
       "id                   object\n",
       "dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df.dtypes # check the changes of data types for weather_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>WindDirection</th>\n",
       "      <th>PressureTendency</th>\n",
       "      <th>WeatherType</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>WindGust</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>id</th>\n",
       "      <th>elevation</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>nationalPark</th>\n",
       "      <th>obsSource</th>\n",
       "      <th>region</th>\n",
       "      <th>unitaryAuthArea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>6000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1000</td>\n",
       "      <td>1.2000</td>\n",
       "      <td>93.7000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>94.5000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>90.4000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>35000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>86.7000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>14</td>\n",
       "      <td>9000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>88.5000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              DateTime WindDirection PressureTendency  WeatherType  \\\n",
       "0  2019-01-20 10:00:00           WSW                R           12   \n",
       "1  2019-01-20 11:00:00            SW                R            8   \n",
       "2  2019-01-20 12:00:00           WSW                R           10   \n",
       "3  2019-01-20 13:00:00             W                R            8   \n",
       "4  2019-01-20 14:00:00             W                R           14   \n",
       "\n",
       "   Visibility  WindSpeed  WindGust  Temperature  DewPoint  Humidity    id  \\\n",
       "0        6000         10         0       2.1000    1.2000   93.7000  3066   \n",
       "1       45000         10         0       2.8000    2.0000   94.5000  3066   \n",
       "2       40000         11         0       3.6000    2.2000   90.4000  3066   \n",
       "3       35000         13         0       4.2000    2.2000   86.7000  3066   \n",
       "4        9000         17         0       3.9000    2.2000   88.5000  3066   \n",
       "\n",
       "   elevation  latitude  longitude     name nationalPark obsSource region  \\\n",
       "0     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "1     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "2     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "3     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "4     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "\n",
       "  unitaryAuthArea  \n",
       "0           Moray  \n",
       "1           Moray  \n",
       "2           Moray  \n",
       "3           Moray  \n",
       "4           Moray  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_df['id'] = weather_df['id'].astype('int')\n",
    "df_in_one = pd.merge(weather_df, site_df, how = 'left', on = 'id')\n",
    "df_in_one.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 9: Generate Shapefile/Geojson File from DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The examples we gave here probably not a great one. But it is true that quite often we are in the situation that no spatial file is available and we have to generate one by yourself. \n",
    "\n",
    "You have learned how to use QGIS to import CSV and generate a vector map from there. Python can do that as well, with simple steps. One more spatial data package you will learn here is Shapely. We will first show you an example and you will create a shapefile of site station following the example.\n",
    "\n",
    "It should be installed already, if not, do it by yourself."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "step 1: you use the package shapely to generate points from latitute and longitude. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from shapely.geometry import Point\n",
    "\n",
    "\n",
    "# combine lat and lon column to a shapely Point() object\n",
    "df_in_one['geometry'] = df_in_one.apply(lambda x: Point((float(x.longitude), float(x.latitude))), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DateTime</th>\n",
       "      <th>WindDirection</th>\n",
       "      <th>PressureTendency</th>\n",
       "      <th>WeatherType</th>\n",
       "      <th>Visibility</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>WindGust</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>id</th>\n",
       "      <th>elevation</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>nationalPark</th>\n",
       "      <th>obsSource</th>\n",
       "      <th>region</th>\n",
       "      <th>unitaryAuthArea</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-20 10:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>12</td>\n",
       "      <td>6000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1000</td>\n",
       "      <td>1.2000</td>\n",
       "      <td>93.7000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-20 11:00:00</td>\n",
       "      <td>SW</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>45000</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>94.5000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-20 12:00:00</td>\n",
       "      <td>WSW</td>\n",
       "      <td>R</td>\n",
       "      <td>10</td>\n",
       "      <td>40000</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>3.6000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>90.4000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-20 13:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>8</td>\n",
       "      <td>35000</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>4.2000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>86.7000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-20 14:00:00</td>\n",
       "      <td>W</td>\n",
       "      <td>R</td>\n",
       "      <td>14</td>\n",
       "      <td>9000</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.9000</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>88.5000</td>\n",
       "      <td>3066</td>\n",
       "      <td>7.0000</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              DateTime WindDirection PressureTendency  WeatherType  \\\n",
       "0  2019-01-20 10:00:00           WSW                R           12   \n",
       "1  2019-01-20 11:00:00            SW                R            8   \n",
       "2  2019-01-20 12:00:00           WSW                R           10   \n",
       "3  2019-01-20 13:00:00             W                R            8   \n",
       "4  2019-01-20 14:00:00             W                R           14   \n",
       "\n",
       "   Visibility  WindSpeed  WindGust  Temperature  DewPoint  Humidity    id  \\\n",
       "0        6000         10         0       2.1000    1.2000   93.7000  3066   \n",
       "1       45000         10         0       2.8000    2.0000   94.5000  3066   \n",
       "2       40000         11         0       3.6000    2.2000   90.4000  3066   \n",
       "3       35000         13         0       4.2000    2.2000   86.7000  3066   \n",
       "4        9000         17         0       3.9000    2.2000   88.5000  3066   \n",
       "\n",
       "   elevation  latitude  longitude     name nationalPark obsSource region  \\\n",
       "0     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "1     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "2     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "3     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "4     7.0000   57.6494    -3.5606  Kinloss          NaN       NaN     gr   \n",
       "\n",
       "  unitaryAuthArea                 geometry  \n",
       "0           Moray  POINT (-3.5606 57.6494)  \n",
       "1           Moray  POINT (-3.5606 57.6494)  \n",
       "2           Moray  POINT (-3.5606 57.6494)  \n",
       "3           Moray  POINT (-3.5606 57.6494)  \n",
       "4           Moray  POINT (-3.5606 57.6494)  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# there is a column added as geometry\n",
    "df_in_one.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "step 2: Then you use Geopandas to generate 'Geopandas dataframe' from 'Pandas dataframe'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas\n",
    "df_in_one = geopandas.GeoDataFrame(df_in_one, geometry='geometry')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "step 3: Then you set a projected and geographic coordination system here to convert the file into a shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_in_one.crs= \"+proj=longlat +ellps= EPSG:27700 +datum=WGS84 +no_defs\"\n",
    "df_in_one.to_file('weather.shp', driver='ESRI Shapefile')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "step 4: The generated shapefile should be in the same folder as your ipython notebook. and the shapefile can be openned by other GIS tools, such as QGIS. Try it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3499"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_in_one)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You have learned how to use QGIS to import CSV and generate a vector map from there. Python can do that as well, with simple steps. One more spatial data package you will learn here is Shapely. \n",
    "\n",
    "It should be installed already, if not, do it by yourself.\n",
    "\n",
    "\n",
    "Though there are c.3531 records, there are only a few points shown in the map. why? because may records have the exact same coordinates. They are weather records from one weather station collected at different time. So there should be only 148 points (== number of weather stations) shown in the map.\n",
    "\n",
    "There are two directions for your to further explore **after the practical**. \n",
    "\n",
    "1 - go for time series analysis, take one weather station as example - time series analysis and modeling is a challenge task to do.\n",
    "2 - generate a series of maps by time series - which sounds more spatial data related, let's try this using what you have learned in Geocomputation week 8 - making maps."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Could you prepare a shapefile of weather station locations using just 'site_df' for task 10, following what we did to generete weather shapefile?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_df['geometry'] = site_df.apply(lambda x: Point((float(x.longitude), float(x.latitude))), axis=1)\n",
    "site_df = geopandas.GeoDataFrame(site_df, geometry='geometry')\n",
    "site_df.crs= \"+proj=longlat +ellps=EPSG:27700 +datum=WGS84 +no_defs\"\n",
    "site_df.to_file('weather_station.shp', driver='ESRI Shapefile')\n",
    "len(site_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Task 10: Generating a Distance Matrix "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A distance matrix is a square matrix (two-dimensional array) containing the distances, taken pairwise, between the elements of a set. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will calculate a distance matrix for all weather stations using methods we mentioned in lecture this week."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>elevation</th>\n",
       "      <th>id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>nationalPark</th>\n",
       "      <th>obsSource</th>\n",
       "      <th>region</th>\n",
       "      <th>unitaryAuthArea</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.0000</td>\n",
       "      <td>3066</td>\n",
       "      <td>57.6494</td>\n",
       "      <td>-3.5606</td>\n",
       "      <td>Kinloss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.5606 57.6494)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.0000</td>\n",
       "      <td>3068</td>\n",
       "      <td>57.7120</td>\n",
       "      <td>-3.3220</td>\n",
       "      <td>Lossiemouth</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LNDSYN</td>\n",
       "      <td>gr</td>\n",
       "      <td>Moray</td>\n",
       "      <td>POINT (-3.322 57.712)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0000</td>\n",
       "      <td>3075</td>\n",
       "      <td>58.4540</td>\n",
       "      <td>-3.0890</td>\n",
       "      <td>Wick John O Groats Airport</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LNDSYN</td>\n",
       "      <td>he</td>\n",
       "      <td>Highland</td>\n",
       "      <td>POINT (-3.089 58.454)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.0000</td>\n",
       "      <td>3002</td>\n",
       "      <td>60.7490</td>\n",
       "      <td>-0.8540</td>\n",
       "      <td>Baltasound</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>os</td>\n",
       "      <td>Shetland Islands</td>\n",
       "      <td>POINT (-0.854 60.749)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>82.0000</td>\n",
       "      <td>3005</td>\n",
       "      <td>60.1390</td>\n",
       "      <td>-1.1830</td>\n",
       "      <td>Lerwick (S. Screen)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LNDSYN</td>\n",
       "      <td>os</td>\n",
       "      <td>Shetland Islands</td>\n",
       "      <td>POINT (-1.183 60.139)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   elevation    id  latitude  longitude                        name  \\\n",
       "0     7.0000  3066   57.6494    -3.5606                     Kinloss   \n",
       "1     6.0000  3068   57.7120    -3.3220                 Lossiemouth   \n",
       "2    36.0000  3075   58.4540    -3.0890  Wick John O Groats Airport   \n",
       "3    15.0000  3002   60.7490    -0.8540                  Baltasound   \n",
       "4    82.0000  3005   60.1390    -1.1830         Lerwick (S. Screen)   \n",
       "\n",
       "  nationalPark obsSource region   unitaryAuthArea                 geometry  \n",
       "0          NaN       NaN     gr             Moray  POINT (-3.5606 57.6494)  \n",
       "1          NaN    LNDSYN     gr             Moray    POINT (-3.322 57.712)  \n",
       "2          NaN    LNDSYN     he          Highland    POINT (-3.089 58.454)  \n",
       "3          NaN       NaN     os  Shetland Islands    POINT (-0.854 60.749)  \n",
       "4          NaN    LNDSYN     os  Shetland Islands    POINT (-1.183 60.139)  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Could you calculate the distance between station id - 3066 to station id 3068?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "#x - longitude y - latitude\n",
    "\n",
    "ori = [{'y': site_df.iloc[0]['latitude'], 'x':site_df.iloc[0]['longitude']}]\n",
    "des = [{'y': site_df.iloc[1]['latitude'], 'x':site_df.iloc[1]['longitude']}]\n",
    "\n",
    "ori = pd.DataFrame(ori)\n",
    "des = pd.DataFrame(des)\n",
    "\n",
    "# to make your life easier - ori is the station 3066, des is the station 3068"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To verify what we taught in the class, could you complete the function below? Calculate the distance based on a Euclidean method. the squre_root method.\n",
    "\n",
    "**implement Euclidean method**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "def distance_euclidean(ori,des):\n",
    "    \"\"\"\n",
    "    calculate the euclidean distant between two points. -  \n",
    "    \"\"\"\n",
    "    distance = np.sqrt((ori['latitude']-des['latitude'])**2+(ori['longitude']-des['longitude'])**2)\n",
    "    return distance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "haversine method, using package pyproj, and cosines method are provided, for you the compare the results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "from math import radians, cos, sin, asin, sqrt\n",
    "\n",
    "def distance_haversine(ori,des):\n",
    "    \"\"\"\n",
    "    Calculate the great circle distance between two points \n",
    "    on the earth (specified in decimal degrees)\n",
    "    \"\"\"\n",
    "    # convert decimal degrees to radians \n",
    "    lon1, lat1, lon2, lat2 = map(radians, [ori.x, ori.y, des.x, des.y])\n",
    "\n",
    "    # haversine formula \n",
    "    dlon = lon2 - lon1 \n",
    "    dlat = lat2 - lat1 \n",
    "    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2\n",
    "    c = 2 * asin(sqrt(a)) \n",
    "    r = 6371 # Radius of earth in kilometers. Use 3956 for miles\n",
    "    return c * r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyproj\n",
    "\n",
    "def distance_pyproj(ori, des):\n",
    "    geod = pyproj.Geod(ellps='WGS84')\n",
    "    angle1,angle2,distance = geod.inv(ori.x[0], ori.y[0], des.x[0], des.y[0])\n",
    "    print (\"{0:8.4f}\".format(distance/1000))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "def distance_cosines(ori, des):\n",
    "    # law of cosines\n",
    "    distance = math.acos(math.sin(math.radians(ori.y))*math.sin(math.radians(des.y))+math.cos(math.radians(ori.y))*math.cos(math.radians(des.y))*math.cos(math.radians(des.x)-math.radians(ori.x)))*6371\n",
    "    print (\"{0:8.4f}\".format(distance))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.800405971038828"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_haversine(ori,des)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 15.8004\n"
     ]
    }
   ],
   "source": [
    "distance_cosines(ori, des)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 15.8501\n"
     ]
    }
   ],
   "source": [
    "distance_pyproj(ori, des)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**they are slightly different! but very close**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we calculate distance matrix using Scipy package. 'euclidean' method is used among [many other methods](https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cdist.html) provided. You already tested the Euclidean method using lat and long, the answer seems quite wrong. (because it is in degree, not in meters). \n",
    "\n",
    "To get the distance in meters, we will first project the data into two-dimensional space (from long, lat to x, y). Then calculate the distance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyproj\n",
    "from scipy.spatial import distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+proj=longlat +ellps=EPSG:27700 +datum=WGS84 +no_defs\n"
     ]
    }
   ],
   "source": [
    "print(site_df.crs) # what is the projected and geographic coordinate system?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define some common projections using EPSG codes\n",
    "wgs84=pyproj.Proj(\"+init=EPSG:4326\") # LatLon with WGS84 datum used by GPS units and Google Earth\n",
    "osgb36=pyproj.Proj(\"+init=EPSG:27700\") # UK Ordnance Survey, 1936 datum - this is the one used in the UK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "site_df['x'], site_df['y'] = pyproj.transform(wgs84, osgb36, list(site_df['longitude']), list(site_df['latitude']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords = site_df[['x','y']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>306,955.6288</td>\n",
       "      <td>863,236.8602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>321,331.0898</td>\n",
       "      <td>869,902.6478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>336,546.1921</td>\n",
       "      <td>952,261.7590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>462,571.0130</td>\n",
       "      <td>1,207,872.3580</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             x              y\n",
       "0 306,955.6288   863,236.8602\n",
       "1 321,331.0898   869,902.6478\n",
       "2 336,546.1921   952,261.7590\n",
       "3 462,571.0130 1,207,872.3580"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords.head(4)  #check it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[     0.        ,  15845.71246803,  93813.82651373, ...,\n",
       "        550461.29765573, 423749.90271714, 769320.39253568],\n",
       "       [ 15845.71246803,      0.        ,  83752.7464451 , ...,\n",
       "        551191.09949613, 423308.10265446, 776229.80656304],\n",
       "       [ 93813.82651373,  83752.7464451 ,      0.        , ...,\n",
       "        623879.72440312, 493622.82100721, 859058.65697336],\n",
       "       ...,\n",
       "       [550461.29765573, 551191.09949613, 623879.72440312, ...,\n",
       "             0.        , 132228.59417675, 343772.25627342],\n",
       "       [423749.90271714, 423308.10265446, 493622.82100721, ...,\n",
       "        132228.59417675,      0.        , 442365.79990348],\n",
       "       [769320.39253568, 776229.80656304, 859058.65697336, ...,\n",
       "        343772.25627342, 442365.79990348,      0.        ]])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance.cdist(coords, coords, 'euclidean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Verifying it using measure tools in QGIS!!!** The shapefile you created can be opened there."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Credits!"
   ]
  }
 ],
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