911 Calls - Data Capstone Project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eeba45bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5f8d2289",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7d281d57",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('911 New.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fc722c17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of               lat        lng  \\\n",
       "0       40.297876 -75.581294   \n",
       "1       40.258061 -75.264680   \n",
       "2       40.121182 -75.351975   \n",
       "3       40.116153 -75.343513   \n",
       "4       40.251492 -75.603350   \n",
       "...           ...        ...   \n",
       "663517  40.157956 -75.348060   \n",
       "663518  40.136306 -75.428697   \n",
       "663519  40.013779 -75.300835   \n",
       "663520  40.121603 -75.351437   \n",
       "663521  40.015046 -75.299674   \n",
       "\n",
       "                                                     desc      zip  \\\n",
       "0       REINDEER CT & DEAD END;  NEW HANOVER; Station ...  19525.0   \n",
       "1       BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...  19446.0   \n",
       "2       HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...  19401.0   \n",
       "3       AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...  19401.0   \n",
       "4       CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...      NaN   \n",
       "...                                                   ...      ...   \n",
       "663517  SUNSET AVE & WOODLAND AVE; EAST NORRITON; 2020...  19403.0   \n",
       "663518  EAGLEVILLE RD & BUNTING CIR;  LOWER PROVIDENCE...  19403.0   \n",
       "663519  HAVERFORD STATION RD;  LOWER MERION; Station 3...  19041.0   \n",
       "663520  MARSHALL ST & HAWS AVE; NORRISTOWN; 2020-07-29...  19401.0   \n",
       "663521  HAVERFORD STATION RD & W MONTGOMERY AVE; LOWER...  19041.0   \n",
       "\n",
       "                              title         timeStamp                twp  \\\n",
       "0            EMS: BACK PAINS/INJURY  12/10/2015 17:10        NEW HANOVER   \n",
       "1           EMS: DIABETIC EMERGENCY  12/10/2015 17:29  HATFIELD TOWNSHIP   \n",
       "2               Fire: GAS-ODOR/LEAK  12/10/2015 14:39         NORRISTOWN   \n",
       "3            EMS: CARDIAC EMERGENCY  12/10/2015 16:47         NORRISTOWN   \n",
       "4                    EMS: DIZZINESS  12/10/2015 16:56   LOWER POTTSGROVE   \n",
       "...                             ...               ...                ...   \n",
       "663517  Traffic: VEHICLE ACCIDENT -  07/29/2020 15:46      EAST NORRITON   \n",
       "663518        EMS: GENERAL WEAKNESS  07/29/2020 15:52   LOWER PROVIDENCE   \n",
       "663519        EMS: VEHICLE ACCIDENT  07/29/2020 15:52       LOWER MERION   \n",
       "663520          Fire: BUILDING FIRE  07/29/2020 15:54         NORRISTOWN   \n",
       "663521  Traffic: VEHICLE ACCIDENT -  07/29/2020 15:52       LOWER MERION   \n",
       "\n",
       "                                           addr  e  \n",
       "0                        REINDEER CT & DEAD END  1  \n",
       "1                    BRIAR PATH & WHITEMARSH LN  1  \n",
       "2                                      HAWS AVE  1  \n",
       "3                            AIRY ST & SWEDE ST  1  \n",
       "4                      CHERRYWOOD CT & DEAD END  1  \n",
       "...                                         ... ..  \n",
       "663517                SUNSET AVE & WOODLAND AVE  1  \n",
       "663518              EAGLEVILLE RD & BUNTING CIR  1  \n",
       "663519                     HAVERFORD STATION RD  1  \n",
       "663520                   MARSHALL ST & HAWS AVE  1  \n",
       "663521  HAVERFORD STATION RD & W MONTGOMERY AVE  1  \n",
       "\n",
       "[663522 rows x 9 columns]>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d085a4ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>12/10/2015 17:10</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>12/10/2015 17:29</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>12/10/2015 14:39</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.116153</td>\n",
       "      <td>-75.343513</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST;  NORRISTOWN; Station 308A;...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>EMS: CARDIAC EMERGENCY</td>\n",
       "      <td>12/10/2015 16:47</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.251492</td>\n",
       "      <td>-75.603350</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END;  LOWER POTTSGROVE; S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMS: DIZZINESS</td>\n",
       "      <td>12/10/2015 16:56</td>\n",
       "      <td>LOWER POTTSGROVE</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "3  40.116153 -75.343513  AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...   \n",
       "4  40.251492 -75.603350  CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...   \n",
       "\n",
       "       zip                    title         timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY  12/10/2015 17:10        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY  12/10/2015 17:29  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK  12/10/2015 14:39         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY  12/10/2015 16:47         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS  12/10/2015 16:56   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e  \n",
       "0      REINDEER CT & DEAD END  1  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1  \n",
       "2                    HAWS AVE  1  \n",
       "3          AIRY ST & SWEDE ST  1  \n",
       "4    CHERRYWOOD CT & DEAD END  1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f31d405",
   "metadata": {},
   "source": [
    "## Basic Question\n",
    "#### What are the top 5 Zipcodes for 911 calls?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "809f882b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19401.0    45606\n",
       "19464.0    43910\n",
       "19403.0    34888\n",
       "19446.0    32270\n",
       "19406.0    22464\n",
       "Name: zip, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['zip'].value_counts().head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9e35c20",
   "metadata": {},
   "source": [
    "#### What are the top 5 townships (twp) for 911 calls?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "32aae4a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LOWER MERION    55490\n",
       "ABINGTON        39947\n",
       "NORRISTOWN      37633\n",
       "UPPER MERION    36010\n",
       "CHELTENHAM      30574\n",
       "Name: twp, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['twp'].value_counts().head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c9e8fca",
   "metadata": {},
   "source": [
    "#### How many unique title codes are on 'title' column?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6c88628c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['title'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "830a3fce",
   "metadata": {},
   "source": [
    "#### The other method to check unique title code is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7821582b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df['title'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e09d31e",
   "metadata": {},
   "source": [
    "### Create \"Reason\" Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dd8b73e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df['title'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "176158af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'EMS'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.split(':')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7b5da11e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Reason'] = df['title'].apply(lambda title: title.split(':')[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "aa79baa3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             EMS\n",
       "1             EMS\n",
       "2            Fire\n",
       "3             EMS\n",
       "4             EMS\n",
       "           ...   \n",
       "663517    Traffic\n",
       "663518        EMS\n",
       "663519        EMS\n",
       "663520       Fire\n",
       "663521    Traffic\n",
       "Name: Reason, Length: 663522, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Reason']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d7121aa",
   "metadata": {},
   "source": [
    "#### What is the most common Reason for a 911 call based on of this new column?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ef98aafb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EMS    332692\n",
       "Name: Reason, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Reason'].value_counts().head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97cdfe96",
   "metadata": {},
   "source": [
    "#### Using Seaborn to create a Countplot of 911 Calls by Reason"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "911a1bba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Reason', ylabel='count'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Reason',data=df, palette='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "dea51e11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 663522 entries, 0 to 663521\n",
      "Data columns (total 10 columns):\n",
      " #   Column     Non-Null Count   Dtype  \n",
      "---  ------     --------------   -----  \n",
      " 0   lat        663522 non-null  float64\n",
      " 1   lng        663522 non-null  float64\n",
      " 2   desc       663522 non-null  object \n",
      " 3   zip        583323 non-null  float64\n",
      " 4   title      663522 non-null  object \n",
      " 5   timeStamp  663522 non-null  object \n",
      " 6   twp        663229 non-null  object \n",
      " 7   addr       663522 non-null  object \n",
      " 8   e          663522 non-null  int64  \n",
      " 9   Reason     663522 non-null  object \n",
      "dtypes: float64(3), int64(1), object(6)\n",
      "memory usage: 50.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f754382b",
   "metadata": {},
   "source": [
    "#### Check data type of the objects in the timeStamp column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "9e0a094d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['timeStamp'].iloc[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d831b7a8",
   "metadata": {},
   "source": [
    "#### Convert the timeStamp column from string to DateTime objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f6e9ef2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['timeStamp'] = pd.to_datetime(df['timeStamp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "11f461a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['timeStamp'].iloc[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "929f22bd",
   "metadata": {},
   "source": [
    "#### Create Column Hour, Month, and Day of Week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "58e47b7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time = df['timeStamp'].iloc[0]\n",
    "time.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "4fbce1c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time.dayofweek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "558b6047",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Hour'] = df['timeStamp'].apply(lambda time: time.hour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8008ec9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Month'] = df['timeStamp'].apply(lambda time: time.month)\n",
    "df['Day of Week'] = df['timeStamp'].apply(lambda time: time.dayofweek)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "6c41e2eb",
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:10:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:29:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>2015-12-10 14:39:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.116153</td>\n",
       "      <td>-75.343513</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST;  NORRISTOWN; Station 308A;...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>EMS: CARDIAC EMERGENCY</td>\n",
       "      <td>2015-12-10 16:47:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.251492</td>\n",
       "      <td>-75.603350</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END;  LOWER POTTSGROVE; S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMS: DIZZINESS</td>\n",
       "      <td>2015-12-10 16:56:00</td>\n",
       "      <td>LOWER POTTSGROVE</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "3  40.116153 -75.343513  AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...   \n",
       "4  40.251492 -75.603350  CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...   \n",
       "\n",
       "       zip                    title           timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY 2015-12-10 17:10:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY 2015-12-10 17:29:00  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK 2015-12-10 14:39:00         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY 2015-12-10 16:47:00         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS 2015-12-10 16:56:00   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e Reason  Hour  Month  Day of Week  \n",
       "0      REINDEER CT & DEAD END  1    EMS    17     12            3  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1    EMS    17     12            3  \n",
       "2                    HAWS AVE  1   Fire    14     12            3  \n",
       "3          AIRY ST & SWEDE ST  1    EMS    16     12            3  \n",
       "4    CHERRYWOOD CT & DEAD END  1    EMS    16     12            3  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c6fd0ce",
   "metadata": {},
   "source": [
    "#### Use dmap to map the actual string names to the day of week:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "4c5dae08",
   "metadata": {},
   "outputs": [],
   "source": [
    "dmap = {0:'Mon',1:'Tue',2:'Wed',3:'Thu',4:'Fri',5:'Sat',6:'Sun'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "7c5ee764",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Day of Week'] = df['Day of Week'].map(dmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "4413afb5",
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:10:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:29:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>2015-12-10 14:39:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.116153</td>\n",
       "      <td>-75.343513</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST;  NORRISTOWN; Station 308A;...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>EMS: CARDIAC EMERGENCY</td>\n",
       "      <td>2015-12-10 16:47:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.251492</td>\n",
       "      <td>-75.603350</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END;  LOWER POTTSGROVE; S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMS: DIZZINESS</td>\n",
       "      <td>2015-12-10 16:56:00</td>\n",
       "      <td>LOWER POTTSGROVE</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "3  40.116153 -75.343513  AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...   \n",
       "4  40.251492 -75.603350  CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...   \n",
       "\n",
       "       zip                    title           timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY 2015-12-10 17:10:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY 2015-12-10 17:29:00  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK 2015-12-10 14:39:00         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY 2015-12-10 16:47:00         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS 2015-12-10 16:56:00   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e Reason  Hour  Month Day of Week  \n",
       "0      REINDEER CT & DEAD END  1    EMS    17     12         Thu  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1    EMS    17     12         Thu  \n",
       "2                    HAWS AVE  1   Fire    14     12         Thu  \n",
       "3          AIRY ST & SWEDE ST  1    EMS    16     12         Thu  \n",
       "4    CHERRYWOOD CT & DEAD END  1    EMS    16     12         Thu  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1623bd0",
   "metadata": {},
   "source": [
    "#### Create a Countplot of the Day of Week column with the hue based off of the Reason column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "ab7a11ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22c034718e0>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Day of Week',data=df,hue='Reason',palette='viridis')\n",
    "#To relocate the legend\n",
    "plt.legend(bbox_to_anchor=(1.05,1),loc=2,borderaxespad=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "4d0f36ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22c035c5400>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9EyTNlTS3tra2hc7KzMysZWWelCV1AX4BXBMRmxvbtUQsGok3VmbXQMT9ETEkIoZUV1fvrclmZmatItOkLKkDhYT8SEQ8nsLrJfVO23sDG1J8NdC3qHgNsCbFa0rEdykjqQo4BNjU8mdiZmaWvSxnXwt4EFgaEXcUbZoOjEufxwFPFsXHphnVR1KY0DUnDXFvkXRKOuZlu5VpONYY4AVfTzYzs7Yqy/uUTwUuBRZKWpBiNwHfAaZKGg+8AZwPEBGLJU0FllCYuT0xIupTuauAyUAnChO8nk3xB4GH06SwTRRmb5s1yhOhzCyvspx9/QdKX/MFGLaHMpOASSXic4HjS8TfIyV1MzOzts5P9DIzyxE/i7p9c1JuI/yDamZ24POCFGZmZjnhpGxmZpYTHr42M2uELx1ZObmnbGZmlhNOymZmZjnhpGxmZpYTTUrKkmY2JWZmZmbN1+hEL0kdgc7A4ZK68/4TuroBH864bWZmZu3K3mZfXwlcQyEBz+P9pLwZ+H52zTIzM2t/Gk3KEXEXcJekL0fEPWVqk5mZWbvUpPuUI+IeSf8M9CsuExEPZdQuMzOzdqdJSVnSw8BRwAKgYTnFAJyUzczMWkhTn+g1BBgYEZFlY6x98vrGZmYFTb1PeRFwRJYNMTMza++a2lM+HFgiaQ6wrSEYEWdn0iozM7N2qKlJ+eYsG2FmZmZNn339n1k3xMzaJq+iZNZymjr7eguF2dYABwEdgHcjoltWDTMzM2tvmtpT7lr8XdI5wNAsGmRmZtZeNfWa8i4i4peSbmjpxpiZ7Y2Hy+1A1tTh63OLvlZQuG/Z9yybmZm1oKb2lM8q+lwHrAJGt3hrzMzM2rEmPTwkIr5Q9LoiIiZFxIbGykj6kaQNkhYVxW6W9JakBel1ZtG2GyWtkLRc0oii+GBJC9O2uyUpxQ+W9FiKz5bUb5/P3szMLEealJQl1Uh6IiXZ9ZJ+IalmL8UmAyNLxO+MiEHp9Uw6/kBgLHBcKnOvpMq0/33ABKB/ejUcczzwdkQcDdwJ3NaUczEzM8urpj5m88fAdArrKvcBnkqxPYqI3wObmnj80cCjEbEtIl4HVgBDJfUGukXES+m52w8B5xSVmZI+TwOGNfSizczM2qKmJuXqiPhxRNSl12Sgupl1fknSq2l4u3uK9QHeLNpndYr1SZ93j+9SJiLqgHeAw5rZJjMzs1bX1KS8UdIlkirT6xLgL82o7z4KS0AOAtYCt6d4qR5uNBJvrMwHSJogaa6kubW1tfvUYDMzs3JpalL+InABsI5CMh0DfGFfK4uI9RFRHxE7gR/y/gNIVgN9i3atAdakeE2J+C5lJFUBh7CH4fKIuD8ihkTEkOrq5nbwzczMstXUpPxtYFxEVEdETwpJ+uZ9rSxdI27wOQpLQkLhevXYNKP6SAoTuuZExFpgi6RT0vXiy4Ani8qMS5/HAC94vWczM2vLmnqf8okR8XbDl4jYJOnkxgpI+hlwGnC4pNXAt4DTJA2iMMy8CrgyHW+xpKnAEgr3QU+MiPp0qKsozOTuBDybXgAPAg9LWkGhhzy2iediZmaWS01NyhWSujckZkk99lY2Ii4qEX6wkf0nAZNKxOcCx5eIvwecv5d2m5mZtRlNTcq3Ay9Kmkahl3sBJRKomZmZNV9TV4l6SNJc4HQKs57PjYglmbbMzMysnWnyKlEpCTsRm5mZZaSps6/NzMwsY07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjmRWVKW9CNJGyQtKor1kDRD0mvpvXvRthslrZC0XNKIovhgSQvTtrslKcUPlvRYis+W1C+rczEzMyuHLHvKk4GRu8VuAGZGRH9gZvqOpIHAWOC4VOZeSZWpzH3ABKB/ejUcczzwdkQcDdwJ3JbZmZiZmZVBZkk5In4PbNotPBqYkj5PAc4pij8aEdsi4nVgBTBUUm+gW0S8FBEBPLRbmYZjTQOGNfSizczM2qJyX1PuFRFrAdJ7zxTvA7xZtN/qFOuTPu8e36VMRNQB7wCHlapU0gRJcyXNra2tbaFTMTMza1lVrd2ApFQPNxqJN1bmg8GI+4H7AYYMGVJyH7P9Mejfb97jtk/8U/naYWZtW7mT8npJvSNibRqa3pDiq4G+RfvVAGtSvKZEvLjMaklVwCF8cLjc7IDkXwLMDkzlHr6eDoxLn8cBTxbFx6YZ1UdSmNA1Jw1xb5F0SrpefNluZRqONQZ4IV13NjMza5My6ylL+hlwGnC4pNXAt4DvAFMljQfeAM4HiIjFkqYCS4A6YGJE1KdDXUVhJncn4Nn0AngQeFjSCgo95LFZnYuZmVk5ZJaUI+KiPWwatof9JwGTSsTnAseXiL9HSupmZmYHgrxM9Mqdxq7ZQdu/bnegn5+ZWVvkx2yamZnlhJOymZlZTnj42g5IvmXIzNoi95TNzMxywknZzMwsJzx8bWXh4WQzs71zUs4J36JkZlnw/y1ti4evzczMcsI9ZTNr19yTtDxxUjazvfKcALPy8PC1mZlZTrinbGa5cyD3zD1cbo1xT9nMzCwnnJTNzMxywknZzMwsJ5yUzczMcsJJ2czMLCeclM3MzHLCSdnMzCwnnJTNzMxywknZzMwsJ5yUzczMcsJJ2czMLCdaJSlLWiVpoaQFkuamWA9JMyS9lt67F+1/o6QVkpZLGlEUH5yOs0LS3ZLUGudjZmbWElqzp/wvETEoIoak7zcAMyOiPzAzfUfSQGAscBwwErhXUmUqcx8wAeifXiPL2H4zM7MWlafh69HAlPR5CnBOUfzRiNgWEa8DK4ChknoD3SLipYgI4KGiMmZmZm1OayXlAJ6TNE/ShBTrFRFrAdJ7zxTvA7xZVHZ1ivVJn3ePf4CkCZLmSppbW1vbgqdhZmbWclprPeVTI2KNpJ7ADEnLGtm31HXiaCT+wWDE/cD9AEOGDCm5j5mZWWtrlZ5yRKxJ7xuAJ4ChwPo0JE1635B2Xw30LSpeA6xJ8ZoScTMzszap7ElZ0ockdW34DJwBLAKmA+PSbuOAJ9Pn6cBYSQdLOpLChK45aYh7i6RT0qzry4rKmJmZtTmtMXzdC3gi3b1UBfw0In4t6b+AqZLGA28A5wNExGJJU4ElQB0wMSLq07GuAiYDnYBn08vMzKxNKntSjog/AyeViP8FGLaHMpOASSXic4HjW7qNZmZmrSFPt0SZmZm1a07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE07KZmZmOeGkbGZmlhNOymZmZjnhpGxmZpYTTspmZmY54aRsZmaWE20+KUsaKWm5pBWSbmjt9piZmTVXm07KkiqB7wOfAQYCF0ka2LqtMjMza542nZSBocCKiPhzRGwHHgVGt3KbzMzMmkUR0dptaDZJY4CREXF5+n4p8L8i4ku77TcBmJC+HgMsb0Z1hwMb96O5rs/1HQh1ub72W98/RER1SzfGdlXV2g3YTyoR+8BvGRFxP3D/flUkzY2IIftzDNfn+tp6Xa7P9Vm22vrw9Wqgb9H3GmBNK7XFzMxsv7T1pPxfQH9JR0o6CBgLTG/lNpmZmTVLmx6+jog6SV8CfgNUAj+KiMUZVbdfw9+uz/UdIHW5PtdnGWrTE73MzMwOJG19+NrMzOyA4aRsZmaWE07KeyHpR5I2SFpUhrr6SvqtpKWSFku6OuP6OkqaI+mPqb5/y7K+onorJc2X9Ksy1LVK0kJJCyTNLUN9h0qaJmlZ+nv8pwzrOiadV8Nrs6Rrsqov1fnV9G9lkaSfSeqYcX1Xp7oWZ3FupX6+JfWQNEPSa+m9e8b1nZ/Ob6ekFr1VaQ/1/Uf69/mqpCckHdqSddr+cVLeu8nAyDLVVQd8LSKOBU4BJmb82NBtwOkRcRIwCBgp6ZQM62twNbC0DPU0+JeIGFSmezPvAn4dEQOAk8jwPCNieTqvQcBgYCvwRFb1SeoDfAUYEhHHU5hcOTbD+o4HrqDw5L6TgFGS+rdwNZP54M/3DcDMiOgPzEzfs6xvEXAu8PsWrKex+mYAx0fEicCfgBszqNeayUl5LyLi98CmMtW1NiJeSZ+3UPgPvU+G9UVE/C197ZBemc78k1QDfBZ4IMt6WoOkbsAngQcBImJ7RPy1TNUPA1ZGxH9nXE8V0ElSFdCZbJ8LcCzwckRsjYg64D+Bz7VkBXv4+R4NTEmfpwDnZFlfRCyNiOY8ZbC59T2X/jwBXqbwfAfLCSflnJLUDzgZmJ1xPZWSFgAbgBkRkWl9wP8Dvg7szLieBgE8J2leetxqlj4K1AI/TsPzD0j6UMZ1NhgL/CzLCiLiLeC7wBvAWuCdiHguwyoXAZ+UdJikzsCZ7PqwoKz0ioi1UPhFGehZhjpbyxeBZ1u7EfY+J+UcktQF+AVwTURszrKuiKhPw581wNA0ZJgJSaOADRExL6s6Sjg1Ij5GYSWxiZI+mWFdVcDHgPsi4mTgXVp26LOk9OCcs4GfZ1xPdwq9yCOBDwMfknRJVvVFxFLgNgrDrb8G/kjhEo+1AEn/l8Kf5yOt3RZ7n5NyzkjqQCEhPxIRj5er3jTM+juyvX5+KnC2pFUUVvQ6XdJPMqyPiFiT3jdQuN46NMPqVgOri0YbplFI0ln7DPBKRKzPuJ7hwOsRURsRO4DHgX/OssKIeDAiPhYRn6QwDPtalvUl6yX1BkjvG8pQZ1lJGgeMAi4OP6wiV5yUc0SSKFyPXBoRd5ShvuqGmZeSOlH4T3dZVvVFxI0RURMR/SgMt74QEZn1tCR9SFLXhs/AGRSGRDMREeuANyUdk0LDgCVZ1VfkIjIeuk7eAE6R1Dn9Wx1GxhP2JPVM7x+hMBmqHOc5HRiXPo8DnixDnWUjaSRwPXB2RGxt7fbYrtr0YzbLQdLPgNOAwyWtBr4VEQ9mVN2pwKXAwnSdF+CmiHgmo/p6A1MkVVL4BW1qRGR+m1IZ9QKeKOQPqoCfRsSvM67zy8AjaUj5z8AXsqwsXWv9NHBllvUARMRsSdOAVygMe84n+0c2/kLSYcAOYGJEvN2SBy/18w18B5gqaTyFX0TOz7i+TcA9QDXwtKQFETEiw/puBA4GZqSfjZcj4v+0RH22//yYTTMzs5zw8LWZmVlOOCmbmZnlhJOymZlZTjgpm5mZ5YSTspmZWU44KZu1MEkh6eGi71WSapu7KlZaeepfi76fVo4Vtsys/JyUzVreu8Dx6YEsULiP+K39ON6hwL/ubScza/uclM2y8SyF1bBgtydupfV6f5nWs31Z0okpfnNa//Z3kv4s6SupyHeAo9Kayf+RYl30/rrNj6QnbJlZG+ekbJaNR4GxkjoCJ7Lral//BsxP69neBDxUtG0AMILCM7q/lZ6FfgOFZRkHRcR1ab+TgWuAgRRWpzo1w3MxszJxUjbLQES8CvSj0Eve/TGp/xt4OO33AnCYpEPStqcjYltEbKSwEEKvPVQxJyJWR8ROYEGqy8zaOD/72iw70ymsP3wacFhRvNRQc8PzbrcVxerZ889oU/czszbEPWWz7PwIuCUiFu4W/z1wMRRmUgMb97Ju9hagaxYNNLN88W/XZhmJiNXAXSU23Qz8WNKrwFbeXyZwT8f5i6RZkhZRmED2dEu31czywatEmZmZ5YSHr83MzHLCSdnMzCwnnJTNzMxywknZzMwsJ5yUzczMcsJJ2czMLCeclM3MzHLi/wNDXywy1BuCaQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Month',data=df,hue='Reason',palette='viridis')\n",
    "#To relocate the legend\n",
    "plt.legend(bbox_to_anchor=(1.05,1),loc=2,borderaxespad=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "b2ad10f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "byMonth = df.groupby('Month').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "9272d86e",
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>55294</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>62312</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "      <td>62336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>48922</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>55405</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "      <td>55427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>53252</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>60001</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "      <td>60027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>47349</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>53655</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "      <td>53671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>50354</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>57474</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "      <td>57509</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat    lng   desc    zip  title  timeStamp    twp   addr      e  \\\n",
       "Month                                                                      \n",
       "1      62336  62336  62336  55294  62336      62336  62312  62336  62336   \n",
       "2      55427  55427  55427  48922  55427      55427  55405  55427  55427   \n",
       "3      60027  60027  60027  53252  60027      60027  60001  60027  60027   \n",
       "4      53671  53671  53671  47349  53671      53671  53655  53671  53671   \n",
       "5      57509  57509  57509  50354  57509      57509  57474  57509  57509   \n",
       "\n",
       "       Reason   Hour  Day of Week  \n",
       "Month                              \n",
       "1       62336  62336        62336  \n",
       "2       55427  55427        55427  \n",
       "3       60027  60027        60027  \n",
       "4       53671  53671        53671  \n",
       "5       57509  57509        57509  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "byMonth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "301d0b47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Month'>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "byMonth['lat'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51ab3190",
   "metadata": {},
   "source": [
    "#### Create seaborn's lmplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "08581261",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x22c0374d5b0>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='Month',y='twp',data=byMonth.reset_index())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "cab74897",
   "metadata": {},
   "outputs": [],
   "source": [
    "t = df['timeStamp'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "efd5a174",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Date'] = df['timeStamp'].apply(lambda t:t.date())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1896d79c",
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40.297876</td>\n",
       "      <td>-75.581294</td>\n",
       "      <td>REINDEER CT &amp; DEAD END;  NEW HANOVER; Station ...</td>\n",
       "      <td>19525.0</td>\n",
       "      <td>EMS: BACK PAINS/INJURY</td>\n",
       "      <td>2015-12-10 17:10:00</td>\n",
       "      <td>NEW HANOVER</td>\n",
       "      <td>REINDEER CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>40.258061</td>\n",
       "      <td>-75.264680</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN;  HATFIELD TOWNSHIP...</td>\n",
       "      <td>19446.0</td>\n",
       "      <td>EMS: DIABETIC EMERGENCY</td>\n",
       "      <td>2015-12-10 17:29:00</td>\n",
       "      <td>HATFIELD TOWNSHIP</td>\n",
       "      <td>BRIAR PATH &amp; WHITEMARSH LN</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.121182</td>\n",
       "      <td>-75.351975</td>\n",
       "      <td>HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>Fire: GAS-ODOR/LEAK</td>\n",
       "      <td>2015-12-10 14:39:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>HAWS AVE</td>\n",
       "      <td>1</td>\n",
       "      <td>Fire</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40.116153</td>\n",
       "      <td>-75.343513</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST;  NORRISTOWN; Station 308A;...</td>\n",
       "      <td>19401.0</td>\n",
       "      <td>EMS: CARDIAC EMERGENCY</td>\n",
       "      <td>2015-12-10 16:47:00</td>\n",
       "      <td>NORRISTOWN</td>\n",
       "      <td>AIRY ST &amp; SWEDE ST</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.251492</td>\n",
       "      <td>-75.603350</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END;  LOWER POTTSGROVE; S...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EMS: DIZZINESS</td>\n",
       "      <td>2015-12-10 16:56:00</td>\n",
       "      <td>LOWER POTTSGROVE</td>\n",
       "      <td>CHERRYWOOD CT &amp; DEAD END</td>\n",
       "      <td>1</td>\n",
       "      <td>EMS</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>Thu</td>\n",
       "      <td>2015-12-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lat        lng                                               desc  \\\n",
       "0  40.297876 -75.581294  REINDEER CT & DEAD END;  NEW HANOVER; Station ...   \n",
       "1  40.258061 -75.264680  BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP...   \n",
       "2  40.121182 -75.351975  HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-St...   \n",
       "3  40.116153 -75.343513  AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A;...   \n",
       "4  40.251492 -75.603350  CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; S...   \n",
       "\n",
       "       zip                    title           timeStamp                twp  \\\n",
       "0  19525.0   EMS: BACK PAINS/INJURY 2015-12-10 17:10:00        NEW HANOVER   \n",
       "1  19446.0  EMS: DIABETIC EMERGENCY 2015-12-10 17:29:00  HATFIELD TOWNSHIP   \n",
       "2  19401.0      Fire: GAS-ODOR/LEAK 2015-12-10 14:39:00         NORRISTOWN   \n",
       "3  19401.0   EMS: CARDIAC EMERGENCY 2015-12-10 16:47:00         NORRISTOWN   \n",
       "4      NaN           EMS: DIZZINESS 2015-12-10 16:56:00   LOWER POTTSGROVE   \n",
       "\n",
       "                         addr  e Reason  Hour  Month Day of Week        Date  \n",
       "0      REINDEER CT & DEAD END  1    EMS    17     12         Thu  2015-12-10  \n",
       "1  BRIAR PATH & WHITEMARSH LN  1    EMS    17     12         Thu  2015-12-10  \n",
       "2                    HAWS AVE  1   Fire    14     12         Thu  2015-12-10  \n",
       "3          AIRY ST & SWEDE ST  1    EMS    16     12         Thu  2015-12-10  \n",
       "4    CHERRYWOOD CT & DEAD END  1    EMS    16     12         Thu  2015-12-10  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "10d2520e",
   "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>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>desc</th>\n",
       "      <th>zip</th>\n",
       "      <th>title</th>\n",
       "      <th>timeStamp</th>\n",
       "      <th>twp</th>\n",
       "      <th>addr</th>\n",
       "      <th>e</th>\n",
       "      <th>Reason</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day of Week</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-12-10</th>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>100</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-11</th>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>332</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-12</th>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>334</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "      <td>402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-13</th>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>279</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14</th>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>386</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>443</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            lat  lng  desc  zip  title  timeStamp  twp  addr    e  Reason  \\\n",
       "Date                                                                        \n",
       "2015-12-10  114  114   114  100    114        114  114   114  114     114   \n",
       "2015-12-11  391  391   391  332    391        391  391   391  391     391   \n",
       "2015-12-12  402  402   402  334    402        402  402   402  402     402   \n",
       "2015-12-13  316  316   316  279    316        316  316   316  316     316   \n",
       "2015-12-14  444  444   444  386    444        444  443   444  444     444   \n",
       "\n",
       "            Hour  Month  Day of Week  \n",
       "Date                                  \n",
       "2015-12-10   114    114          114  \n",
       "2015-12-11   391    391          391  \n",
       "2015-12-12   402    402          402  \n",
       "2015-12-13   316    316          316  \n",
       "2015-12-14   444    444          444  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Date').count().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "3ba976a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby('Date').count()['lat'].plot(figsize=(14,3))\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "0168379f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fCOBj8+ePAVxkuf0LKWW1lHIngG0Ahh+Bv09ERHTMUIuCsSNEADPoRNT6hLlMHM9HTdPcAF0C+E0IsVwIcZN5Wzsp5QEAMP9PN2/PALDH8ty95m0+hBA3CSGWCSGW5eXlNXMTiYiI2i5m0ImIiNoORzOff5KUcr8QIh3ANCFEfROlhZ/b/PYmpJTvAngXAIYNG8YeBxERUR1UI8lF4gjgQA0RtT7hL+qjRmtWBl1Kud/8PxfA9zBK1nOEEB0AwPw/13z4XgCdLE/PBLC/OX+fiIjoWKcz6K27GRQgPBUVrbsdRHTsYrvUPE0O0IUQMUKIOPUzgDMArAPwE4BrzYddC+BH8+efAEwQQkQIIboC6AlgSVP//rFCcAiKiIjqoRcFY0RGYIeYiFqfm+1RszSnxL0dgO/NANIB4HMp5VQhxFIAXwkhbgCwG8BlACClXC+E+ArABgBOALdLKV3N2noiIqJjHTOmZMH9gIham5trozRLkwN0KeUOAIP83F4AYHwdz3kKwFNN/ZvHIu7YRERUH6n/Z3tBnswVC/CIqLXw6iLNcyQus0YtSO/g3MOJiMgPNZDrdvveRscePWDDXYDaiKpaFtwGGzdXLW0WBugBzskdnIiI6uEvg+5i23HsUgM2jNCpDZi0Zj/6PDIVW3NKW3tT6DCwCWoeBugBjp0sIqLWV1XrQmVNYGZxVBxmbS44uHvskl7/EwWzX9fnAAA2HChp5S3xr6iiBhPn7mDVkhc3l3FvFgboAa7WxT2biKi1jX52Fvo+OrW1N8Mv1UpYB3SZPT12SUbo1IaoUumQAF1U4cHv1+LJyRuxNPtQa29KQJF6DjpPRE3BAD3AuayTComIqFXkl1W39ibUSXWErFlzZtCPXfqye628HUQtQQ02BmqAXlRRCwCodbG/bsUmqHkYoAc4drKIiKg+qpVwWjqIXKDn2OWZ8sB9gIKfJ0Bv5Q2hw8Ipus3DAD3AOVniTkRE9TGbCWuHiJ2jYxdXcae2RJ3KRIBm0Mk/XoWqeRigBzhm0ImIqD6qpNlaYskA/djlWZuJ+wAFP88c9FbekAYwELXT5yF+Lk3CAD3AOTmnhYiI6iH9ZdDZKzpm6Tno3AWoDVCZWGbQgwun2DQPA/QAxww6ERHVR3WErFf94PSoYxczV9SWuP0MQAYiVqzYuVnJ0ywM0ANcoJ+QiIiodalArMa6SByjs2OWvrxRG9oHvliyGwu25bf2ZgSU3NIqnPjvGdiaU9ram3JEufVVKgK7opT9dTu2Qc3DAD3AqRJ37uhERIGvqKIGszfnHtW/qVqH6lqXvo3VV8cuzxz0tuP+79biqomLW3szAspv63NwsKQKH8zf2dqbckT5m8ITiFi1ZMcriTQPA/QAMu7F2Zjw7kLbbaqTxc4WEVHg+8uXq3Ddh0uP6nXT/WbQ2WYcs7iK+7HhWJmS7W8KTyAK9Az/0aZL3AP7awtYDNADyI68cizaUWi7TY0YNmdkLq+0+qh2FomI2qqGyoZ3F1YAAHJLjuY519imaqdlFXf2io5ZvA76sUHAiNDb+tes+sGuAA+AA30A4WjTl1lr5e0IVgzQA5w64JtT2nPCU9Mx7MnpLbVJRETHrIY6YfGRYQCAgyWVR2NzAPhfFIzllm3fofIa3PbZchRX1Npu16u4t8ZGEbUwdV4L9AC4llddslGD2azmahoG6AFOjRjWBtDIYY3TzRMREbV5ew9V4ECxPdBuqIwxIcoI0A8UVx2x7fLmr/vD7Gnb987vO/DL2oP4dFG27XadQW+jHWOXW+KXtQfa1CJ4TaFK3Nv6x6DOZYE6B119DxwUtVNVXGyLmoYB+lGQV1rd5OuZO92Bd2Ia8NivOPX52a29GXQU/LR6P5ZlFzb8QKI2aPSzszDy6Zm2QKfWWf+5OCYiFABwoOgoBuh+OkBct6TtqzGnNEQ4Qv3f30YH0t+ftwO3fbYCk9YcaO1NaZTC8hpc9vYCn8G+ltLWL2Pl0nPQA3t/DqREWiDQl8dr27vnEdPkAF0I0UkIMUsIsVEIsV4Icbd5+z+FEPuEEKvMf+dYnvOAEGKbEGKzEOLMlngDga6yxoUTnpqOx35a36TnqxG5NXuLj/rKwHWpcbmxr+jolW9S63lu6ia8N3fHUft7ew9VYFtu/ZeMybp/Ml6fsfUobVFgK6qowdtzth/zmaQjzdrxaqgTVlVr3F9UWXNEt8nKbwY9AAL0nJIqPP7z+iYPUFP9alzGqv3hDntXTp0Papxt43P33pd35pcDAIoqa/09POB8u3wvlmYfwsS5jVttfdbmXPaxLAL9Ouiq+WUG3c7NEvdmaU4G3Qngb1LKvgBOBHC7EKKfed/LUsrB5r9fAMC8bwKA/gDOAvCmEML/sG8bUlJlNCC/rK1/pLeuDrY1C/LOnKMXKBEBQFm1E4Xl9QcauaVVDQbVjTX62Vk47aXf67xfnehfnLYFC7cXNLkTU1xZ2yaC2od+WIdnpmzCkp2scjiSrHMfG+qElVc7zf+N4Gnt3mKMe3G2bguOBH+7ciBk0B/+YR0+nJ+NuUF2/eqiihrc8fkKn7ndgUYF4D4Buvl/oGccvc3YmIOr31/sc272HhRTg2BRYcHRhQwNMWqgGztQdf2HS3Hua3OP5CYFFXeQXM0o2I63I42LVTZPkwN0KeUBKeUK8+dSABsBZNTzlAsBfCGlrJZS7gSwDcDwpv79YFFsjvCGhtT/Ude1+IV1vqMj9Bi5pgYFjIpqV4MB+vCnZtQbVLekKqfnOs9XvrcI41+cfdivUV7txKDHf8PjP29owS1rHYVlxncT6B2XYFdryUQ21AmrqDH20TIzUH9p2mbsyCtvkakid/5vJb5dvtfn9kDNoKvPKhC25XB8OD8bk9YcwIcLAvv60ipAd4TY+wY6cyUbHxQGgnu/WYO5W/OxJafMdrv3oFhVrXGMBcsgq+q7NeY8rbLERY0YHFLH1+F+DMWVtfhs8a6g+fzU/hzoGepAX8TuaHMH4BTdYNIic9CFEFkAhgBYbN50hxBijRDiAyFEknlbBoA9lqftRR0BvRDiJiHEMiHEsry8vJbYxFajAnTvBtRbtSXwsLKe0PceajhbWFRRg88W7wqqRpkCU43TjRqXu8EA/WhSmZO6fm+MvFLj8lcfLchuiU1qVarhC5J+VtCyzuVtKEAvr1EZdON/NTjbEp3Ln1fvx9++Xu1zu7+OdiBcZi3EXD3pSPTPbv3vcjw56cgMsqmMdKBnxNRl9bw7wNavvrnz0J+avAF//XJVs16jsQZmJgAAFm63V1x4fw8qQFfHWKBTGfTGZBLr6gv609QpDI/9uA4Pfb8Oy3cdatLzm8LpcuOV6Vt0n9iq1uXGWa/8jt/WH/T7XH254Raa4/3xgmzM2tTyU0bZ77bjInHN0+wAXQgRC+BbAH+RUpYAeAtAdwCDARwA8KJ6qJ+n+/3WpJTvSimHSSmHpaWlNXcTW1WJzqDXH6BbAw1rY1Rd60K/DvH400ldkVPS8KJDP67aj4e+X4cXftvSxC2mQPPdir041ApBcoUZaBRV1h71EdC6RvZVx6w5rB2EYMvseVMNYFmQdFRbWklVLd6avf2If483frxM/9xQFqyi2h48qMHZ5lY5HG62KxCqKlSzdyTOH1PWHcTEeUcmwx1mZjwDfQ632j7vIFz6eUxTvTd3J75fua9Zr9FYyTHhAID9XldA8M5Mqv5SeU3z24OGOF1uPPHzhmYt8KYG5xqTYT2cQWf1eod7dBWY/YnSo9huTN+Yi1emb8UzUzb63Pf7ljxsOliKF+vot5ZWGdvZUue0x35aj+s/WtoirwVYLgMXAOfcQKI+l5Y4/x8qr8GfPlqKgrLqZr9WsGhWgC6ECIMRnH8mpfwOAKSUOVJKl5TSDeA9eMrY9wLoZHl6JoD9zfn7wUBn0BsoT7cGHtafy6qdiI1wICU2HBU1LlQ2skFasdsYGbV26lqinCmQSqKe+HkDFu8oOGKv/+miXa2+gnlOSRXu+Wo1xr8056j/bRX0SQkcqvA/QNASAbM/1XV0Klvi71kXFjqaHRQA2LC/BKe9NMdvFqEpVMMXLJmkppi9ObfORvnpXzbh2ambMOMIZEOsQf/afcX6Z39ZVSkl/jNrG7bmlOoMujp+1Lm/udnY+jru/k7L/gYtFu0oOOyss8stMXHujiYde8LMoB9OVjAQhIWqDHrgtHf+qMD8uamb8cKvm/Xttgx6MwL0ljxP/bhqnz5f7SmsQNb9kzHFa20etY+pqq3NB0tx3zdrbPtejdOtF4lTg8hH0qo9Rfhg/k784+s1dT5GSlnvIKma9tKYQOVwjjP13R5ut0zt30ezZFztq/5K95dmG/3VgZkJWLAtH5e9vcBSvi+Rb57/AzVDrTP85vbtLqjAfi7yZ5tq01yfLNyFmZty20TlY2M1ZxV3AeB9ABullC9Zbu9gedjFANaZP/8EYIIQIkII0RVATwBLmvr3g0VxIzPo1oDE2hGrqHEhOiIUqbHGyHJBef2jR5W19obAOuJYV9BzOALlsi1l1U58MH8nrnh3UbNex+ly48aPl/oN9B/5YR3+8PbCZr3+4ZBSYuq6A7ZGXFVgNKXM/GBxFSa8uxC5pU273FOFZTCorgz+QUumoyXLQesKOCsPo/Oy6WAJsu6f7PPdWjudJS28CrDLLXH8v6bhGz/zhAFjPvK23LIWG1hyt/EMelWtC9d9uLTObId63y3dUZ+/LR/Ld/sv//TXqS2rduL5Xzfj4jcX6GyPWiROdYarmzAdw6q8nvfo7zJL/gKzCe8uwsR5Ow/rWP1x1T48OXkjXp95+FdOUK3e3V+sOmKDeRU1Tjw7dVOLvr7+zlo4g+42r9/dUoGG2r6yaifemLXNck/LtPvb88oaflAj/LR6H+7+YhUmzt2BHXll+HKpMdvxO6/MvGpziswB4Ts+X4Evl+3B5oOeRUi/Wb4XB81qQnWMtZTf1h/EjI05ttvUIFN9bfAbM7dhwGO/6u32ptqtxhx3/vbj2ZtzcfJzM30GTPQaD1JCSolPF+1q1MKGqqrnaFaIVJrnL3+DFMXmFS8qa12456vVWJp9CPvMKZ2l1U69Dx/JqqCqWheenbqpSW2pWsRQbd+Y52dh1DMz/T52xsacRifagp27BUvc1Wuo4/FY0JwM+kkArgYwzuuSas8JIdYKIdYAGAvgrwAgpVwP4CsAGwBMBXC7lLLN76XqhBrSwE5VVwa9vNqJmAgHUmIiAAAFZfUHauq56kRhPQE3t4NovL7nNVpzNLOlRicPllRh+sZc3Pzf5S3yes0xac0B3PLfFfjAUrZpbSwaU71Q43Rj+oYcSCnx9pztWLSjEN+vaLg8sbLGZesEef/tgvIa1Djd+Hzxbtv3nm/JbK7eU9Tojv/YF2bj9s9X1Hl/XR2vwyn/W7DNCIK9r6Bg7eS0VIZIKamsRWF5DR77cZ3f+9Vx2VILPqrOTnMC9ClrD2DU0zMCcr6tel+bDvq/SoDqaNa6JNxuqff9piqurEVVrQt/nLgYl9UxOOdvHqTaj9T2ZiZFobzGiZKqWl0e3NjvyOly45ZPl2PVniLb7RX1BCP+3vKB4roH5vwNuJVXO/HVsj0+n5865hpqe/yxtnuHc5nQgrJqLN9Vd/WSdV/9z6xteGv2dh30tQR1XLXEMeF0uXU1w8xNubjtsxV4beY2v4/NL6vGS9O24P5v687WTlqzH0vNyi7v4PtgcRWklLb9oTnvYZ/Xuje15oD2mr1Fh/U6qh+yNLsQ416cowcTQr36RSpwOVRh7zdZB6c+WZiN4zIT0CEhssUrh276dDlusExnATyDxfUNAn5tDsiq0vGXpm3BF0t26/srvapq6uOvjbvuw6XYU1iJ3QUVttvVd1vjdGPxzkI88sM6PDm54QoZNQBVVn30rlKQb54//AVr6vxZUlkLtUt8u8L4TPNLPX2MI5nx/9+S3Xhr9na89/vhXy3JM4Wh/mNt3b5i3PDxMvyrEd9RW9CSl8dT7dKxE543bxX3eVJKIaU8znpJNSnl1VLKgebtF0gpD1ie85SUsruUsreUckrLvIXAUu102RoNVc7T0Oi+taG1lgOWV7sQEx6KZDODPq+By9Wok3uFuQ01dbxuU1VbBxKaMfr60m+bfcrb6uN2S/xr0gZszTE66t4dh6ZSo+Le38+RntMqpdTvxXtbdhWW69usgWq1Lmere9vu+3YNbvxkGTYcKNGZ87jIMJ/n5JVW2/aNWz9bjjNf+R17Cit0I2MNCArLa/DJwmw8+P1afLlsj+125Q9vL8SzUzY18M4NO/PLMXlN3d9/XR2Z6sPIktW1cm6xJctx6VsLGv16jaEupVXXgJxqqEJDQpBbWmUr3T7cwPJQeQ3W7y8B0LwA/bGf1mN/cZVePC+QlFWpaRb+PxuH5fJFE+ftwI2fLMOv63P8PhYAflq9H5e/sxB7Civ83j/o8d9w8Zv17xPTNuTi88W7bbd5l20O7ZKE8mon7vx8pee9NPI72nOoElPXH8RF/5lvu4xgRW3dz/fX6d1zyP97BDyBhNVTv2zEvd+swWKvS/Z5SvQP/5xoPQzUMbE9rwznvja33kskXvfhUlz61sI6O7zWNlat+O2vSs3tlnj6l43YVVDuc1999NzuRrZx//h6NT5dmI0dZsZ5wfZ8ZJtl2Cc8NR3XfmgUC6p9YOo6/+e+/5u4GK/N2Iovlu7xGQCvdrqwYFs+7vh8JS57eyG+XrbHZ6DlxKdnYNqGnCYvEvfkpA146bfN+M+sbViztwh3/s+z/9a63MjOL8f0jbn4yxerGv2a2/PKsPGA2W4X2QeNvC9uo9ph9b7UvmcdHNp0sBTj+7RDTITDVuV1pKjvrL757uq8rgYYXpuxFfd/t1bfrzLoW3PKbPtURY0TWfdPxvcr9+rXqKqnn+bdh1N9gmqnW1c7FJTXoLzaib31HP/qc1XVPkeDGswvqfT9m+r8ad2e12caU4as7dLhZNDnbc3HA5bvQPHXlqzbV6yv6tKUhejUeaqhAF1NFfQeaGmrVD+6Od3plbsPIev+ydhhnk8bSna2JS2yijt5PDtlM/o/9is2mB3nHF2KVf+J0Bb4WkZQy2uMDHparJFBf/7XzahxurG7oAILLMF6Va0LK3cf0g2calSsjXNLlOtZt605ZTqvzdyGWz8zMqjbckvxh7cW+M3q7Mwvh5QSeWXVeH/eTpz+8u/YX1SpO3cNzBxokGo0vD8bayN5uNmCxnhj5jac/vLvtqy1Wjm4otrl8z0Cxj5U63Kj6wO/4D9mBuK/i3Yh6/7JKK6oRaklW1dZ49IN24Pfr8U5r83Tr5NbWoWTnpmJ3o9MweIdBXC63Ji92bhawsnPzcLxT0xDZY3LJ4OuysGt1QveZX8T5+20VQD405jBj7rKeQ+nxN2zgrRXgG7Jmlc73S26gJV+7Tr2S92QO90Y/tQMjHluFgBjTma/R389rH1tyjrPirdl9XS0lmYXwulyo9blxj1frsLGAyW2+6PDjWsJW4PMqlpXs7OHbrfEP39aj5mb6g6YG1KqA3T/96uOZlWtC3O3GudDda4trqjFhW/Mw7ZczzH27fK9WLKzUGeK/XXWvD8f5bS+7QAAb8/Zjge/t3f8rJ+dEECvdnFwS2DOFs9VSBqT7Xt26iaMfWG2/v0GS2l/feW8/j6fPYV1B8D+suEqU+VdputZ5K7+/eGt2dux8UAJckuq8N9FxiWcrPuQOqb//vVqrN9fgiU7657mscH8Dno+NAX/W7Lb535rR14FwrERDgDG2iQT3jWqH3bkl+Gd33fgts9WIDu/HA99vxaP/riuwcEwFQg15hhwutz4evlePPLjeox7cQ5Kq2px1XuLceoLs1FSVYtDFbV631TtzZacMox+diZKq2qRW1KFTxZmo7C8xlYp8snCXfq9AcDL07biqomL9e//+GYNdvsZaJqxMdc2iPrDyv24/bMV+G39Qfz969V4Y+ZW2/tfll2InfnlqHG6MXHeTrw2cxue/3WzT4VTRY1LF87XdYUAf5/r+Bfn6Hmj3ud+73LVCp1BVwG60Sbme61BMbhzImLCQ33WEFm3rxjTNzT9fKNY30epOehaUc/xq46NdfuKcY9lxfuqWhdqnG79vvYVVWLuVs85QbXRf/1yNUY+PQNSSp9kgbVk3XtAQmfQXW6s22ccMzM35WLk0zMw+tlZPq+jVklXbWNJCwToG/aXNGoKnjrn5PlZT0Rn0KtqbQHY3K352G9ZnE8NWlXVuhpMev3f+4vxvyW7bf0Yt1vaBhrV93yLpYKyKQGgGjhoKMPv1AP0jf8bNU43Jq3Zjxs+Woq7v1jZ8BPqIaU8quvVqL6XOoaa4sdVxlJlM811Zprb5w8mDNBbmCo9e/f37ah1ueudK7XpYAmu/WAJyqudtoBQZeHUwRQT7kCn5Gicd5wxvX/hjgKMeX4Wrpq4WJ+kHv5hHS5+cwGyzUyB6rDX2Oa2Ny642ZJTWucBZd3Ops75827EH/x+HZbtOoQlXguy7S6owNgXZuOZKZtsJ5VRz8y0ZcDcbv8d7fq43EbnUZVdeT/dOvhwwRvzsc6ySFRdal1uPPDdWp1Fqc+vG4yGUjVMGw+U6IVvvlu5D30emQrAXlZXUePCFjPr/uF8IwieONcox7rwP/Mw+IlptsfmWkaerUHHil2HUONyQ0pg2a5D2OXVySutduLnNfttn/mr07egxqVOtvbA3dsTkzb4/T5U56PEa99yutw+2aInJ23wuzBYQyXuS3YWIuv+ydiaU+rpTJqNYm5JFbLun4yvltnnhzeU2Zy3NR9Z90+2dZbrYp3S8syUTVjilY1U26I6BOU1LkgpsXhnISprXTojrqggVw34PT1lIxaZ89dVeWJyTLjtM73qvUW47G0jC/zr+oO47O2F+GLpHuzML8d3K/fhQnN/VsdvVLgR2Fg7WX0emYo/msFAfce50+XGg9+vxbZc333+tw0H8dGCbDw7ZbOfZ/p6c/Y23Pixfa55qfkevQdZCsqq8enCbDjMFFxplVOXdKtFAKdtzMHqvcV4bYannFht55acUpz49Ay8PcdTzthQMJYWF277/VHLNIaiSs9nFxPuQFK0/bGAsZ/tKijHVe8tqnPRu7dmb7f9nm8JpOsbEPU+2k7qkVJnlQDgfy0TNUDoPQimPpf6Op8bD5Tg2ambcO0HS3Dft2vw8A/rsDW3zPZaheW12FNYgZW7iwB4OsK3fbYcJ3nN10yICtM/+8uCWY/ZreZ3OnHeDlQ7Xfhg/k4s2lEIt1vqzy+3tBp/+ngpPlu8G58s3KX39RqnG2v3+p7bVbbGuu/vLqjAasu0AymNqi61wJWiOpQAsGq35/Fut7Sdk/ceqsQNHy3D8H/PwKM/rsczUzYiMszTJXti0gaMfXG2533m+J/m4e2HVfYpTW/P2Y7Jaw/gpk+X45vle/HCb1t8Kp/GvjDbthAi4DvAU1XrGbRV+0JheQ3mWQbGej8yFS/9VvfxXlpVa6uq8N6n1f5SVFmLWpcb4eYAnHeA3jM9FlmpMVi/r9gW9J/3+jzc+Im9RN2fqesO1vt5WrO8qr2rq4Lk7FfnIqfE2L77v1trm1ff79GpuOSt+aiscekBpJySajhdbrzw62bd5gPGPrqnsNI2FVFKaRuE8S6z95S4u7DbUnmnAu+s+yfjo/k7sW5fMc5/Yx5u+nQ5DpXX6AGoxq7B4nZLVNa4sH5/se57AMZ3fs5rc/GnRqyIrgZd/C04q9rN0iqnbXB+3f5izNmch6ToMHRMiITLLbG7oAJ9H52Kmz6te1qiddBdrZMzdd0BdHvwF7w9x3OOfWvOdnw0f6etmmfzwdJ6z53+eDLost5K1Spzf3eECLjcEo/8sA7r99fft3xj1jbc8flKzNiUazu3NMXnS3aj/2O/Hvb7ayr1NeSWVDd56pn3FTWOoQQ6A/SWFhdpnIR/WLUfj/64HjnmyaHG5fYpl3ttxlbM2ZKHX9Ye0Cd4wHO982qnG24JREcYGa6nLh4IALYFqL4yR8pVp12d8MtqnJDSfrJQ894OFFfWebCUVtXijJd/x311zIGznpwbE6CXVzvR7YHJ6P3wFD1y7B1kqeCj2unGtA05+GRhNt6avV2XaL3z+w6fAQ7VmXBLo+Tt1Bdm46XfNvud5zhtQw5+Wm0/sV334RL0fGiKreGvqqd8f8ZG43WtgWRxZS2u/3AJdhdUoKCsWmd7nvCzSnJljcsWxOSWqMy9EaCd/epcvOs196mq1j5dorTKiXPNTHjHxCgAnkxGdkGFrVEqr3b6zNNX2754ZyHCQ0PgCBE4VF7jt6Oyek+RrTOQX1aDSWuMz9Daqahr5NxfOeCUdQfR55GptqAIMAZcTnl+tv3v7y3Gk5N9L8fS0D432dzGOVvy9Lw/NWq9wuwsF1fWokNCpH5OXYNR6vN8bYaxONa6/cX4fuVefL2s7rmuqqNR7XTh7Tnbcfk7C23Bs+rkWUv19h6q1I10bom9I3qgpAofLcjGTZ8uQ7XThXfm7MCEdxfhYHEVXppmXJJmcKdE23zlBdsLsDT7EFxuiUnmNIKqWpcOYGtcbpz3+jz8+ZNlqHW5dQZdBW3qnLFkZyEWbM9Hn0em2uYD/7L2AD5dtAuA8T19vng3HvxuLWpdbmTdPxmfLMwGAGzPM/aThGhPsLVgmzHYsaewAg//sBYP/7AWZdVO3PjxMjw3dTOmb8zFtA05eGX6FuwuqNADjd5FDue8NheP/Lhel3WWVjv1/p1fVo2ckiqUmZ97jNkxLiir1h2xX9fnIKekGs9O3aQ7+P5WF7ZKNauYlE8W7tIVUtbnxlgW9bQqrXLi4wW7sGB7AZbsLMRPq/fjqwbmTVs7I95VJfuKKj1VR5bPZ3CnRAzMSMSO/DLUuowKkcd/Xm8bZLz7i1Vwu415+yqLF+Ew9oPCcvvnoIIo7wGMGqcbheU1yC+rxtmvzgVgfE8qiDvj5d9tmfqiihp9dRHA87hf1h7EvqJKzNiYoyuDrAF6XIQDpVW1tnO7v2qrdftK9HkaMK7CoTqieaXV2JHnOW+psvgnJ2/A+W/Mw55CI/jemV+OiXN34Dtz3Y41e4v13zrt5Tm48D/zIaURrJzw1HS8P28nrnzPvlDpwz94Bm6sAflzv272WRfAOigdGhKCqLBQ2/1SGhVcUsp6pwQARoXHsC5JjaqUu+aDJfh59X7b+fS7Ff4XtlQqazztkTo3XvLmfPzf+4tR7XSh/2O/osbprnN+PWBcPs3a9Vi6sxDTN+TgiyW78X9mwiEqLBRSArsKyvUAnPf0m7S4CIzrk44CyzQfK1Ud883yvT6LpBZX1uKW/y63fW9qYFdRz3G7pW7j/E0jqap11VlxYzzH2C8ra13ITDLa7Ilzd+CU52fjjVnbcNtn9iqF9fuLbd/JxgOltgUyP5yfrfuR5dVOfazWON3Yd6gSJ3ZL9tmGxydtwHmvz9OBfm5ptT6mP1qQjbxSY7Dzts+W+12TxeWWGPfibJz72lzc9tkKPP7zBvy4ah+KK2oxyzwmre3PJwuzdabeemk69drFlbU+A/KqSuBQeQ2KKmpx7nEd0C01Brkl1Zi7NR+n9k5HRFgoFu0owGkvzYGUxqXZ/rtol99ttg4CqAD9d3MgyboI4HNTN+OfP2+AlEBWSjQA4LcNOTj5OXv1gTeny42CsmrUutxYvadID3RUO131ThtQfYE9hyowce4OfLpoF+6yTCPxp6WmcwLQ079aavHHhqhjpsbl1utKHC5VReNvXa22ztHaG9CWVNW6bAHfN8v3QEogKiwUlWawFe7wdNzUiOrqvUW2Doman6LmAqrHJUSFITkmHNM2eEpbH/1xPS4f1kl3MneZz5XSyKJaG+ufV+/HlcM74ar3FuOmMd3wwNl9fErMFmw3Av3tufZs4fmvz8OAjAT8b4mnQ+ldbqUXcRACv64/iEU7CtA9LRZuaQTfk1YfwMk902wBUY3TrTtqT/+y0daBeeWKwfpn63sGgGXZh5AcE47C8ho8+uM67Cqo0B2DGX87BZlJUbj87YUYlpWM982S6+TocIzumYpl2YW65HBXvmckcXteGeZvy0eXlBgc8OoMrd5bhFV7inDxm/PxzCUDccUJnbFwewFmbc5D+TercfOYbvqxB4qq8NcvV2FE12Tkl1XjjnE9ccYrc7CnsBILHxiHnXnluuP29C+bdJWFt80HS1FmGZjYke85qcZHhqGgrLrOMtbsggqfEf8tOWVwhAp8vng3zujfDit3F6GwokZ3Vq0qaly2vw14Bo7W7iuGlBJCCFsH1OpQeY3ebwHgjZlb8YJ5jdNvlnv2oVV7iup8DX8Zw4ZK3CPMDm610zMg5nRJHCiutGWzE6LC8Mh5/XDbZytQVu3E54t344SsJPRsFwfA6Kze89VqLHxgnG7MSiqdurT5smHWK0Ya3pmzHU+bc/Ctg1CP/rAOr0wYAsA+sv/Y+f3w+M8bMGXdAV3Gm1NqLPL0+ZLd6JQUrYPLvYcqcd83nkGz816fp//GyT1TjcuPzN+JS4Zm6sdszS3FQvN4DhHCZ8Bm7tZ8nPjvGboKYldBBSat2Y/uabH6MSq7eOlbC/HIef1ww+iuulN59YlddNAgBPQ830d/XI+rhnfWx7W1RFMF9iv3FOG/i4z3fFxmIqZbOk1/NjNgr8/chkfO7atvX7WnCIlRYXh5+hY9oKnek3Vw663Z2/HW7O0YmJEAwBiBL6mqxdAnp8Of8hqnXoW9Pr3MfcNq9uZcDO6UZPv7MREOpMZF+Dz2QHElFmw3zjtbcsrw8nTjeDitXzskRYf5XZ1WlfO9On2rDl4B4IVfN+ONWduQGhuBZQ+fZlvFPSk6DL3bx6LWJZGdX46KGhc+nJ/tk33ZkV+Gb5bvw9tztmP5w6fp6itrG/b2nO14xtynnW5j3Ywe6bEQQuDC/8zHxgMluOf0XvrxqbHhiI/0tGXWku3ckmo9YAQYAYY1+6kW58pMirIFQ1Hhobjrfysxy5yGM6ZXGn63TB2w2mIZbHzsp/XokR7r93FXvrcIP95+kl5Acn9RJa58b5HPQFBBeQ1mbsrFpUMz9flke1459h6qsFU31MW6UJg1c6eoNgwwsmqHKmoxrEsSlu3yDGRc8MZ8nNwzFZsOluIfZ/aucz999+qheOiHdfq5o3uk1rlmzfr9Jbjzfyvxy10n69s+W+w7leD8QR1xzoD2uPWzFaiwBOhOs2ot2+xvXD3Rc0GePu2N4yS/rNpnUEv5vxM747sV+1Ba7fTJeA/vmowlOwuxLbdM7wfen3VYaAh6m39nV2E5EqLCcMoLnqBqT2ElLvjPPBRV1OL6k7Lw2Pn99X1q2on1Nb2nURwsqULPdnF45Md1+nNxuiW6PjAZFwzqiEfP64cqpxuTVjcuo1le7URidBjiIh26OgPw7UNtOliKFMvg3qeLspFfVo3uaTHYnleOxTsL0evhKZj191Pxp4+W6sHyqlo39hdV4cwB7bEtt9x2DHuPK+SXVdv+7rp9xXjkx/UAgEuPz8ShilpcOLijXkhuzd4i/T0PykzALhgDfP07xmNcn3Tbe4wOD8Wj5ms994fjcO83a5AUHYZp95yiA2kpjSA9JsKBf3yzBpcen4FS83LCqs0Y0TUZTpcbc7bkoarWjWFZSVi7rxj7vQa4Hv5hHV6etgWT7hqN5Jhw/O2r1bjt1B62RVgPFFeipKoWP5iVDXUtOPr+dSfg0R/XYb65uKzLLf2WorvcEvd+swbfrdyHy4dl2iryckur/QboOSVVGPHvGRjbOw2Acf5XfQVrP2f25lz0bBeHDDMBA3gyyEqty62/m8OlXqolp/XVx7rv5ZRUITnGd+C6Id7v1V8fcFtuGbqmxhzW1IFgwAx6C5FSYvhT023BTq1LwumWyEqNAWBkDNbuLcaXS40TvgpGt+eWY++hSnRKNg7KN2Ztw5Kdhbj2A6PRs3bcOiVF+WSgDxRX+V0I5vqPlvpkhT6cnw3A6ND+tiEHv64/iGembPKMMpqNV8929o7N2n3FPo2YdXS0pKoWpzw/G5e+tQBLswtx86fL8eH8bFuHaafZAbRmFK1z5byzCzmWwHW+GWjcOLorAGNETjUO1s4MAOQUV+HHlfuxem+xDs4BYwG14opa26XTflq9H52TjZHTf/+yEf/+ZRNu/nQ5/vmzPQueXVCO37fkQUrgvm/XIq+0Wg80bMkpxWbL+9ycU4rvV+7D/d+txQu/bbEF0rM25eEhS4Zlw4G652+9MWsbnp3qWXRti9mwhIYIHKqo8enYdEuN0aPA/kb1z3ltLs54+XdUO904Z2AHJMWEoaiiFqv2FKFHeiy6mvtpamwEvl+5Dyt3H0KIAF6dMNj2OkUVtdiZX4752/Lx8+r9OjMAeObp5pRU2fYPFZwD9o7RRf+Zr3/2HlWPCPM9PfnLoJdW1eoF5zzZ0BrdmSyvduKU52bjA0v1R2RYqK52eXu2MadY7Rfl1U7c89VqAMaJX3UsVHDl7YVfN+PytxfqBtfbrM15KKmqxd++Wm0rIz2+cxIA4N+/bNLHdG5JNZbsLMRD36/DNR8swSzL9b1/sARY1g7YhBM6I8IRgpmb83CjZQXi2Zvz9OMqapw+g06AfYrCS9O24I7PV9rmcFpHvf81aYMtyK92urDN3O8jw0Jt575//rxeZ7/VnEMppc52RTg83+293/iv1nG5pe04vOg/8zFl3UFboOndYbNSn/Vni3fjoe89x9wnfxqOf57fD/82K5KenLQRb8/errOm/nRKjsKJ3VJ8bl+xqwi3fbbcVoYaa1kzxGrZrkPIL6uBEMAWy7z44/81Ta8B4U1AILe0Ci9P32I7x6tVsPPLqjH0X9Ns2eGk6HD0TDeCl625Zfo4VOeZZy4x3vfK3UX42Jwb/PevV2O5eR5Vc9FLq2p1cA4AK3Yfwukv/46Jc3dixe5D+hyjKjnU3/O+Jv35gzqiW1oMvly2x1Z9s+lAKbo9+IvPe777i1XYVVCBQZkJOKNfOxSU1+jgHIAtOLcObAOeTF6K2RHclluGcEcIupnntkRLNcdFb87X56Ir3vUNzgGjIm7mplxbm7U0u9C2toDy3B+O87lNtU1dzPMyABzfOVH/XFheg9vHdkd0eCh+Nqt/TuqRqu9/6fJB6JwcrQeU/3RSV/xxRGffDQUQEiIQb57TOiRE4v6z+/h9nNU5rxmVD9aAwCorJRpRZoVNZa1n0Da/rBqfLNylH6cqAeIjHSitcuK5qZsw7MnpGPFvY1AsOSZct90AcHq/9rj0eM9gotWAjsbA2va8ch1IWhc8U995+3ijCur7FfvwycJsWzDwzNSNuu/jdEm8M2c7lpnbuML8TpIs+4J3u6KO5++9LgMnpTGFYfSzs3DSMzPrPOdbtYuPQGmVE3GRYXUOWFw8JANJ0WF4dcZWHeACRiKiQ0Ikfrj9JNvjd+aX2Y6lrbmlqHG5kZkYpfd9b7ed2h2AUY1QVevCoEzjc/6H5fz70YJs/P3r1ej50BRsPlgKKSV+s7QHiZapO+v3l2Ca5b6CshrbgJAaSDpUUYvft+ShqKJWH3+HKmrx7Yq9+Hn1flz34VI4QgT+clpP299Jj4vU7eKQTkl6LQzjfs93V1Beg5FPz8Tbs3dg0poDOOe1uXrqHwDsL6rCV0v3oKLGhdAQUWeFSbzX91NX4uSxn9bpaQzW4Pzc4zogp6TKZzrky9O24Jr3jb78LD/nebU96pKiE95diMU7CnT1j/cgTl0JjcYINStSGrPgZ0FZtd+pa4fDNtWgjs+zIWFeQbd3gH6wuAqnvTQHT/mpuAx2DNBbyJacsjoX3FABTHFlLc5/Yx7u+3Yt9hdV6kZgd2EF9hRWICMxCuea88ytGZk0y4hqJzOYbB8fibvG9QBgBBj+RvOX7CzUpUYXDu4IwOjctIs3TkKzNuXi5k+X4+05282Fe4r1aHFjytdv+e8KXVq/eEchdhdWYMXuItvliayjldn55Zi9ORd3WFY2fsQSrHpTjV9GYpSe+9fR0pEY3tVTznXdqCzd4L79+w7c61Wif8/pvbCvqBIfLrAvYFZZ68KVw40Oz/xtBYgJt5cY/uPM3rhwcEfsKaywLeC1ak+RHtRwuiQ2Hii1ZYxVRwmA7vgCxoqUB4urcPkwT+fk2pFd8I8ze/u8/2lei92oQYABGQlYv79Ez+VUrhnZBT/fORoAdEn/sodPw+IHx/u8dkJUGJKiw5FfVo0Vuw9haOckfHjdCXjonL66M/nbhhzEhDtw7sAOutT25J5G5/Hl6Vt1YHXLKUbDnxQdhltOMSoJ/vzJMox8eiZqnO5GLzb2jleJv9MlMWtTrq3U3l9W/doPluD2z1dge16ZDjj3FVXqMvviylqfAazIsBDEmZk+FfgWV9biYHEVrnjXs/9uPliqS6sW7fBk4K3HxxuztmFJdqEO+K0mnNAJxZW1eHv2dn3ZGKVdfKTP43NLq2wdojdn+5aLXnJ8hu33qPBQjOyego0HSrBkZ6GeS7zIcq31H1ftr7f01MqaSfuvmfGOM/dta+ej98NT8V/zsdtyy7DVEqD/d9FuPUBSaF6i76MF2fqc569EuTGD36qj/tj5/QB4yt3UcdurXaytmgUwOgk/WzJdJ/dMxXUndUWs+X19uWwPPrYEG1ZXmJUSnZKi/X6/q/YU+WSoYsIdSPOTQZfSCFTG90nXwYKyYvchW6CrhAhg6c5DPrdbFZTX2AZa0uMjdZvzr0kbcMt/7WW0J/dKQ7gjxDZH3NpxVOfsSV5XWVABz8vTt+ASr5Xun710IC4c3FF3yNLiItC/YzwAY8CiX4d4n+32vga2t97t43Dh4Az9mv93Ymfb1IHFD47HCEsbABjtEAA8cE5fHaiM6Zmq24qhnZOw+MHxyEiMqnPhQatR3VMwee0BnGIpeZ29Oddvttk6UGkV7gjBlLs9mer+HRPw8hWD9O9dU2PRJSUGRRW1iIt04JyBHfR9GYlRuMhsuwHjWFdVNdYAU7FW21kHwRqi+h2A0eZdO7ILeqbH4pLjM3XZvfeUq8d+Wu/zOiO6pWBfUSXeNNdSUJUuN4/phj6WfSAlJtzv9gNAalw44iMdyC2p0n/POlCoBhNUoD5jUy4mei1MOmdzHgZlJqBHeixW7y3C01M24Q9vL0ROSZUeuDtUYSzQp96b1TO/bMKzUzeh2mlMAUr3Op4bs1jpExf2x8VDMlBR7UJJZS3iI8P0PjmkcyLuHu8JSO89q7ff9mBrbhn6dYhHTLj93FNZY2/PVMCVkRSls5RCwNavUNUkszbnYvXeYsRGOpAaG24b7LUO9P1x4iK8NWe7bV0M7yosa//urTnbcfX7nkqKvNJqHVSXVhmXnOySYgyUfbZ4F16etlU/tn1CpG3AJjk6XGdOh3RORN8OcbbKnOtGZemfX50wGCHCeE3FGjjP3ZqHvYcqERoi8MJlnkG0qLBQ25SA+Cj7wGpda86oyi9vHRMisaugwnblg10F5Xh1xlZbAsdbQXkNal1uPeC5p7ASV7y7CONenI3KGpctUQUAJz0z06f9aCz1fdR3yUDl7Ffn4rSX5jTp7yhuKfV5KLeJAbr3gpTeCcqNB43PTSU+2xIG6C3EOg+mQ0IkuqXF6N9Vg2Kdf7c5p1TPLdlXVIm1+4rRp3083rhyCBKjw3TJ5xc3nYgz+7f3ea3E6DBdZvvlsj3o0z5OZy9HdkvRAZWad6vKM6udblw3qiviIx260zquTzrmbcvHFe8s0p37TQdLMXHuDizcXuCzoMRTFw/QP9/w0VI89uM6XZaq3GwGatay4tzSalz34VKfEqP3rhlmyd76jv72SI/VQVLHRE8jpjLfAHBq7zTMv38cAPgtfxzZ3ch+eV/rGwAGZiToMqKuaTEY1iVJ3zeiazJO6p6KWpfE9I25OGeg8V387atVeNHsUJdVO7FqzyFbhu0fZ3myF2rhwNgIh+4UZyR6tj0pJtxvh96bmj80MMPT0Vn4wDgdnMRGhiHa0pAPz0pGamwE2sVHYpIZuCvxkcZ0iTV7i1FUUYuxfdKQlRqDP4/ppuckA8b6B47QEL3o1ZDOSRjVPQU/r96PfUWVeOnyQRjcKRGA0SlPMjsHqkO1aEeB3xWj+3eMx6DMBFv5lnfp5tp9xbj+o6Xo9+ivuPr9xXC63D6XgAI8+3heabXubOwurLCVjXuLsmTQAaMzI4RxmSK1Gi4A2zx4a0dm9LMzsWL3IVuFg6oy7mkpqz0uMxGAsbAjAFv2K9Grg3pq7zTkllRj76EK9GoXixFdk/1m9W4c3c3ntuTocD1P87e/jEFchANrLItfqYW0LhmSYQuE+/oJnA6WVOH/TuyMIZ0TUVbthCNE4JlLjY6Nd+aw0DIgokq2FWsp54yNOfoyNt73KSsfPQO9zMqdQeY+pdxgZt+WZR9CSkw4LhrsGaQ4qUeKzjreNKY7Hjinb52lzd/eOkpXJMVF+AbcVi9fMQjDsoxzQVpchC3g+ceZvXHD6K7YnleGwooanDOwvR50i4lwINIMaiK9qkAuGNQRI7qm6MBFlQPP2pyr1zqw2l9chds/X4GEqDDM+vupeOS8fnVu77g+6bj5lG64c1wPHaB5VyWFhgi0j49EWmyEz5oXyvr9xSipqsWPq/bZMr+KyuiEWz6PlJgI28J4j1/QX3eok6LDbFlh73NRXYora3FCV8+5eHzfdjrQ7pgQiXbxkT7bpwKn9LgIPWhxzcgsvT+4pES7+Mg6z7c3n9IN0+85Rf/+qFkarc5nI7om49f1OX7nQcaEO/DFTSfq38PNACMuwoHocIcOdNPiIpAY5fmsslKikWgGm91SY2yBa3xUmJ52o6gyzutGdcXv/xhru0+d0yIcIXWWwQ7ulIjFD47HsC5JiI1wYMlD4zHAnA4CALeP7YHHLxyAafecgq6pMTqDXuF1ZQ9/hmf5zoEGgOgIh23QOjU2QmdjvQc2MpOikRJrfH/e2cKTeqToygB/U0KU8hoXuqbGoF18hO08eNf/VmLD/hJ93hv+7xkY9PhvPpnN0mon3pq93Vi/4YL+utrGylquu+TB8Ti+c6Lu9wBAz/Q4dEqORlmNE8WVxuCLytB2SY7G+L6e8vDYCP+DegDQq30cQrxGLw9V1CA8NAQTTuhkq5TISIzW23Xj6K56mg9g9JfCHSG6Amn1nmJkJNmPH+s6B/llNXhu6mb0bhenB5TqWwdBtbfWY3LOvWMRGiKwI68MUgJdzfs+nJ9ta09TYz19B8BoG0f3NPpTT18yEEII3V7eNa4HeluOiZN6pKJLSozeV1S1DGCcJ5btOoSPFmSjfXwkBpntMQC8fuUQPHOJJ2CPcHguZwwYU75yS6pw/uvz8NTkDfjrl6vqvRSpWsPDall2/YOrKbq/VOPz2FqXxPgXZ/ucwwFjYcdXpvsO6DYk1OxvNeaSn+rzbE45vJTG4AsAHCw2Xm9nfrleu6AxvCse1Dl+88FSLNierytLy2tcLXIp6UDCAL2FqBWVAaPM98kLPUGsCqrVaqcAMHdLPpxuqTsctS6JE7KSIYTQmQchjOvpWhsidRIPDRF6xweAM/u3x0VDjJH2HfllWPvPM9E9LUaPFqvMJwD07RCHDglRKK9xIS7SgbFmqXhZtROPnNsXp/VNx95DlXhy8kZc+d4i3OC1snK7uEh8dP0J+MeZvVFe49LZJ2vAXFdD7c/oHqn6RHXViC62DtyLlw3CaEvnrkOCpzHPSIzSwXSvdnGIDnf4zXIBQI+0WKO01BzJbG8ZrW6fEInMJE9lwnvXDNP3RYaF4qyB7TG4UyKOy0zA4xcMQFyEw6daYk9hJfp1iNPbc5llLvB7c3ci3BGC0T1S9fdhnWeW3ECAbs22jO6RqkujE6LC0CEhSs+7jo1w2ObgfHj9CfrnARkJ+O2vY/Tvaj0DwOhAn97PMwhkPSGrbI3qXKbGhuOJCz3z+TonR6OT+dn9/YzePqtXX/PBEkwzB5vevXqorlbo3zEeAzMT/JZaPXpeP4zrk24rG567NR+P/7wB87fn41xLhslq6rqDOoNmDbL9zdOPCrcH6B9fPxxdkn2DEcAYcHvxskG22/LLanDJmwts2YXSaif+fHJX/N+JXfRtGWbnc+XuIozplaYXegSMfUsFcNeO7IIBHROQV1aNQxW1SIgKw2BLKaw1u9A1NQb3nmWvuFCdm+M7JyIrNQYZSVE6eLYOuNx/dh99DC15cDzuO8u3cgMwjic18BIdHqoDHJU5PKNfO/1Y67akx0XoTuqqPUXo1S4W4aEhuNvrusmzNvk20HERDrQ3t61v+zi89cfjcc/pvfDxn4brAH1zTinio8IQHxWmByGjwjxZRbUOhjoXndQjxVZpYy3ljfEK0P9+Ri9bR7xfhwRdnp8eF2E7D182NBN92sfB6ZYoqqjFcZmJenBM7Vef3zgC0/7qCfZCQwQuG5aJgZmeTvNj5/fHqb3T9P7655M9ZcDe29Y1NQZdU433Ze2vhztCMO++sXjxskF44Oy+iIlwQAihz6k3jO6KM/sb35eap2ctDfdZmAzA6zO2YvWeYoztnY66WLc1OTZcD652T4vBOQM76HNRUnQ4jrO8Z2sw6O0PQzPxxlXGeg27CyuRHuc5T3dKikZKjHGeVOfLzikxvi8CID0+Qg/yjOqeotdVUMeENZO57vEzdYZ/SKck2+BORmKUDpgvPT4TY3ql1bntMRGhOLFbCrKfORfZz5yrq4nUIq9qXmx6XIRt4cRuabH6+8hMitaVPYCxL2V4BbAq2xsdHorOXgMU6rmO0BDbAIoy6++n4ofbT0K7+Eh8fctIrHz0dKTHRaJjgm/21vO+jP25rLq23ks0vXHVEIzq4RmknnyXpx2PjQhFvGWfS44JR1KM8XtWSgxWP3qGvk8NUkxacwBl1U49iAUAT1400PYd1DfntFtarN5/IhwhePyC/vpqGX+wtM/ei4ylxITrcx9gVC3661e43BITrxmGMb3SkBIbge9uOwkPnN1XD0REhoUgPtIBKY3gIT4qTLf7sZEOPQ0FMAZ3rBl067HVq53vYOPDP6xDjcuNrqkxGGLZ1oykKKSbFZKVtS5bvyIxOtzWR3v36qF63x7eNRmjunu+O+v3kZUajWTzuPN33XlrWfgtp3TH83/wtJXpcRFIi43QA+vWgdfjOyfigkFGn9W72iMpJhzj+rTD9n+fgz7tjWNT7c/G5+j5mwlRYXpQ/LjMBLx4uefvX2JpN+OjwnQiCDCm0Hn3u6xB9oPfr8Xwf8/A2n3FeG/uTny/cp9tSp7VxUMydIJm0p2jdYXX375e7ffxAHBCVhL+eYHRl/ptfU6dA7T+LqUIAK9M33rYV1IKNduw3QUVeOLnDY0KaBu6hN7L07ZgylrPFMMF2/J1O6wy6Ckx4Xh5+hb85YuVeG7qJtz+2QpMXnNAv3ZZtdNWaSqlxMLtBbjkzfl6oW1l8poD+OuXq3DmK7/jqvcW2xYoXLGrCG0JA/QWYl1Qq9blRjtLg6ca2Hnb8pEaG4G4SIeeD3vrKd3xh6GZGNE1WQeiWWanIyUmwmcUPN08iXsvFJESG45R3Y3n55RUIzbCga6pxkkrNTYcAzMSdEe9X4d4Hdx3S41BhiUr3S4+0tZBADwr3o43A/nu6bE4tXc6bj2luy0LZc0cDu6UqOfUNyQq3NN4p8SE2xapOm9QB1xlyTpaOyvtEyLxztVD8eqEwbr0XW3PPaf3wsOWBaYSo8OQHB2uV5a+1ZyPZbznCN1wpcdHIikmXI/WRoWHIj4yDD/cfhJ+umM00uIi9DSDU3un4Z/nezJa/Tom4IPrT8Dce8ciMiwUCx8Yp++798ze6NshXge/1uxpklfDec/pvXSH+rpRWbh4iKeR+ctpPXHBoI64aHBHHbirxs27E+EdgPSwfK4JUWF6rl9kWKito2O9nJK6VTVkyTHhtiA8MToMCdFhyH7mXJzRvz0SLIGT8tRkI3OaGhehL5vTOTnaZ/6oEhvhQCc/5aKfLtqFSEcoHj3ffxbxowXZqHG5cUodneh7z+qtO3eRYaG2krl28ZH6e1XboNx6anecNcAzgHH3+J62klBrmVz7hCjbwFmy5bPqnuYbTKjPIC4yDOnxEXC5jYW94iPD9MBHr3ax+OcFnvccFR6K60d19fs6KmNireZQx8Y5A9sjPT4SWWaQFx8VpgMeALjJUhrePS1WZxtKqpw+x/K7lkGsk3uk6c98dM9UPHB2Xz0g2C4+EsOyklDjciMyLATbnjobUWGh2JpbhqiwUJw/yFO+GxIidDYtISoMZw/sgLvG98QpvdJsq+7XON0IDRGINQPi+KgwvWCUOo+o/WdgRqIO+ADooACwf8eA0RG3Dv50So7C+cd1RGpshG3QBTC+r26W42l0j1TEmIGYqgoZ1SMVnZKj8fmfR2D6Padg4QPj0L9jgi1jmJkUpc+b4aEhukOZGhuO724bhf4d43HecR0wwRzYGts7Hf+6sD++vmWUHkwIEUZgl+Q191TNzx/ZLUW3LSoYt5Y43jm+h/55+j1jMKJrMt6buxOVtS5bMD3776fqkv8RXZPxt9M9AzMpMeG6Skt1utS5LsnrnO5NVT4BwLOXHoezB3TAxUMy8ORFxiD3vy7sj6ToMHRK9pTvqvc6ODPRZxElAEiPi8Qn1w/H3HvHwhEaoteBUdU86vnt4iIRG+HQ0x3Ud2ilnts+IQJ9O/guFKhEe5Uhq7ZalWSqrJ81oACMc6rK3MVGOGxVF/FRYT7zwz2XRzS2tUNCpB5wUG1AWKjwKYu23g8YGWjVh/BXXq1kJEZBCGBnXrme8uJPXGQY+nWIx4CMeNwxtgf6tvdU58SEO2xVheGOEF1FICFtAxZZqTG27PQLlsHRaK8paAsfGKenWKXGRuDxCzyDxz3SY/V5IyMpSg8OA0bVwid/Gq5/v2NsD/0Z3nNGL3xzy0h9X3tLnyguwoGJ5rnPLSVO69cOn/xpuK39fM4MULukxNg+7/hIhw4so8Md+vsDjHOfShqc2C0Zd4z1lL9bA3lvSTHh6NfR8znHRjhwtXmuGtolyVaanxgdpoP9HumxGNUjVa+Sf/5xHfR+Fh/pQIJ5vAFGUsTaVnt/Bx9ZEgFZKdG2vkxYaAjaxUfoqsluabEY1ycdaXHGgIa6dLBaWE31MVW7af1cVXl2XKTDlqUPCw3R5570uAj0SI9FaIhAl5Ro/OW0njqhUFBWbRtkjXCE+vSR/J1LrPxVEHx9y0i8dPkgjO6Ziq1PnY0BGQm6gsof9fllJEbpAZuHf1iH5Nhw24KbVg+f21evIQBAr7+09DBL3dU5eeK8nfhg/k69SGZ96qsaAIBXZ2zFrebCsZ8t2Y2rJi7Gr+bUWreUCBFCn19+WLUfU9YdREWNC7d/vgKXvmVMlXrkh3W49K0FegrFV8v24Mr3FmHF7iKfy0YC9rUhpqw7qKcBLc0uxMM/rMXK3Yd8nhOMGKC3EOvIco3LbWtU1c8VNS4M7pRoO2n26RCHFy4bhC9vHqkbKRWg++ssqDkyKohS56/kmHAkx4Tj/07sjNeuNDqkqnHq3zEBQgh0SYlBaqyRrVUn0Y6JUbasdEpshE/HVZkwvDM2P3mWHoUMCRG2bNCDloA4OSYcD5zd1+c1AOBfFw3Az3fYyxxVQxYVFmpruLxPoikx4XjuD8fhvWuGISw0BCmxEbjQUu6qVk/u2yHeNl9dCGEb6bV2kmMjHHokWXUko80TbFiI7yGiBglG90jV1QcAMCwryQiszM/WGvxMGN4Z3dM9HRRriWNyTLgte3vX+J66NNo72O3TIR6O0BC8MmEIxvUxgvhISwa9PtYyubhIB443s/2dvMrcnG5PSZEqc1L7i1vaF2ZKiLIHBdbs3IQTOuGakV10BzUtNkI3xN5lntYsXrjDPrI9/Z5TdFVJ+4RI2/Fz2dBM20DM1Sd20eWLI7ul4KubPR2tMT3TdHYjKizU1oi2twTo3VJjsO7xM/WIfafkaNs++NfTe6GP2SHISonGi5cP1vcN7ZJkCyatAWEHP1kq1UGOj3LobE9uaTUSojz7kdMtERcZhhtHd9UdR+/SabVgoQoKrHMP1X6hOr1dU2PMQCBUb1+IAO63TMvo2S7Wdmxbgw9rGSdgdPbUwIf6TlVmJK+0Wg8WRIc74AgN0cHQ/53YGa9fOcT2Wipw8V7cUgihK1vUJW1UMD6+Tzv8+eRuePfqoTqzrwKwEAFbFtaaIfE+XjomRiE+ynNbdLgDnZKjsezh0/TcSSUyLAS92sUiOSYcI7uloH/HeP0+rfM4AWBU91T0SPdk86zBULv4SF3CnBgdpoOqHumxOL5zEibfdTLeuOp4vZ8IIXD1yCwM7ZKkB3y85+QpqvN7au80jDenP43pZQTqqsTx5ztG2zKUPdLjbFkma1YtKzUGp5irEEeHh9rOJymxEfqcpcrB1QrcSdFh9XZYEy3nk9AQgdAQgZevGIyh5vnp6pFZWPnoGYhweI5ZdT4amJmAdY+fqZ/vCBEICxVIMgcO1THUOTkaZ/Zvh1fMBS9VZ18NpqnAwN8x2s0c6I50hNqmhDzmNVDoHRCrtkR1cN/84/G45PgMjOqeirjIMDx2fj89UHyVGTyO6GZU0amKmdhw3wUHa5zG56o6+vPuG4clD50GwHM+CQsNsQW9Sl1tRH0BemRYKGLDHXht5rY619kBjDZFCIFJd56Mv5/Z27Z/xEQ4bMch4Am+1BTTidcMw+XDMhEb4dDnqvS4CNvVE7y3Mz0uUk97O71fOq61zE3u2yFeV25U1bhsFQWdkqNtr/v3M3vrNifSEaov7aT+pnru4M6Jukqgrkquswa0R/Yz5yI5JtzWbsRHhun2R63L8vczeulzpwo6jQXlPM9TFR3j+qTrSiIlNsKBuMgw3HxKN1211y0tFpv+dRYuHpJpG0w3BoaM96z2HfU2E6LDdb9GDUaoYyw5Jtw2PeHqE7tg+j2eajzrMdM5Jdpnvr4ayOzVLhaje6Ti3auHYv59xqCcGvxSizD+54/HY+pfTrb1ARW1wJmA8Pkb6jOqcRlt5cIHxmHaX0+BIzREDx6rvoz6Lv1VmFin4tRn+j1j8K8L+xuVgBkJOvBXx5+1IuB0S7XZhifO1NUbMZb9HDAG/q2r4lv1aR+Pey3ts6roq+8Sf/54zz2vdTZcvq6qyMqrndh00P73rBn8J37eoNe9+e+i3ViWXQiX22iz1LpX3nbml+P81+dhtbm+0y9rD2Dt3mLbApSNqbC/aEgGOiVH4aVpW/DfRbvxwHdrG35SEOBl1lpImaXhqnG6bR2SDpYM9ck9U/Wc7vMHdbQFx0pqnHHQ9vQzj1I1IrVmEBUiBNxS6gP9yYs8JZqqk6pOXpcMyUBpVS2EEDrjBNgXXkuNDbc1Dmf1b4/luw8hr7QacZEOn3k2AzMTsGB7AR44uw+6p8XiwsEdMX1DDoQQPuXOeruiwzAwMwHP/eE4ZJp/Ww88mEfjST1S/F7/UQiBy/1c4kp58Jy+uP2zFRjaJcnn+qepceHYnGOcPK1BphACN4zuhsykaD36fMup3fHoj+ttAZaiMgFhoSHokhKDXu1icaii1meF1nBHCCbdaVz+IzbCgf4dPQFPYnQYrhuVhY8WZKNdfKStQwB4SvDVJao++dNwLNhe4LeDpRqDw7nEREiIQFZKNJ6+ZKBPGav1Gt0qoH743L4QwugkWLfVXxY8IcpYHT4tLgJ92sfrk21aXIRuiBOiwiDg2d6N/zpLX4c23BFi+yyTzQzc+v0lSPMqNf7L6b2QkRil54o/cWF/Pbe2Q2IkhljKxPt1iNfHiRoQ+Of5/fDVsr2Ij3LoDon6HCdeMwwP/bBWZ5LvHt9TN+qqo5gQHY6OCUaJ6P7iKgzMSNDXE1fbrqjy7UfO66cbLF22Z2bQlfioMN3xUe/2Ycv8Y/UZqABKdbzU9Adrx1C9V1WmeMfYnjjvuI627XNL+wBOelwkUmP8t4xq4O3EbslYtKPQzOhnIVQAp5vrZagS0e15ZRjfNx0vTduiM6tqn1aB6bAuSXo+oio19h6AAKAzOqVmcPn5n0fgk4W7cFq/dISGCJxhWasjVpflGo995pKBthX0AeiBAs97jqh3XquVEAJxkWFY9tBp+nM7qXsqrj6xCy6wLOrlj7XyKdwRogdkT+2dhs4p0Xjq4gE4y/Je6nKCOY3IOn3J6pUrBuP5PwyCIzQEHROjMPfesTogHZSZiBmbcpGVGo0wh/09q3P838/ohY6JUXj/2mF6HuCYXmkY2S0F95nzXuPMVbtjwkMREx6Kcwa21xU/KvBSne1Jd47W56r3rx2mL6sWHR6K//35RH2ZvvpcMLgjDlXU4K+neTJN1jYpKzUGFdVOn+8xNETgnas9VR9q0Fx1lm8a0w1nD+igS8ZDhGfF6itO6IRvV+xF3w7xtqlRE07ojNTYCL0olHdQYT33AMbg2UuWwbzrT/IEWwMyErD2n2fo/fb5PxyHJy7sr/etu8b31Ku//+PM3pBS6sXkbNVP5rnbu/Lu4iEZ+H7lvjoHSvwFK1allgTE7WO74z+zfC8Z529Nh3bxEcgpqdZ9ikuOz9DJBdXvUANbp/Vrh9O8BtiSY8IR7gjB3eN71lm9oAbbe3hlmrskR+tzX1ezzX743L54cvJGdE6Otq0KDnjOGd5XD4kKD0X3tBj866IBOG9gB0SHOzD//nF+r9TgTQ3uAEBkeKguKVbH0x3jPJnybpZpGOp7P7Fbsv7OPrjOyFSrK9OckJWkB7G8kyHqOSEhAssePg25JdUICw3BGf3b4dUZW/X+4Rkkkehotk8qy/rHEV0wf1uBrXJFfU7W5IO14rJraozPfPnrRmXh+5X78PQlx5l/T9gef3LPVNxpfg6RYaG6pN2b+r6cbulzfKuBOHVcWweDVLuuMtCpMeHYX1yl14jonByt+9Xd02KR/cy5ui9Slx7pceiRHoerR2b5vV8tUDvhhE545tLj9OtFhzt0QsQtpa3C7vjOSbbLc75z9VCEh4bgsZ/W6wSFkhQTjtTYCNvCrI3hPUXBewE2f9QidU/9shHfLt+L1Y+dgciwULw+Y6utUth6lZx52/Ixb1s+xvdJR2iIsXikvxXsAdja5SebuBL70C5JiLS0A+n1DDgGEwboLcS66IIKLtS1K62ltFcO76zLxOoagR3bOx1n9GuHxy1zfRXViVeNc0iIANwS/q4vWGFuk9qeP1tKWK0ZfmuQlRLrWewnIzEKr181BOe+Nhd5pdU+cxUB4LiMRNt2vTphiOW1jNdJi4vA0odO0ycp1RBaA+07x/eE0y1x8RAjG/7ZjZ7FdgBjTtaMjQ0vLHFitxQsf+R0AJ5VblXn4MJBGZi/rQChIUIHMOqkPzAzwZYxvGZkFq6p4+R7+9geqKpx6dW0f7pjtC2otbKWiFqz5InRRgblqhGd9QDKm388XjeOZw9sj5mbc3G3eemRMb3S6pz/ePXILnjo+3U6oLtyeOc6L7Vive6uEMJW9qf4mxeeHh9p+24Vfx07tdJ6ZlKUrVMVGRaKa0ZmYfrGXAztkqzLkNp7nUyTosN14wkY+2fv9nHAathuBzy/33N6L3RJibY13AlRYQgLDcHnfx6BkkonQkKE7hSq7+u6k7riOrOjrBpBdb33Mb3SMPdeT/ntXy3lZyo7FW9mjX675xQcKq9BaIhAqtl5ueWU7rZjRr1PaxYkKyUGO/LKEe4IQb8O8QgLFah1ScRFOtAtNQaXHp+JP43O8vmMAWC9Jct/2bBMHN8l0dZJnXL3yaiqdelGT+0T7RMidaCmtk+tijv5rtG6sxISYuwfKrMz+a7RtukPn/xphM4EhYQI/TkCns7m2QM6oF+HePRpH6czun88sTM+nJ+ty/G/uXWUft7wrsl4/cohOLW3776e6VXp0SUlps5F007umQZgo85ITBjeGRO8HmOtULrt1O664/TO1UN9MjR1sXZGQ0IE/nXRgHoe7d8JWUl46fJBOHuA+fmM6NLAMzx/b/3jZ9qu+WvlCA2BdTzVOoXjlQmDsT2vHHGRYejgNSVcDd4O7mR0/lX2HTDO3f+zLIQ29S9jsD23TB93b/5xqL5PVTioYMF6LrS+phACI7un6IU865ORGIUHz/GtzJp771hICXy+ZLdt8am63HRKN5w3qKOuFhBC2OZzb3jiLP3z8K7JWPnI6Uj0ulZ9VHioHlwBfM+FkWGh+rzUGNZAJ8TSRgGwlb62T4jES1cM9vsaJ/dMxXnHdcB9Zrbt61tGYvWeIlw3Ksu2dog/MeGhtkFkqw+vOwHXf2SsRWPNPEc4QnSw6T01DgB+/csY/Lr+oH5d6wBFj/RYzPjbKejqZx0Bda5UVRh/raP0FzD6S5/fOEIH+j/fMRq7CsuNsnFzGpwKZG8Y3RU3jO7qdyBO9RMcfqrmhBB68B6o+7J03vp1jMd9Z/XBs1M3ITw0RA8mVfupelEVMeqcvPafZ/gdUHnlisHG2jgDGh7EA4z+n+oD9u+YgA+vP0F/5mN7p+OXtQfRMz1ODx7cZa4uf87ADph+zxh0TY21DQJ1SY3RfcaTeqTY9nuVcJrxt1P0tg/qlIgd/z7HJ3AHjIGkT28Y0aj3ccXwTvhy2R49Xeedq4fqjPDxnRPx2pVDdCWMlRACO58+R3/nqXER2F9chSrz/f5+71if5/gTEx6K8hqXT1WjP6rKq72fihyVsCsoqzEDbSPYVv2XzKQoXDa0k14cemwdWfVe7WKxxXIZNCklPl20C2f1b19ngOp99QHvq+LsL6pEZa0LUkL3Rf67aBdW7DqEn1fvR7XTjW25ZYiNcOhFkuszY1MuBmUm4M8nd0NabAQ2HSzBoh2FOigfkBGv11+5blQW0uIi9GLBfz2tF4ora22B/4Pn9DEuhTymG1Jiw1FW7cKBokrERYbh9rE98MiP61Ba5dRz4IMdA/QWUl7tRHR4KB6/oL/OTv1w+0koLK9BZFgoHj63L8aYl7dRo1b+Dl7AGLm3zvG0io8Mw/KHT9Oj+7rE3U+2+k+ju2Jnfrkun7M6qUcqrhnZRc877dUuFltyyhATHqpLsaudLoSFhuDCwRl4/tfNfgcBTuqRgvF90jGiq2/nSs2z9r7Mlr+GPCEqTC+Y4c9D5/bDQ+fWvYKxP0IILHlwvB6wvfyETshMikJoiGfunfciO40RHxmGxy2LANZXvmkVEiJ0psiY1ydsnR3r5XWiwx34z1XHN+p1/ziiC648obNuAJ++xHfFWWXm307Ro7t16Z4Wg40HSnDuwA44e2DjOgFWKkveOTlGd2BVwzmmVxqynzkXgLEP3jmuB4aZmcDjMhOwZm8xRnRNxhrLqGpoiNDZQrVgyln922Pq+oM603qX5ZI1quRXDTSptRkA6MCrwM/CJ2oBm8ZcQkeNyqusbWyEQw88hYQI7Pj3OebK8J7W3HsgQn0GMzflIjREIDIsFH8/ozeenrIJJZW1cISG2Ba88WbtwAshfDJIqhz3gkEdseVgqc8ovHqetfPi3UG37kve94U7/C9EBRjf2apHT0d0uDGAMfUvnpLIR8/rh5vGdPNbPSSEsM1Lt4qNcCA8NAS3WObi1aV3+7g6O4WK6iyP75NuKx88s57s9XvXDGtUANiQmX/zLB4nhLAtZnQ4vOdQNlZcZJiucoj3qiSYcEInHJeZUGewZpWRGFVnsPLspQPx1bIk2yJWR4oafGjMtb8B47u3lvJ78z6nW+f3P3hOHywxL32n2o+6FlmznpeOhsiwULxhaTdOyErW5864OlZ1V9b+88w6gw9rkGBts/58cjf8uv4gtuaW+V1ILTE6HFec4P+67QDqXJtADd75q6LzJoTAKEtpsvdgu/V49g7MH7+gv/4OVb+kstYI+ubeO7ZRbUFDbh7TDb3bx+LUXul6DvOlXpfKBIzP6l8X9sfonmm27fF20RDf5x4Oa8XcZcM64dTe6XpQdvGD423TCKxtiqr4O6NfO4SECMz6+6m20uWxlkFV7++1vvNwYx3fOUn3HQDf7/WCOtoNdb/ywmWD8Pyvm/22h95WPXo6Nh4oxZXvLcLZAzvgm+V7cfnQuis4lf87sQv2FVXixpON/vXce8fq7LXqRxeW1yAsNASLHzwNIZa+wrz7xvl/UQDf3zYKIebjeqbH4uOFuzD+xdm4a3xPDMpMxKM/rsfkNQfwpWVqn9stUeV0ITrc4ZNBL6rw9IO25ZbitJd+9/mba/YW266EsPFACf7xzRqfx3VJicauAt8F7f44ogtCQwQutSzMqJJ1n914Iiat2Y83Z23HneN6ICU2Ar9tyMHqPUXokR6rpw4nRYdhpblw4ajuqejfMd7nWL5oSAYuGpKBP3+yDLv9bEcwYoDeQsqqnYiJcOhLnwHGCVadZNWBChgH1o688jqznA2xrmB5z+m98O9fNvksEAQYJWTvX3eCz+2A0bl+whJkfnvrKBwsroIQQpfLqmur33Zqd1w8JMNWCq8kRofX+TdSYyIwvk86bjBXJA13hKDG6a5zpfUjwXskUTXkTpcbV43ojBu95nQdaY3NFB2uxjaAidHhSGxgTOKZS4/D5cM61bticX1UgNwlJRohIQJLHzrN73ceE+HA387wzJX+7MYRcLklQkKEXuRLVVSouYRqddtXrxyMbbllfjsx147qgt2FFbjupCyf+zyNo2+QFR8ZhrvH97St+l2Xvh3iseD+cX7nrAL272POP07Ftyv2+V008fpRWchIjNJzp1XmubGl1o1x7ags29xMby35t6wS65jiIoTwG5w3xpanzm70YxtzTCx72P++WRfrfMLm6FbPomlHmxACz//hOHRP9+x7jQnOG5ISG2FbjLOtuGlMd9xkjjclRIXh5SsGYbifAepg09g2pHtaLH6562R0So4yFiUb2QWLdhQ0ebDIH7X/Was+jgTreVGtP6EW/G2pvx0SIvR6MZ2So21Bpre6SqaPJOt6L/WtRfDIef1w/9l99OCVdYBry5NnH9YUu9bUq12c7Uo99UmMDsfI7imYfNdodE+Lxb1n9vbb1/aWEBVmuyKIdV86vnMSxvRK01dQOZzPbYg5hQ3wTBHbnleOu79YpSsL9hfbB7WumrgI6/eVYHTPVGzLtZfEvzZzG7bmluHxC/r7Dc69xUU6/Abnfzu9F0JDBZ6buhnxkQ6c3CsNk9cYC9BdNqzuwef4SAf+OKKLrWosIzESq/cYFZgqyXLIsiZNfVcBAYwkTFOvEx9oGKC3kLJqZ4PX1VWev2wQLhta2CINgNFZaH4nyDqYoDIiqoRbCOE3OG9ISIiwBe9RYaGocbobXMzsaHCEhvi9tikZmcqGgvNvbx1V5yU+xvRKw+9b8nTGuDHXeAfsGYOU2AisfuwMXUoXGRZq69hEOOoux0yMDq8z86zmt9W10nt9pZTeGntMdEmJqXN11pAQYStVHN8nHY+d36/JGVU6PN7rRhyrLqtnXY8j5bvbRqGiuvkZytZmvcrGsSDcEWJbObxdfKRtodaWEBUeis9uHGG75N2R9tfTeqGk0qlXhCY7YwHHpq1hEGxm/u0U24KI/S1XvGmuyLBQ2xUEmkoNkJzYLRkx4Q7MMC9duqewEvd/uwbHd05Ch8RILDIvPTtlnbGy+qDMBKy2ZMSnrDtY56XUMhKjdNXHt7eOxIpdRXjqF2PK3Fc3j8RV7y3CiG7JuHN8T/y0ej8A4ypP/7nqePRptxW1LrffBMD0e07BxgMlfu978qKBGNE1BcdlehbfG3wYVVjpcZGocbp9rnQVjESg1+oPGzZMLlu2rLU3o0E3frwUOSXV+NlyDe9gVlJVi+iwUJ/Fy5rjiZ834IP5O7Hu8TMDIkinI6OixomCspojnv1oquKKWsRFOlqk7I6I6Fgwdd0BbNhfgnssVU9E1DqcLjfe+X0HrhreGQlRYej24C8NPueKYZ0wpHMi7jdXOb/5lG5YvKMQq/YUQQhj/aLPF+8GALx8xSD0aR+Ps1+di4fO6avXsLrx42WYvjEHqx8zSs6jwkIR7ghBZY0LXy/fg5N7ptU7fehwlVc79RTAxnC5ZdBUcyhCiOVSSp+yjqMeoAshzgLwKoBQABOllM/U9/hgCdAB44BpyYC2rXG5JYoqamwl+kRERERE1DQ/rd6P53/dhKLyWkwY3gnvzTUWV+uZHovHzu+PmIhQDOlsXDHl/Nfn4YJBHfHAOX0xce4OPDl5IwZkxGPSnSdj3b5iFFXUYrR5dZDc0iqkxETooLeq1oVdBRW2K0FR8wREgC6ECAWwBcDpAPYCWArgSinlhrqeE0wBOhERERERUWuQUuLxnzfg3OM66EUive8HjOmrB4or8ZcvVuGpiwce1Skl5FFXgH6064yHA9gmpdxhbtQXAC4EUGeATkRERERERPUTQtR7VSTr3O8OCVG2Vd8pcBzteuwMAHssv+81b7MRQtwkhFgmhFiWl+f/4vZEREREREREbcnRDtD9zdz3qbGXUr4rpRwmpRyWlta0Sz0RERERERERBZOjHaDvBWC9nksmgP1HeRuIiIiIiIiIAs7RDtCXAugphOgqhAgHMAHAT0d5G4iIiIiIiIgCzlFdJE5K6RRC3AHgVxiXWftASrn+aG4DERERERERUSA66tdBP1xCiDwAu1p7O46AVAD5rb0RREcJ93c6VnBfp2MF93U6VnBfpyOli5TSZ8G1gA/Q2yohxDJ/170jaou4v9Oxgvs6HSu4r9Oxgvs6HW1Hew46EREREREREfnBAJ2IiIiIiIgoADBAbz3vtvYGEB1F3N/pWMF9nY4V3NfpWMF9nY4qzkEnIiIiIiIiCgDMoBMREREREREFAAboRERERERERAGAAXoLEUJ0EkLMEkJsFEKsF0Lcbd6eLISYJoTYav6fZN6eYj6+TAjxhtdrhQsh3hVCbBFCbBJCXNoa74moLi21vwsh4oQQqyz/8oUQr7TS2yLy0cLn9iuFEGuFEGuEEFOFEKmt8Z6I/Gnhff0Kcz9fL4R4rjXeD1FdmrCvny6EWG6ev5cLIcZZXmuoefs2IcRrQgjRWu+L2g7OQW8hQogOADpIKVcIIeIALAdwEYDrABRKKZ8RQtwPIElKeZ8QIgbAEAADAAyQUt5hea3HAYRKKR8WQoQASJZS5h/lt0RUp5bc371edzmAv0opfz8a74OoIS21rwshHAD2A+gnpcw3g5YKKeU/j/qbIvKjBff1FAArAQyVUuYJIT4G8ImUcsbRf1dEvpqwrw8BkCOl3C+EGADgVyllhvlaSwDcDWARgF8AvCalnHL03xW1JcygtxAp5QEp5Qrz51IAGwFkALgQwMfmwz6GcQKAlLJcSjkPQJWfl/sTgKfNx7kZnFOgaeH9HQAghOgJIB3A3CO35USHpwX3dWH+izEzLPEwAnaigNCC+3o3AFuklHnm79MBsBKQAkYT9vWVUkp1vl4PIFIIEWEG+vFSyoXSyHh+op5D1BwM0I8AIUQWjFHlxQDaSSkPAMYJAUYAUt9zE80f/yWEWCGE+FoI0e4Ibi5RszRnf/dyJYAvJct6KEA1Z1+XUtYCuBXAWpiZdADvH8ntJWqqZp7XtwHoI4TIMitHLgLQ6chtLVHTNWFfvxTASillNYygfq/lvr3mbUTNwgC9hQkhYgF8C+AvUsqSJryEA0AmgPlSyuMBLATwQgtuIlGLaYH93WoCgP81f6uIWl5z93UhRBiMAH0IgI4A1gB4oEU3kqgFNHdfl1IegrGvfwmjIiobgLMlt5GoJRzuvi6E6A/gWQA3q5v8PIxJBmo2BugtyOyAfQvgMynld+bNOWYJjJrzktvAyxQAqADwvfn71wCOPwKbS9QsLbS/q9caBMAhpVx+RDaWqBlaaF8fDABSyu1mlchXAEYdmS0mapqWOq9LKX+WUo6QUo4EsBnA1iO1zURNcbj7uhAiE0bf/Bop5Xbz5r0wkmpKJjh1iVoAA/QWYs4pfB/ARinlS5a7fgJwrfnztQB+rO91zI7bzwBONW8aD2BDi24sUTO11P5ucSWYPacA1IL7+j4A/YQQaebvp8OY90gUEFryvC6ESDf/TwJwG4CJLbu1RE13uPu6Of10MoAHpJTz1YPNMvhSIcSJ5mteg8b3e4jqxFXcW4gQYjSMUq61ANzmzQ/CmNPyFYDOAHYDuExKWWg+JxvGQkHhAIoAnCGl3CCE6ALgUwCJAPIAXC+l3H203gtRQ1pyfzfv2wHgHCnlpqP3Loga1sLn9ltgrPZbC2AXgOuklAVH7c0Q1aOF9/X/ARhkvsYTUsovjtLbIGrQ4e7rQoiHYUxJslaCnCGlzBVCDAPwEYAoAFMA3Mm1dKi5GKATERERERERBQCWuBMREREREREFAAboRERERERERAGAAToRERERERFRAGCATkRERERERBQAGKATERERERERBQAG6ERERG2YEMIlhFglhFgvhFgthLhHCFFv+y+EyBJCXHW0tpGIiIgMDNCJiIjatkop5WApZX8ApwM4B8BjDTwnCwADdCIioqOM10EnIiJqw4QQZVLKWMvv3QAsBZAKoAuATwHEmHffIaVcIIRYBKAvgJ0APgbwGoBnAJwKIALAf6SU7xy1N0FERHSMYIBORETUhnkH6OZthwD0AVAKwC2lrBJC9ATwPynlMCHEqQD+LqU8z3z8TQDSpZRPCiEiAMwHcJmUcufRfC9ERERtnaO1N4CIiIiOOmH+HwbgDSHEYAAuAL3qePwZAI4TQvzB/D0BQE8YGXYiIiJqIQzQiYiIjiFmibsLQC6Mueg5AAbBWJemqq6nAbhTSvnrUdlIIiKiYxQXiSMiIjpGCCHSALwN4A1pzHFLAHBASukGcDWAUPOhpQDiLE/9FcCtQogw83V6CSFiQERERC2KGXQiIqK2LUoIsQpGObsTxqJwL5n3vQngWyHEZQBmASg3b18DwCmEWA3gIwCvwljZfYUQQgDIA3DR0dl8IiKiYwcXiSMiIiIiIiIKACxxJyIiIiIiIgoADNCJiIiIiIiIAgADdCIiIiIiIqIAwACdiIiIiIiIKAAwQCciIiIiIiIKAAzQiYiIiIiIiAIAA3QiIiIiIiKiAPD/K3TMNXog9zAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1008x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Reason']=='Traffic'].groupby('Date').count()['lat'].plot(figsize=(14,3))\n",
    "plt.title('Traffic')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "2dbb6666",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Reason']=='Fire'].groupby('Date').count()['lat'].plot(figsize=(14,3))\n",
    "plt.title('Fire')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "c586e547",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Reason']=='EMS'].groupby('Date').count()['lat'].plot(figsize=(14,3))\n",
    "plt.title('EMS')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98bb9775",
   "metadata": {},
   "source": [
    "#### Create Heat Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "f9601a15",
   "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>Hour</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day of Week</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>1983</td>\n",
       "      <td>1635</td>\n",
       "      <td>1449</td>\n",
       "      <td>1296</td>\n",
       "      <td>1339</td>\n",
       "      <td>1639</td>\n",
       "      <td>2670</td>\n",
       "      <td>4143</td>\n",
       "      <td>5018</td>\n",
       "      <td>5288</td>\n",
       "      <td>...</td>\n",
       "      <td>6394</td>\n",
       "      <td>7040</td>\n",
       "      <td>7065</td>\n",
       "      <td>7113</td>\n",
       "      <td>5668</td>\n",
       "      <td>5056</td>\n",
       "      <td>4375</td>\n",
       "      <td>3913</td>\n",
       "      <td>3422</td>\n",
       "      <td>2834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mon</th>\n",
       "      <td>1894</td>\n",
       "      <td>1571</td>\n",
       "      <td>1368</td>\n",
       "      <td>1272</td>\n",
       "      <td>1336</td>\n",
       "      <td>1844</td>\n",
       "      <td>2675</td>\n",
       "      <td>4430</td>\n",
       "      <td>5504</td>\n",
       "      <td>5724</td>\n",
       "      <td>...</td>\n",
       "      <td>5713</td>\n",
       "      <td>6289</td>\n",
       "      <td>6346</td>\n",
       "      <td>6408</td>\n",
       "      <td>5441</td>\n",
       "      <td>4488</td>\n",
       "      <td>3823</td>\n",
       "      <td>3254</td>\n",
       "      <td>2658</td>\n",
       "      <td>2072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>2447</td>\n",
       "      <td>2059</td>\n",
       "      <td>1883</td>\n",
       "      <td>1592</td>\n",
       "      <td>1451</td>\n",
       "      <td>1580</td>\n",
       "      <td>1880</td>\n",
       "      <td>2489</td>\n",
       "      <td>3457</td>\n",
       "      <td>4315</td>\n",
       "      <td>...</td>\n",
       "      <td>5421</td>\n",
       "      <td>5181</td>\n",
       "      <td>5211</td>\n",
       "      <td>5213</td>\n",
       "      <td>4980</td>\n",
       "      <td>4753</td>\n",
       "      <td>4127</td>\n",
       "      <td>3895</td>\n",
       "      <td>3226</td>\n",
       "      <td>2965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>2424</td>\n",
       "      <td>2135</td>\n",
       "      <td>1946</td>\n",
       "      <td>1614</td>\n",
       "      <td>1471</td>\n",
       "      <td>1488</td>\n",
       "      <td>1726</td>\n",
       "      <td>2408</td>\n",
       "      <td>3001</td>\n",
       "      <td>3728</td>\n",
       "      <td>...</td>\n",
       "      <td>4744</td>\n",
       "      <td>4475</td>\n",
       "      <td>4560</td>\n",
       "      <td>4505</td>\n",
       "      <td>4402</td>\n",
       "      <td>4135</td>\n",
       "      <td>3748</td>\n",
       "      <td>3161</td>\n",
       "      <td>2629</td>\n",
       "      <td>2323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thu</th>\n",
       "      <td>1731</td>\n",
       "      <td>1408</td>\n",
       "      <td>1426</td>\n",
       "      <td>1236</td>\n",
       "      <td>1293</td>\n",
       "      <td>1775</td>\n",
       "      <td>2816</td>\n",
       "      <td>4432</td>\n",
       "      <td>5297</td>\n",
       "      <td>5412</td>\n",
       "      <td>...</td>\n",
       "      <td>6079</td>\n",
       "      <td>6493</td>\n",
       "      <td>6375</td>\n",
       "      <td>6935</td>\n",
       "      <td>5512</td>\n",
       "      <td>4703</td>\n",
       "      <td>4045</td>\n",
       "      <td>3490</td>\n",
       "      <td>2844</td>\n",
       "      <td>2354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tue</th>\n",
       "      <td>1720</td>\n",
       "      <td>1459</td>\n",
       "      <td>1322</td>\n",
       "      <td>1213</td>\n",
       "      <td>1247</td>\n",
       "      <td>1741</td>\n",
       "      <td>2784</td>\n",
       "      <td>4425</td>\n",
       "      <td>5634</td>\n",
       "      <td>5566</td>\n",
       "      <td>...</td>\n",
       "      <td>5926</td>\n",
       "      <td>6252</td>\n",
       "      <td>6495</td>\n",
       "      <td>6883</td>\n",
       "      <td>5628</td>\n",
       "      <td>4621</td>\n",
       "      <td>3845</td>\n",
       "      <td>3409</td>\n",
       "      <td>2708</td>\n",
       "      <td>2137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wed</th>\n",
       "      <td>1664</td>\n",
       "      <td>1484</td>\n",
       "      <td>1259</td>\n",
       "      <td>1265</td>\n",
       "      <td>1128</td>\n",
       "      <td>1609</td>\n",
       "      <td>2668</td>\n",
       "      <td>4644</td>\n",
       "      <td>5469</td>\n",
       "      <td>5444</td>\n",
       "      <td>...</td>\n",
       "      <td>6069</td>\n",
       "      <td>6533</td>\n",
       "      <td>6745</td>\n",
       "      <td>7062</td>\n",
       "      <td>5691</td>\n",
       "      <td>4686</td>\n",
       "      <td>4116</td>\n",
       "      <td>3537</td>\n",
       "      <td>2826</td>\n",
       "      <td>2207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Hour           0     1     2     3     4     5     6     7     8     9   ...  \\\n",
       "Day of Week                                                              ...   \n",
       "Fri          1983  1635  1449  1296  1339  1639  2670  4143  5018  5288  ...   \n",
       "Mon          1894  1571  1368  1272  1336  1844  2675  4430  5504  5724  ...   \n",
       "Sat          2447  2059  1883  1592  1451  1580  1880  2489  3457  4315  ...   \n",
       "Sun          2424  2135  1946  1614  1471  1488  1726  2408  3001  3728  ...   \n",
       "Thu          1731  1408  1426  1236  1293  1775  2816  4432  5297  5412  ...   \n",
       "Tue          1720  1459  1322  1213  1247  1741  2784  4425  5634  5566  ...   \n",
       "Wed          1664  1484  1259  1265  1128  1609  2668  4644  5469  5444  ...   \n",
       "\n",
       "Hour           14    15    16    17    18    19    20    21    22    23  \n",
       "Day of Week                                                              \n",
       "Fri          6394  7040  7065  7113  5668  5056  4375  3913  3422  2834  \n",
       "Mon          5713  6289  6346  6408  5441  4488  3823  3254  2658  2072  \n",
       "Sat          5421  5181  5211  5213  4980  4753  4127  3895  3226  2965  \n",
       "Sun          4744  4475  4560  4505  4402  4135  3748  3161  2629  2323  \n",
       "Thu          6079  6493  6375  6935  5512  4703  4045  3490  2844  2354  \n",
       "Tue          5926  6252  6495  6883  5628  4621  3845  3409  2708  2137  \n",
       "Wed          6069  6533  6745  7062  5691  4686  4116  3537  2826  2207  \n",
       "\n",
       "[7 rows x 24 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(by=['Day of Week','Hour']).count()['Reason'].unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "75371c51",
   "metadata": {},
   "outputs": [],
   "source": [
    "dayHour = df.groupby(by=['Day of Week','Hour']).count()['Reason'].unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "68a67b70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Hour', ylabel='Day of Week'>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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I0y6pqi8DT52l/S7gxDmeczZw9iztlwFHL7TvVovZJH/M6BzZHwLeBfwEcGmbfUqSJEmSRiZdAKrP2r7O7DOr6nTga1X1JuAZfPvJvpIkSZKklrR9zmyX2r40z0PN7YNJHg/cDRzecp+SJEmSJCZfzbjP2i5mP57k0cBbgcubtne13KckSZIkaeDaus7s04FbqurNzf19gauALwK/10afkiRJkqRvN+BTZls7Z/ZPgM0ASZ4NvKVpu4cdXHBXkiRJkrR7eM7szltaVXc3+z8FbGiuN/vhJFe21KckSZIkadyAh2bbGpldmmRboXwi8PdjX2v7PF1JkiRJ0sC1VVh+APjHJHcyWtH4nwGSfA+jqcaSJEmSpJb1farwJFopZqvq7CQXAGuAT1V981K9S4BXt9GnJEmSJOnb1YCnGbc25beqLp6l7Utt9SdJkiRJ+naOzEqSJEmSFp8BF7NtLQAlSZIkSVJrdljMJnnBLG2/0E4cSZIkSdLuUjXZ1mcLGZn9n0meu+1OkjcAp7QXSZIkSZK0W9SEW48t5JzZk4GPJ/lV4CTge5s2SZIkSVKP7dELQFXVnUlOBj4NXA78xNildiRJkiRJfTXgym3OYjbJfXz7P30F8ETgJ5JUVa1uO5wkSZIkSbOZs5itqv2mGUSSJEmStHvt0dOMkwT4GeDwqnpzkkOBNVV1aZvB0oPh8FrekysXbe5BjvTkh2BJD3I88kjXCQDIQ5u7jkAemek6AgB73939AeORfZd2HQGA+2a6/zvklXeu6joC++z/UNcRAHj4oeVdR2DJsn78nG55sPv3giXdHyuAXlzzsbZ0nwFg6QPdHzuX39ODz1nAPpu6TgCrbtvadQQAVty7pesIw9KTQ18bFvLT+0fAM4D/0ty/H/i/rSWSJEmSJO0mmXDrr4WsZvz9VXVsks8CVNXXkqxoOZckSZIkSXNaSDH7SJKlNAPUSQ4E+jFnSZIkSZI0tz18mvHbgY8CByc5G/gX4H+1mkqSJEmSNLmacOuxhVxn9s+TXA6cyGjS9Iur6trWk0mSJEmSJtODRefaspBpxgCPBR6sqvckOTDJ4VV1Y5vBJEmSJEmTqZ6Prk5ih9OMk7wReANwVtO0HHh/m6EkSZIkSZrPQkZmXwI8DbgCoKpuTdL9hQwlSZIkSfMb8MjsQorZzVVVSbatZryq5UySJEmSpN1hwOfMLmQ143OT/Anw6CT/Dfg08M52Y0mSJEmSJpWabOuzOUdmk+xfVV+rqt9J8iPAvcCTgd+oqvOnllCSJEmStGt6XpBOYr5pxtcluQP4DPCvwDur6kvTiSVJkiRJ0tzmLGar6qAkTwKe2WyvT3IgcDHwr1X11illlCRJkiTtigGfMzvvAlDNSOyXgPcm+W7ghcBrgOcBFrOSJEmS1Gd74jTjJNtGZJ8BHAp8mdGo7MtoLtMjSZIkSeqxPbGYBf6FUdH6NuCvq+rB6USSJEmSJGl+8xWzj+db58v+QpJljIrbi4CLqurLU8gnSZIkSdpVe+LIbFV9FfhIs5FkH+DlwJuAw4Gl0wgoSZIkSdpFe+ICUEkexeh82W2js08DbgD+htGleiRJkiRJPZY9cWSWUeF6MaPrzL4ZuLSqHppKKkmSJEnS5PbEYraqDpxmEEmSJEmSFmre68zuDkmWAgeP91VVN7fdryRJkiRpuFotZpO8GngjcBsw0zQX8JQ2+5UkSZIkDfuc2SVzfSHJbze3p07w+q8BnlxVR1XVf2q2OQvZJOuTXJbksltvuWSCbiVJkiRJVCbbemzOYhZ4YZLlwFkTvP4twD0LfXBVbaiqdVW17vGHfv8E3UqSJEmSqAm3HptvmvEngTuBVUnuBcLonxOgqmr1Al7/y8CFSf4WeHhbY1W9bdcjS5IkSZL2dHOOzFbVr1bVo4C/rarVVbXf+O0CX/9m4HxgBbDf2CZJkiRJatuURmaTLE3y2SQfb+4fkOT8JNc3t/uPPfasJDckuS7J88faj0tyVfO1tyeZd57zDheAqqpTkhwMPL1puqSq7ljIP6iq3rSQx0mSJEmSdr8pLgD1GuBaYNvA55nABVX1liRnNvffkORI4DTgKODxwKeTPKmqtgLvANYDFwP/DzgJ+MRcHc53zizwzQWgLgVOBX4SuDTJTyzkX5PkH5L8/fbbQp4rSZIkSZrQFEZmk6wFfhR411jzKcA5zf45wIvH2j9YVQ9X1Y3ADcDxSdYAq6vqoqoq4H1jz5nVQi7N8z+Ap1fV7U3QA4FPAx9awHNfP7a/N/BSYMsCnidJkiRJ6liS9YxGS7fZUFUbtnvY7wO/xrefUnpwVW0CqKpNSQ5q2g9hNPK6zcam7ZFmf/v2OS2kmF2yrZBt3MUCRnQBqury7Zr+Nck/LuS5kiRJkqQJTTjNuClcty9evynJi4Dbq+ryJD+4gJec7TzYmqd9TgspZj+Z5O+ADzT3f4rR/OUdSnLA2N0lwDrgcQt5riRJkiRpMlM4Z/ZZwMlJXshoNu7qJO8HbkuyphmVXQNsGyDdCBw69vy1wK1N+9pZ2ue0wxHWqvpV4E+ApwBPZTSs/IYF/bPgcuCyZvsM8DrgFQt8riRJkiRpEpXJth29fNVZVbW2qg5jtLDT31fVy4DzgDOah50BfKzZPw84LcleSQ4HjgAubaYk35fkhGYV49PHnjOrhYzMUlUfAT6ykMcCJHk6cEtVHd7cP4PR+bI3AV9Y6OtIkiRJkiYwvdWMt/cW4Nwkr2B0ydZTAarqmiTnMqoLtwCvalYyBngl8F5gJaNVjOdcyRgWWMzugj8BfhggybOB/w28GjiG0XzrBa2GLEmSJElaHKrqQuDCZv8u4MQ5Hnc2cPYs7ZcBRy+0v7aK2aVVdXez/1OMpiZ/GPhwkitb6lOSJEmSNGaK15mduoVcZ/ZFSRa0evGYpUm2FconAuPXlm2rgJYkSZIkjZvCdWa7spAi9TTg+iRvTfJ9C3zdDwD/mORjwEPAPwMk+R7gnl1KKkmSJEnaKanJtj7b4ShpVb0syWrgp4H3JCngPcAHquq+OZ5zdpILgDXAp6pq29uwhNG5s5IkSZIk7bIFTR+uqnuBDwMfZFSgvgS4IsmchWlVXVxVH62qB8bavlRVV0yYWZIkSZK0EHvyNOMkP5bko4zOe10OHF9VL2B0zdnXt5xPkiRJkrSrBlzMLmQxplOB36uqfxpvrKoHk7y8nViSJEmSpEn1/bzXSSzknNnT5/naBbs3jiRJkiRJO7aQacYnJPm3JPcn2Zxka5J7pxFOkiRJkqTZLGSa8R8yujzPXwHrgNOB72kzlCRJkiRpN9iTpxkDVNUNSZZW1VZGl+f5TMu5JEmSJEkT2qPPmQUeTLICuDLJW4FNwKp2Y8HKG+5su4sdqru+1nWEkSXpOgEz9z+w4wdNw7IF/f2lVUsOWdN1BAC+9vSDuo7Apudu6ToCAN9z+MauI7Bm2SNdRwBg2ZKZriOwpAe/Nb933692HQGAQ/bq/vfIgzMruo4AwFP3vrnrCNw3s3fXEQB4zso7uo7AL9z0Y11HAOCKmw/tOgJbtvTj+2Lz6u4/7624b0FX7Wzd8vu6fy8Gpftfy61ZyHfszzaP+0XgAeBQ4KVthpIkSZIk7QZ78qV5quorSQ5s9t/UfiRJkiRJkuY358hsRn4zyZ3AF4EvJbkjyW9ML54kSZIkaVelJtv6bL5pxq8FngU8vaoeU1X7A98PPCvJL08jnCRJkiRpAgOeZjxfMXs68NNVdeO2hqr6MvCy5muSJEmSpB7bU0dml1fVdywpXFV3AMvbiyRJkiRJ0vzmWwBq8y5+TZIkSZLUBz0fXZ3EfMXsU5PcO0t7gH5ckEuSJEmSNLc9sZitqqXTDCJJkiRJ2r36ft7rJHZ4nVlJkiRJ0iI14GJ2vgWgJEmSJEnqJUdmJUmSJGmoBjwyazErSZIkSQPlObOSJEmSpMXHYlaSJEmStNgMeWTWBaAkSZIkSYuOI7OSJEmSNFQDHpm1mJUkSZKkobKYlSRJkiQtNuk6QIs8Z1aSJEmStOg4MitJkiRJQ+U0452X5EZmeeuq6olt9SlJkiRJ+pYhX5qnzZHZdWP7ewOnAgfM94Qk64H1AEcd+DwOfdRT20snSZIkSUM34GK2tXNmq+quse0/qur3gefu4DkbqmpdVa2zkJUkSZKkCdWEW4+1Oc342LG7SxiN1O7XVn+SJEmSpD1Hm9OMf3dsfwtwE/CTLfYnSZIkSRrjObO7oKp+qK3XliRJkiQtgMXszkuyF/BS4LDxfqrqt9rqU5IkSZL0LY7M7pqPAfcAlwMPt9iPJEmSJGk2FrO7ZG1VndTi60uSJEmS9lCtXZoH+EyS/9Ti60uSJEmS5pGabOuz3T4ym+RqYKZ57Z9P8mVG04wDVFU9ZXf3KUmSJEmaRc8L0km0Mc34EOCYFl5XkiRJkrQzBlzMtjHN+Maq+spcWwv9SZIkSZI6kGTvJJcm+VySa5K8qWk/IMn5Sa5vbvcfe85ZSW5Icl2S54+1H5fkquZrb0+S+fpuY2T2oCSvm+uLVfW2FvqUJEmSJG1nCue9Pgw8t6ruT7Ic+JcknwB+HLigqt6S5EzgTOANSY4ETgOOAh4PfDrJk6pqK/AOYD1wMfD/gJOAT8zVcRsjs0uBfYH95tgkSZIkSdNQE247evmR+5u7y5utgFOAc5r2c4AXN/unAB+sqoer6kbgBuD4JGuA1VV1UVUV8L6x58yqjZHZTVX1Wy28riRJkiRpJ6TaH5pNshS4HPge4P9W1SVJDq6qTQBVtSnJQc3DD2E08rrNxqbtkWZ/+/Y5tTEyO++8ZkmSJEnSlEw4MptkfZLLxrb139FF1daqOgZYy2iU9eh5Es1WL9Y87XNqY2T2xBZeU5IkSZI0ZVW1AdiwwMd+PcmFjM51vS3JmmZUdg1we/OwjcChY09bC9zatK+dpX1Ou31ktqru3t2vKUmSJEnaeanJth2+fnJgkkc3+yuBHwa+CJwHnNE87AzgY83+ecBpSfZKcjhwBHBpMyX5viQnNKsYnz72nFm1MTIrSZIkSeqD9k+ZXQOc05w3uwQ4t6o+nuQi4NwkrwBuBk4FqKprkpwLfAHYAryqWckY4JXAe4GVjFYxnnMlY7CYlSRJkqTBavvSPFX1eeBps7TfxRynoFbV2cDZs7RfBsx3vu23sZiVJEmSpKFqf2S2M22sZixJkiRJUqscmZUkSZKkgWp7mnGXLGbnkeX9eHvqoW90HYGa6cdPQbbOdB0BpnDh6YVIT/5P+mDtqnu6jsDmmaVdRwBg80z3x629lz7SdQTu37pX1xEAuO7Bx3UdgdXLuv8dAnDrlv27jsDjl32t6wgAPFLd/y7bZ9nmriMAMLN1tstKTtfyb3SfAWDJlq4TwNKH+/HZYtkD3f8eGZR+/Le2ovtPPZIkSZKkVgx5ZNZzZiVJkiRJi44js5IkSZI0VD05Ra4NFrOSJEmSNFBDnmZsMStJkiRJQ2UxK0mSJElabNL9AuqtcQEoSZIkSdKi48isJEmSJA2V04wlSZIkSYuNC0BJkiRJkhYfL80jSZIkSVpshjwy6wJQkiRJkqRFx5FZSZIkSRqqAY/MWsxKkiRJ0kANeZqxxawkSZIkDdWAF4DynFlJkiRJ0qLjyKwkSZIkDZTTjCVJkiRJi4/FrCRJkiRpsXFkVpIkSZK0+MwMt5ptdQGoJD+Q5Oeb/QOTHN5mf5IkSZKkPUNrI7NJ3gisA54MvAdYDrwfeFZbfUqSJEmSxgx3YLbVacYvAZ4GXAFQVbcm2a/F/iRJkiRJY4Z8zmyb04w3V1XR/C0gyaodPSHJ+iSXJbnslns+12I0SZIkSdoDVE229Vibxey5Sf4EeHSS/wZ8GnjnfE+oqg1Vta6q1h36qKe2GE2SJEmShi812dZnrU0zrqrfSfIjwL2Mzpv9jao6v63+JEmSJEl7jlYvzdMUrxawkiRJktSFno+uTqLN1Yzv41tv3QpGqxk/UFWr2+pTkiRJkvQt6fl5r5Noc5rxt61cnOTFwPFt9SdJkiRJ2s5M1wHas9sXgEoya4FcVX8NPHd39ydJkiRJ2vO0MTJ7KXBskh8fa1sCrGPQM7YlSZIkqV+cZrxrfoxvFa9bgJuAk1vsT5IkSZI0bri1bCvF7EFJXgdcvV17AT8LvK2FPiVJkiRJ23NkdqcsBfYF0sJrS5IkSZIWKMOtZVspZjdV1W+18LqSJEmSJAHtFLOOyEqSJElSHzjNeKec2MJrSpIkSZJ2UgZ8ndndXsxW1d27+zUlSZIkSbtgwCOzS7oOIEmSJEnSzmrzOrOSJEmSpC4Nd2DWYlaSJEmShioDnmZsMStJkiRJQzXgYtZzZiVJkiRpqGYm3HYgyaFJ/iHJtUmuSfKapv2AJOcnub653X/sOWcluSHJdUmeP9Z+XJKrmq+9Pcm8l321mJUkSZIk7aotwK9U1fcBJwCvSnIkcCZwQVUdAVzQ3Kf52mnAUcBJwB8lWdq81juA9cARzXbSfB1bzEqSJEnSQKVqom1HqmpTVV3R7N8HXAscApwCnNM87Bzgxc3+KcAHq+rhqroRuAE4PskaYHVVXVRVBbxv7DmzspiVJEmSpKGqmmhLsj7JZWPb+rm6SnIY8DTgEuDgqto0ilCbgIOahx0C3DL2tI1N2yHN/vbtc+rvAlBbtnSdAOafoj019Uj370WWLt3xg6Zg5uFvdB2BJd94uOsIACzZ3P3J/Ev37v57E+DeR/buOgIz1Y/jxeaZ7n9W913W/c/IYXvf1XUEAO7ZurLrCOy7tPvjJsBhy+/sOgKPW3p/1xEA2H9J98esvZb04/i9ZGn3v8u2rOo+A8Cy+7v/PTKzovsMALXM8bbdasIFoKpqA7BhR49Lsi/wYeC1VXXvPKe7zvaFmqd9Tv0tZiVJkiRJk1nAIk6TSrKcUSH751X1kab5tiRrqmpTM4X49qZ9I3Do2NPXArc27WtnaZ+Tf/aQJEmSJO2SZsXhdwPXVtXbxr50HnBGs38G8LGx9tOS7JXkcEYLPV3aTEW+L8kJzWuePvacWTkyK0mSJEkDtZBFnCb0LOBngauSXNm0/XfgLcC5SV4B3AycClBV1yQ5F/gCo5WQX1VVW5vnvRJ4L7AS+ESzzcliVpIkSZKGquVitqr+hdnPdwU4cY7nnA2cPUv7ZcDRC+3bYlaSJEmShqr9kdnOeM6sJEmSJGnRcWRWkiRJkoZqwCOzFrOSJEmSNFRTuDRPVyxmJUmSJGmgprCacWcsZiVJkiRpqAZczLoAlCRJkiRp0XFkVpIkSZKGama4I7MWs5IkSZI0VAOeZmwxK0mSJElDZTErSZIkSVp0BlzMugCUJEmSJGnRcWRWkiRJkobKBaAkSZIkSYtOzXSdoDUWs5IkSZI0VJ4zK0mSJElSfzgyK0mSJElD5TmzkiRJkqRFZ8DTjFspZpNcBcz5rlXVU9roV5IkSZI0xmJ2p72ouX1Vc/tnze3PAA/O9aQk64H1AEc95kQO3c+aV5IkSZJ22YCL2VYWgKqqr1TVV4BnVdWvVdVVzXYm8Px5nrehqtZV1ToLWUmSJEnSXNpezXhVkh/YdifJM4FVLfcpSZIkSQKYmZls67G2F4B6BfCnSR7F6Bzae4CXt9ynJEmSJAkGPc241WK2qi4HnppkNZCquqfN/iRJkiRJYwZczLY6zTjJwUneDfxlVd2T5Mgkr2izT0mSJElSY6Ym23qs7XNm3wv8HfD45v6XgNe23KckSZIkaeDaLmYfW1XnAjMAVbUF2Npyn5IkSZIkoGpmoq3P2l4A6oEkj2G0+BNJTmC0CJQkSZIkqW09nyo8iVaK2SSvBf4V+DXgY8ATk/wrcCBwaht9SpIkSZK2M+AFoNoamV0L/AHwvcAXgfOBCxktBHVnS31KkiRJkvYQrRSzVfV6gCQrgHXAM4HnAr+e5OtVdWQb/UqSJEmSxsz0+7zXSbR9zuxKYDXwqGa7Fbiq5T4lSZIkSeA0452VZANwFHAfcAnwGeBtVfW1NvqTJEmSJH2ncmR2pz0B2Au4HvgPYCPw9Zb6kiRJkiTNxpHZnVNVJyUJo9HZZwK/Ahyd5G7goqp6Yxv9SpIkSZL2DK2dM1tVBVyd5OuMri17D/Ai4HjAYlaSJEmS2uZ1ZndOkl9iNCL7LOARRtecvQj4U1wASpIkSZKmozxndmcdBnwI+OWq2tRSH5IkSZKkeZQjszunql7XxutKkiRJknbCgEdml3QdQJIkSZKkndXaAlCSJEmSpG45zViSJEmStPgMeJpxasAX0U2yvqo27OkZ+pKjDxn6kqMPGfqSow8Z+pKjDxn6kqMPGfqSow8Z+pKjDxn6kqMPGfqSow8Z+pKjDxn6kqMPGdS+oZ8zu77rAPQjA/QjRx8yQD9y9CED9CNHHzJAP3L0IQP0I0cfMkA/cvQhA/QjRx8yQD9y9CED9CNHHzJAP3L0IQP0I0cfMqhlQy9mJUmSJEkDZDErSZIkSVp0hl7M9mGefB8yQD9y9CED9CNHHzJAP3L0IQP0I0cfMkA/cvQhA/QjRx8yQD9y9CED9CNHHzJAP3L0IQP0I0cfMkA/cvQhg1o26AWgJEmSJEnDNPSRWUmSJEnSAA2ymE1yUpLrktyQ5MyOMvxpktuTXN1F/02GQ5P8Q5Jrk1yT5DUd5dg7yaVJPtfkeFMXOZosS5N8NsnHO8xwU5KrklyZ5LKOMjw6yYeSfLH5/nhGBxme3LwH27Z7k7y2gxy/3HxfXp3kA0n2nnaGJsdrmgzXTOt9mO04leSAJOcnub653b+jHKc278VMknUdZfg/zc/I55N8NMmjO8rx5ibDlUk+leTx084w9rXXJ6kkj20zw1w5kvxmkv8YO268cNoZmvZXN58zrkny1jYzzJUjyV+OvQ83JbmygwzHJLl42++zJMe3mWGeHE9NclHzu/VvkqxuOcOsn6+mefycJ8O0j51z5Zja8XOeDFM9dqojVTWoDVgK/DvwRGAF8DngyA5yPBs4Fri6w/diDXBss78f8KWO3osA+zb7y4FLgBM6ek9eB/wF8PEO/19uAh7bVf9NhnOA/9rsrwAe3XGepcBXge+acr+HADcCK5v75wI/18G//2jgamAfYBnwaeCIKfT7Hccp4K3Amc3+mcBvd5Tj+4AnAxcC6zrK8DxgWbP/2x2+F6vH9n8J+ONpZ2jaDwX+DvjKNI5hc7wXvwm8vu2+d5Dhh5qf0b2a+wd1kWO7r/8u8BsdvBefAl7Q7L8QuLCj/5N/A57T7L8ceHPLGWb9fDXN4+c8GaZ97Jwrx9SOn/NkmOqx062bbYgjs8cDN1TVl6tqM/BB4JRph6iqfwLunna/22XYVFVXNPv3Adcy+vA+7RxVVfc3d5c329RP1k6yFvhR4F3T7rtPmr9YPxt4N0BVba6qr3caCk4E/r2qvtJB38uAlUmWMSomb+0gw/cBF1fVg1W1BfhH4CVtdzrHceoURn/soLl9cRc5quraqrqu7b53kOFTzf8HwMXA2o5y3Dt2dxUtHz/n+f31e8Cvtd3/AnJMzRwZXgm8paoebh5ze0c5AEgS4CeBD3SQoYBto6CPYgrHzzlyPBn4p2b/fOClLWeY6/PV1I6fc2Xo4Ng5V46pHT/nyTDVY6e6McRi9hDglrH7G+mggOubJIcBT2M0KtpF/0ubKVC3A+dXVRc5fp/RB7GZDvoeV8CnklyepIsLej8RuAN4T0ZTrt+VZFUHOcadRssfxGZTVf8B/A5wM7AJuKeqPjXtHIxGZZ+d5DFJ9mE0wnFoBzkADq6qTTD6gAAc1FGOvnk58ImuOk9ydpJbgJ8BfqOD/k8G/qOqPjftvmfxi83UwT+dxjT4WTwJ+M9JLknyj0me3kGGcf8ZuK2qru+g79cC/6f53vwd4KwOMsDoGHpys38qUzx+bvf5qpPjZ9ef8RaQY2rHz+0zdH3sVPuGWMxmlrY9+i8xSfYFPgy8dru/Uk1NVW2tqmMY/WXu+CRHT7P/JC8Cbq+qy6fZ7xyeVVXHAi8AXpXk2VPufxmjKVrvqKqnAQ8wmg7ViSQrGH0I+asO+t6f0V/SDwceD6xK8rJp56iqaxlNwzof+CSj0yO2zPskTU2SX2f0//HnXWWoql+vqkObDL84zb6bP7D8Ov34IPgO4LuBYxj9Aep3O8iwDNgfOAH4VeDcZnS0Kz9NB38MbLwS+OXme/OXaWb8dODljH6fXs5omunmaXTah89XfcgwX45pHj9ny9DlsVPTMcRidiPf/he5tXQzbbAXkixn9IP951X1ka7zNNNZLwROmnLXzwJOTnITo6nnz03y/ilnAKCqbm1ubwc+ymhq/DRtBDaOjY5/iFFx25UXAFdU1W0d9P3DwI1VdUdVPQJ8BHhmBzmoqndX1bFV9WxGU+i6GGUBuC3JGoDmtvUplH2W5AzgRcDPVFUf/jD6F7Q8hXIW383oDz6fa46ha4ErkjxuyjmoqtuaP47OAO9k+sdPGB1DP9KcQnMpo9k+rS+INZvm9IgfB/6yi/6BMxgdN2H0B8ku/j+oqi9W1fOq6jhGhf2/t93nHJ+vpnr87MtnvLlyTPP4uYD3ootjp6ZgiMXsvwFHJDm8GfE5DTiv40ydaP5S/G7g2qp6W4c5Dty2il2SlYwKiC9OM0NVnVVVa6vqMEbfE39fVVMfgUuyKsl+2/YZLZAw1RWvq+qrwC1Jntw0nQh8YZoZttPlqMLNwAlJ9ml+Xk5kdK7N1CU5qLl9AqMPp129J+cx+oBKc/uxjnJ0LslJwBuAk6vqwQ5zHDF292Smf/y8qqoOqqrDmmPoRkaLrXx1mjngmwXCNi9hysfPxl8Dz23yPInRInp3dpADmt+nVbWxo/5vBZ7T7D+Xjv4IN3b8XAL8D+CPW+5vrs9XUzt+9ugz3qw5pnn8nCdDp8dOTcn2K0INYWN0vtmXGP1l7tc7yvABRlOgHmH0i/8VHWT4AUZTrD8PXNlsL+wgx1OAzzY5rqblFRcXkOcH6Wg1Y0bnq36u2a7p8PvzGOCy5v/kr4H9O8qxD3AX8KgOvx/exOgX3NXAn9GsUNpBjn9m9EeFzwEnTqnP7zhOAY8BLmD0ofQC4ICOcryk2X8YuA34uw4y3MBoDYZtx8/WV8KcI8eHm+/PzwN/w2hhk6lm2O7rNzGd1Yxney/+DLiqeS/OA9Z0kGEF8P7m/+QK4LldvBdN+3uBX2i7/3neix8ALm+OW5cAx3WU4zWMPvd9CXgLkJYzzPr5aprHz3kyTPvYOVeOqR0/58kw1WOnWzdbmm8CSZIkSZIWjSFOM5YkSZIkDZzFrCRJkiRp0bGYlSRJkiQtOhazkiRJkqRFx2JWkiRJkrToWMxKkhaNJPdvd//nkvxhV3kkSVJ3LGYlSXu8JEu7ziBJknaOxawkaRCSfFeSC5J8vrl9QtP+3iQ/Mfa4+5vbH0zyD0n+Ariqo9iSJGkXLes6gCRJO2FlkivH7h8AnNfs/yHwvqo6J8nLgbcDL97B6x0PHF1VN+7uoJIkqV0Ws5KkxeShqjpm250kPwesa+4+A/jxZv/PgLcu4PUutZCVJGlxcpqxJGmoqrndQvP7LkmAFWOPeWDaoSRJ0u5hMStJGorPAKc1+z8D/EuzfxNwXLN/CrB8urEkSVIbLGYlSUPxS8DPJ/k88LPAa5r2dwLPSXIp8P04GitJ0iCkqnb8KEmSJEmSesSRWUmSJEnSomMxK0mSJEladCxmJUmSJEmLjsWsJEmSJGnRsZiVJEmSJC06FrOSJEmSpEXHYlaSJEmStOhYzEqSJEmSFp3/Hz4DgeHsqld9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "sns.heatmap(dayHour, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "e00972e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x22c0c6cdca0>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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M6u63u7t3386yZyd5YJI3JDl9Cs/p7qur6u7TYvdM8vphtaumtlum67dt59BW4oCsjXJA15Yxy/621X7/M75RSLxZAI4BW3oEeQrDBwzEo6o6NcnLkjyzu687yPThA93RB2kHWEWzvTHdam8WAI7Elh5BPhxVdXwW4fg3u/t3p+ZrquqMafT4jCTXTu1XJTlrWP3MJB+a2s88QDsArJSjNLXtcByN6W+H4hOPgzAt7fatLyCv2AjyoUxnmviVJO/o7ucPd70yyZOSXDL9fMXQ/ltV9fwk98jiYLw3dvfeqrq+qh6SxRSNJyb5uaP03wCA9dgWU9uWYQUC+qozLe12rPOLQrbcCPJDk3x3krdU1Zunth/NIhhfWlVPSfKBJI9Lku5+W1VdmuTtWZwB42ndvXda76lJXpTkpCwOznOA3ibahBGSoz0SsuXffQPAVrXOEeStFZC7+y9z4PnDSXLe7axzcZKLD9C+J8n9l9c7Nmhbj5Bsh3ffALBVbfs5yAAAsB7rHEHee+hl4Bgy41SPuaZ0mLrBSlrSc2mjzxvPDyDJNp9iAUfBlprqYeoGK2zTn0ueH8B+plgAAMDAFAsAYOWsyLSbxNSbY9L6AnJvrfMgA8BWs4RguF1C4aZPu0lMvTlWmYMMW5xvQoJtZ9ODoVDIsW5dAblNsYBV5JuQANbBwAKHYg4yANuWIPQ5Hot/xsACB2UEGQZHMPdvu/8Rga1OEPocjwUcJnOQ4Z+bbe6fPyIAsDUYQQYAgIGADAAAg2rnNmadvuHBz5llpznuY9fNUTb7PvrxWerWjh3z1L3T581SN0nymc/OUva6r/miWep+6l7zPManXj3f6961585Te99J80xx2/nx9c20O1zvftILZ6l7U98yS90kOS41S92f/vh9Z6l7153Xz1L384//1Cx1k+Qvrr/PLHWvvvG0WeqetGOe/e1vP3LPWeomyd59x81S904n3TBL3ST500f8zDxPvg2Y51EEAIAtSkAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGOze7AwAAcCBVdVp3X1dVdz7Q/d398Tm2KyCvgLW1tQuT7Nrsfhyuu+SbNrsLAMA2UVUXJLlgaNrd3bun67+V5FFJLk/SSWpYrpPce44+CcirYdeePXsu2uxOHK5vePBznrPZfQAAtocpDO++nfseVVWV5Gu6+wNHq0/mIAMAsLK6u5O8/GhuU0AGAGDVvb6qvvxobcwUCwAAVt3XJvm+qroyyWeymIvc3f2lc2xMQAYAYCVV1b+Y5h4/8mhuV0AGAGBV/V6SB3X3+6vqZd39rUdjo+YgAwCwqsbTus1ySrcDEZABAFhVfTvXZ2WKBQAAq+rLquq6LEaST5quJ587SO+0OTYqIAMAsJK6e8dmbNcUCwAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGCwc7M7wNZz3HWfnafwiSfOU/fWW2cp27NUTXLdp+eqnBxXs5Tdu2ue99qnfHieR/mka2+ZpW6S7D11nsd45yfnebk+8ROzlM0n9t0wS9033XSHWeomyfX7ds1S94a9J8xSd+/OeZ5377np9FnqJsn7PnOXWeru63medzfvned598lPnTJL3SQ5+/SPzlL35J3zvW6uIiPIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAIDBzs3uAAAA3J6qel+Svm17d997rm0KyMeYtbW1C5Ps2kiNu+URS+oNAHCsq6oLklwwNO3u7t3D7bXh+q4kj0ty5zn7JCAfe3bt2bPnoo0UeOQ5P/KcJfUFADjGTWF490Hu/9htmv5rVf1lkp+Yq08CMgAAK6uqHjTcPC6LEeU7zLlNARkAgFX2M8P1W5NcmeTb59yggAwAwMrq7q892tsUkAEAWFlVdWKSb01ydobs2t0/Odc2BWQAAFbZK5J8KsnlSW46GhsUkAEAWGVndvf5R3ODvkkPAIBV9tdV9X8dzQ0aQQYAYOVU1VuT7Msir35vVb03iykWlaS7+0vn2raADADAKrpnkgdsxoYFZAAAVtH7uvv9m7FhARkAgFV096r6wdu7s7ufP9eGBWQAAFbRjiSnZjHn+KgSkAEAWEVXz/llIAfjNG8AAKyioz5yvJ+ADADAKjpvszYsIAMAsHK6++ObtW0BGQAABkd8kN7a2tqFSXYtsS/HsrM3uwMAACxs5CwWu/bs2XPRsjpyLFtbW7tos/sAAMCCKRYAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAw2LnZHWALuvXWeeru3TdP3ZrnfeC+G26Ype7OU0+ZpW6S7PvU9bPU3XHjPL+7vbvm+d3tuGnvLHWTZMeueer2jnlernumYZJT64RZ6p5Q8/3u7nfCNbPUff/Nd5ul7rW3nDZL3VN33DhL3SQ5dedNs9S99sZTZ6l71smfnKXunE47YZ7HeF/XLHVXlYC8Ta2trV2Y5EB/qs8+yl0BANhSBOTta9eePXsuum3j2tra/9EGAMDnmIMMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMdm52BwAA4Laq6i1J+vbu7+4vnWvbAvKx58a1tbWLNlLgbnnYkroCABzrquqCJBcMTbu7e3eSR023nzb9/PXp53cluWHOPgnIx5g9e/ZcstEaj7zXDz5nGX0BAJjC8O4DtL8/Sarqod390OGuC6vqr5L85Fx9MgcZAIBVdkpVffX+G1X1VUlOmXODRpABAFhlT0nyq1X1eVnMSf5UkifPuUEBGQCAldXdlyf5sqo6LUl196fm3qYpFgAArKyqOr2qfiXJb3f3p6rqvlX1lDm3KSADALDKXpTkj5LcY7r97iTPnHODAjIAAKvsrt19aZJ9SdLdtybZO+cGBWQAAFbZZ6rqLpm+NKSqHpLFgXqzcZAeAAArp6qemeSvkvxIklckufd0/uO7JXncnNsWkAEAWEVnJvnZJP8yyTuTvCbJZVkcrPfROTcsIAMAsHK6+4eSpKpOSLKW5KuSPCLJj1XVJ7v7vnNtW0AGAGCVnZTktCSfN10+lOQtc25QQAYAYOVU1e4k90tyfZI3JPnrJM/v7k/MvW1nsQAAYBX9iyQnJvlwkn9MclWSTx6NDRtBBgBg5XT3+VVVWYwif1WS/5Dk/lX18SSv6+7nzLVtARkAgJXU3Z3krVX1ySzOffypJI9Kcm4SARkAgGNHVX1/FiPHD01ySxbnRH5dkl+Ng/QAADgGnZ3kd5L8QHdffTQ3LCADALByuvsHN2vbzmIBAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAg52b3QG2nr7DyfMU3tvz1P3Yx2cpu+PUU2epm53zPS1r14kzFa5Zyu64cd8sdY+76dZZ6ibJ3ht3zVL3xE/P8xgf/+lZyuYPP3vaLHWv2zvP45sk1+69wyx1r7llnsfiozfP8xq0s/bOUndOu3bM85y+5sZ59om9N+6YpW6S7Kx5XjfvsmumF4sVJSCvhhvX1tYuWnLNs5dcDwDgmCAgr4A9e/ZcsuyaMwRuAIBjgjnIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAA205VPfIAbd93OOsKyAAAbEf/saoesf9GVT0ryWMOZ0VfFAIAwHb06CS/X1U/nOT8JP9yajskARkAgG2nuz9aVY9O8sdJLk/ybd3dh7OugAwAwLZRVdcnGYPwCUnuneTbqqq7+7RD1RCQAQDYNrr7Dhut4SA9AAC2nVp4QlX9x+n2WVV17uGsKyADALAd/UKSr0zyf0+3P53kvx3OiqZYAACwHX1Fdz+oqv42Sbr7E1V1wuGsaAQZAIDt6Jaq2pHpgL2quluSfYezooAMAMB29IIkL09yelVdnOQvk/y/h7OiKRYAAGw73f2bVXV5kvOSVJLHdvc7DmddI8gAAGxXd01yQ3f/fJKPVtW9DmclARkAgG2nqp6T5FlJnj01HZ/kNw5nXQEZAIDt6JuTPDrJZ5Kkuz+U5LC+RERABgBgO7q5uzufO4vFKYe7ooAMAMB2dGlV/WKSO1bVv0vyx0l+6XBWdBYLAAC2jaq6U3d/ort/uqq+Lsl1Se6T5Ce6+zWHU0NABgBgO3lXVX0kyV8n+askv9Td715PAVMsAADYNrr77lkcoPdXSb4qye9W1TVV9Yqq+pHDqWEEGQCAbWUaMX53khdV1Rcm+cYkz0jy9Umed6j1BWQAALaNqvqqLEaOvzLJWUnem+T1SZ6Q5E2HU0NABgBgO/nLLILw85P8XnffsN4CAjIAANvJPbIYQf6qJN9XVTuzCMyvS/K67n7voQoIyAAAbBvd/eEkvztdUlUnJ3lykucmuVeSHYeqISADALBtVNXnZTH/eP8o8gOTXJHkf2VxZotDEpABANhOrsjioLy/TvJTSd7Y3Z9dTwEBGQCAbaO777bRGr4oBAAABkaQAQBYeVW1I8npGfJrd39gjm0JyMeQtbW1C5Ps2midu+b8JfQGACCpqguSXDA07e7u3bdZ5ulJnpPkmiT7puZO8qUHqPefuvtZVfW47v6fR9InAfnYsmvPnj0XbbTI+V/6489ZQl8AADKF4d2HWOwZSe7T3R87jJLfWFU/nuTZSQRkAAC2pQ8m+dRhLvuHST6a5JSqui5JZTHaXEm6u087VAEBGQCAVffeJJdV1f9OctP+xu5+/m0X7O4fTvLDVfWK7n7MkWxMQAYAYNV9YLqcMF0OqbsfU1WnJ/nyqekN3f2Rw1lXQAYAYKV193OTpKrusLjZnz7UOlX1uCQ/neSyLKZX/FxV/XB3/86h1hWQAQBYaVV1/yS/nuTO0+2PJnlid7/tIKv9eJIv7+5rp3XuluSPkxwyIPuiEAAAVt3uJD/Y3V/Q3V+Q5D8k+aVDrHPc/nA8+VgOM/saQQYAYNWd0t1/uv9Gd19WVaccYp0/rKo/SvKS6fZ3JPmDw9mYgAwAwKp7b1X9xyymWSTJE5K872ArdPcPV9W3JPnqLOYg7+7ulx/OxgRkAABW3ZOTPDfJ72YRdv88yfceaqXu/t1pnXURkAEAWGnd/Ykk33+0ticgAwCwkqrqlQe7v7sfPcd2BWQAAFbVV2bxNdMvSfKGLKZXHJaqelSSP+jufevdqNO8AQCwqj4/yY8muX+Sn03ydUk+2t1/1t1/doh1H5/kPVX1vKr6kvVsVEAGAGAldffe7v7D7n5SkockuSLJZVX19MNY9wlJHpjkH5L8j6p6XVVdMH0b30EJyAAArKyqOnE6XdtvJHlakhfkMM9M0d3XJXlZkpcmOSPJNyd506ECtjnIAACspKp6cRbTK16V5Lnd/dZ1rPtvsjg93Bdmcf7kc7v72qo6Ock7kvzc7a0rIAMAsKq+O8lnknxxku+v+qdj9CpJd/dpB1n3cUn+S3f/+djY3TdU1ZMPtlEBGQCAldTdRzwduLufeJD7Xnuwdc1BBgBg26mqh1TV31TVp6vq5qraW1XXHc66AjIAANvRzyf5ziTvSXJSkn+bg8w7HpliAQDAttTdV1TVju7em8Wp3v76cNYTkAEA2I5uqKoTkry5qp6X5OokpxzOiqZYAACwHX13Fln332dxJoyzknzr4axoBBkAgG2nu99fVXebrj93PesaQQYAYNuohYuq6qNJ3pnk3VX1kar6icOtISADALCdPDPJQ5N8eXffpbvvlOQrkjy0qn7gcAoIyAAAbCdPTPKd3f2+/Q3d/d4kT5juOyQBGQCA7eT47v7obRu7+yNJjj+cAgIyAADbyc1HeN8/cRYLAAC2ky+7na+UriS7DqeAgAwAwLbR3Ts2WsMUCwAAGAjIAAAwEJABAGAgIAMAwEBABgCAgbNYbF83rq2tXXSbtrOXUbg+e1inEDyCwjVL2X233DpL3ezrWcrWLbfMUjdJsnfvLGX3HdZp19evbp1nn+gdW3BsYJ6HIvtOmKfuV5x47Sx1/+iGs2epmyR3PO6GWep+du88T5BTdtw0S93Tdt44S90kee8Nd52l7nE1z+vxacfP81jU8ftmqZskJ++c52/0p245aZa6q0pA3qb27NlzyW3bDhCYAQC4jS04jAIAAPMRkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADALDSquqrq+p7p+t3q6p7zbk9ARkAgJVVVc9J8qwkz56ajk/yG3Nuc+ecxVk5N66trV200SJ3yyOW0BUAgKSqLkhywdC0u7t3D7e/OckDk7wpSbr7Q1V1hzn7JCAfQ/bs2XPJMuo88pwfec4y6gAATGF490EWubm7u6o6SarqlLn7ZIoFAACr7NKq+sUkd6yqf5fkj5P80pwbNIIMAMDK6u6frqqvS3Jdkvsk+Ynufs2c2xSQAQBYaVMgnjUUjwRkAABWVlVdn6SnmydkcRaLz3T3aXNtU0AGAGBldfc/O2NFVT02yblzbtNBegAArJyqOuBAbnf/XjLvOWeNIAMAsIremORBVfUtQ9txSdbyuSkXsxCQAQBYZf8mnwvEtya5Msmj59yggAwAwCq6e1X9YJK33qa9k3x3kufPtWEBGQCAVbQjyalJ6mhvWEAGAGAVXd3dP7kZG3YWCwAAVtFRHzneT0AGAGAVnbdZGxaQAQBYOd398c3atoAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGCwc7M7wNZzwzl3naXuyW/5x1nq7jj9brPUzY03zVJ27xecMUvdJDnuxptnqft5b/3ELHU//DV3maXuLaeePEvdJDn75XtnqfvBr9s3S90+bp5xkm97xxNmqdtds9RNkqqepe5Zp35ylrqfvPmkWerurHn2tSQ5bqbH+L0fn+e1Yq59YucJ87xOJMnlv3P/Wep++gvn63MeMl/pI2UEGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAACsrKo68XDalklABgBglb3uMNuWZuecxbeztbW1C5Ps2ux+bIZT7v7tm90FAGCbqKoLklwwNO3u7t1V9flJ7pnkpKp6YJKa7j8tyclz9klAPnK79uzZc9Fmd2IzfM03Pu85m90HAGB76O7dSXYf4K5vSPI9Sc5M8vyh/fokPzpnnwRkAABWTne/OMmLq+pbu/tlR3PbAjIAACuru19WVd+U5H4Zprd290/OtU0H6QEAsLKq6r8n+Y4kT89iHvLjknzBnNsUkAEAWGVf1d1PTPKJ7n5ukq9MctacGxSQAQBYZZ+dft5QVfdIcmuSe825QXOQAQBYZb9fVXdM8rwkl09tvzznBgVkAABWTlV9eZIPdvdPTbdPTfKWJO9M8l/m3LYpFgAArKJfTHJzklTVw5JcMrV9Kgc+b/LSGEEGAGAV7ejuj0/XvyOLb9h7WZKXVdWb59ywEWQAAFbRjqraP5h7XpI/Ge6bdZDXCDIAAKvoJUn+rKo+msWZLP4iSarqi7KYZjEbARkAgJXT3RdX1WuTnJHk1d3d013HZfGlIbMRkAEAWEnd/foDtL177u2agwwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAYOdmd4Ctp3qmwrfcMk/dE06Yp+5xNUvZPn7G9603z1O7PnPjLHVP/dDeWeqecN2ts9RNkn075tkvjv/UPC/XJ189S9lcdcZd5ik81+tPkhw3T/GP3eGUWere9NnjZ6l73M59s9RNkls+Pc/rcd00z2tbnzDPY7HjMztmqZskuz4+z358y6nz9XkVbeQV98a1tbWLltWRLejsze4AAADLd8QBec+ePZcssyNbzTH+5gAAYNsyBxkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYCMgAADAQkAEAYCAgAwDAQEAGAICBgAwAAAMBGQAABgIyAAAMdm52BwAA4GCqakeS0zNk1+7+wFzbE5ABAFhZVfX0JM9Jck2SfVNzJ/nSubYpIB+5G9fW1i7a7E5shlPv9u2b3QUAYJuoqguSXDA07e7u3cPtZyS5T3d/7Gj1SUA+Qnv27Llks/uwWR7+yOc9Z7P7AABsD1MY3n2QRT6Y5FNHqTtJBGQAAFbbe5NcVlX/O8lN+xu7+/lzbVBABgBglX1gupwwXWYnIAMAsLK6+7lHe5sCMgAAK6uq/jSLs1b8M939iLm2KSADALDKfmi4vivJtya5dc4NCsgAAKys7r78Nk1/VVV/Nuc2BWQAAFZWVd15uHlckrUknz/nNgVkAABW2eX53BzkW5NcmeQpc25QQAYAYOVU1Zcn+WB332u6/aQs5h9fmeTtc277uDmLAwDAEfrFJDcnSVU9LMn/l+TFWXyr3sG+eW/DjCADALCKdnT3x6fr35Fkd3e/LMnLqurNc27YCDIAAKtoR1XtH8w9L8mfDPfNOshrBBkAgFX0kiR/VlUfTfLZJH+RJFX1RVlMs5iNgAwAwMrp7our6rVJzkjy6u7efyaL45I8fc5tC8gAAKyk7n79AdrePfd2zUEGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADAAAAwEZAAAGAjIAAAwEZAAAGAjIAAAwEJABAGAgIAMAwEBABgCAgYAMAAADARkAAAYCMgAADARkAAAYdbeLy2yXJBeouzX7vNXqbsU+b7W6W7HPW63uVuzzVqu7Ffus7tG/GEFmbheoO3ttdeevre78tdWdv7a689dWd966R42ADAAAAwEZAAAGAjJz263u7LXVnb+2uvPXVnf+2urOX1vdeeseNTVNpgYAAGIEGQAA/hkBGQAABgIys6iq86vqXVV1RVVduOTaV1bVW6rqzVW1Z0k1d1XVG6vq76rqbVX13GXUHervqKq/rarfX2LNX62qa6vqrcuqOdU9q6r+tKreMT0Wz1hi7TtW1e9U1Tun+l+5zD5W1X+eav99Vb28qu64pLo/NdV8c1W9uqrucST9HrZzn6nW/st1VfXMI6x1e32+c1W9pqreM/2805LqPm66va+q1o6wz//HvltVvz08HldW1ZuXVPeiqvrHofY3LqPu1P706XXubVX1vCX1d0P78CFqb3g/PtjrTlX9UFV1Vd11Sf2da1/b0HPjELUfUFWvnx7jPVV17pLqfllVva4Wf/v+V1WddiR9vs12fmB6fN9aVS+pql0brTnVfcZU821H+rq2Ejb7RMwu2++SZEeSf0hy7yQnJPm7JPddYv0rk9x1yX2uJKdO149P8oYkD1li/R9M8ltJfn+JNR+W5EFJ3rrkx+KMJA+art8hybuX9ftL8uIk/3a6fkKSOy6zj0m+PsnOqf0/JflPS6p72rDM9yf570t8vHck+XCSL1jyY/G8JBdO7Rcu8bH4kiT3SXJZkrU59t0kP5PkJ5ZRN8lFSX5og7+jA9X92iR/nOTE6fbdl1R3Q/vwIWpveD++vd9dkrOS/FGS9+cIXp9vp7+z7GsbfW4covarkzxyuv6NSS5bUt2/SfI10/UnJ/mpDe7T90zyviQnTbcvTfI9G6k51bl/krcmOTnJzuk5cs5G627GxQgyczg3yRXd/d7uvjnJS5M8ZpP7dFC98Onp5vHTZSlHsFbVmUm+KckvL6Peft3950k+vsyaU92ru/tN0/Xrk7wjixfTDZlGPB6W5Fem2jd39yeX2cfufnV33zot9vokZy6p7nXDYqdkSfvG5Lwk/9Dd7z+SlQ/y+3pMFm9IMv187DLqdvc7uvtdR9LXofbt7rtVVUm+PclLlll3I26n7lOTXNLdN03LXLuMuhvdhw9Re8P78UEe4/+S5EeOpObt1Z1xX9vQc+MQtTvJ/tHdz0vyoSXVvU+SP5+uvybJt6637gHsTHJSVe3MItCuu68H8CVJXt/dN0z78Z8l+eYl1D3qBGTmcM8kHxxuX5UlBKxBJ3l1VV1eVUv7tp5aTIN4c5Jrk7ymu9+wpNL/NYs/HPuWVO+oqaqzkzwwixH1jbp3ko8k+R+1mG7yy1V1ykaLHqSPT07yqmXVraqLq+qDSb4ryU8cad0DeHyOIAweyG36fHp3X50swm6Suy+p7tz+VZJruvs9S6z576epBb96pB+nH8AXJ/lXVfWGqvqzqvryJdUdbWgfPpA59uOqenSSf+zuv1tGvaNgac+NA3hmkv88PcY/neTZS6r71iSPnq4/LosR+yPW3f+YRf8+kOTqJJ/q7ldvqIcLb03ysKq6S1WdnMUo+ob6ulkEZOZQB2hb5ojbQ7v7QUkemeRpVfWwZRTt7r3d/YAsRmzOrar7b7RmVT0qybXdfflGax1tVXVqkpcleeZtRp6O1M4sPjZ8YXc/MMlnsvh484jdXh+r6seS3JrkN5dVt7t/rLvPmmr++430e9jOCVn80fufS6i17N/XrHUP4juzpDcMkxcm+cIkD8giCPzMkuruTHKnJA9J8sNJLp1Gv5dio/vw7Vn2fjyFoB/Lct80bmVPTfID02P8A5k+MVuCJ2fx9+7yLKY83byRYtMbxcckuVeSeyQ5paqesNFOdvc7spga9Jokf5jFFMtbD7rSihKQmcNV+efvGM/Mcj66SZJ094emn9cmeXkWUzqWZvrY/7Ik5y+h3EOTPLqqrsxiqskjquo3llB3VlV1fBah6De7+3eXVPaqJFcNI/O/k0VgPiK318eqelKSRyX5rp4mxS2j7uC3spyPN5PFm7w3dfc1GylyO32+pqrOmO4/I4tPRpZRdzbTR73fkuS3l1Wzu6+Z3vzuS/JLWd7rxVVJfneanvXGLD4hWvfBaQey0X34MC1rP/7CLELW302vc2cmeVNVff4Sas9lw8+Ng3hSkv3Plf+ZJe1v3f3O7v767n5wFm8g/2GDJf91kvd190e6+5Ys+vxVG+1nknT3r3T3g7r7YVlMFVnmp0FHjYDMHP4myTlVda9phOzxSV65jMJVdUpV3WH/9SwOaNnwWRyq6m41HS1eVSdl8eLxzo3W7e5nd/eZ3X12Fo/Dn3T3ht+lz2kaBfuVJO/o7ucvq253fzjJB6vqPlPTeUnefiS1bq+PVXV+kmcleXR337DEuucMiz06S9g3JhseLT3I7+uVWfyxzvTzFUuqO6d/neSd3X3VsgruD0KTb84SXi8mv5fkEdM2vjiLg04/utGiG92HD1F76ftxd7+lu+/e3WdPr3NXZXFw54c3WntGG3puHMKHknzNdP0RWVI4rKq7Tz+PS/LjSf77Bkt+IMlDqurk6bl+XhbHGWzY0Nd/kcUb3mV+InT03PaoPReXZVyymHf07ize5f7YEuveO4uPbP4uyduWVTvJlyb52yR/n8Uf0HUfQX8Y23h4lnsWi5dk8ZHxLVn8UXrKkup+dRZTYv4+yZunyzcuqfYDkuyZav9ekjsts49Jrshi/vv+tnUdpX+Qui+b9ou/T/K/sjhYbaOPxclJPpbk8+b4fSW5S5LXZvEH+rVJ7rykut887W83JbkmyR8ta99N8qIk37fM50SSX0/ylun/8cokZyyp7glJfmPaL96U5BFLqruhffgQtTe8H9/e7264/8oc2VksDtTfWfa1jT43DlH7q5NcnsXfqDckefCS6j4ji7+p705ySaZvQt7IJclzs3iT9NbpeXLiRmtOdf8ii8GPv0ty3jJqbsbFV00DAMDAFAsAABgIyAAAMBCQAQBgICADAMBAQAYAgIGADMBhq6pP3+b291TVz29WfwDmICADsOmqasdm9wFgPwEZgKWoqi+oqtdW1d9PP//F1P6iqvq2YblPTz8fXlV/WlW/lcWXeQCshJ2b3QEAtpSTqurNw+0753NfJf/zSX6tu19cVU9O8oIkjz1EvXOT3L+737fsjgIcKQEZgPX4bHc/YP+NqvqeJGvTza9M8i3T9V9P8rzDqPdG4RhYNaZYADCXnn7emunvTVVVkhOGZT5ztDsFcCgCMgDL8tdJHj9d/64kfzldvzLJg6frj0ly/NHtFsD6CMgALMv3J/neqvr7JN+d5BlT+y8l+ZqqemOSr4hRY2DFVXcfeikAADhGGEEGAICBgAwAAAMBGQAABgIyAAAMBGQAABgIyAAAMBCQAQBg8P8DwtW78m2aoZ0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(dayHour, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "e5686e4f",
   "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>Month</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day of Week</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>9309</td>\n",
       "      <td>8255</td>\n",
       "      <td>10941</td>\n",
       "      <td>7997</td>\n",
       "      <td>8904</td>\n",
       "      <td>9207</td>\n",
       "      <td>8681</td>\n",
       "      <td>7336</td>\n",
       "      <td>7694</td>\n",
       "      <td>6934</td>\n",
       "      <td>8379</td>\n",
       "      <td>9305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mon</th>\n",
       "      <td>8896</td>\n",
       "      <td>8747</td>\n",
       "      <td>8060</td>\n",
       "      <td>8410</td>\n",
       "      <td>7881</td>\n",
       "      <td>8511</td>\n",
       "      <td>9499</td>\n",
       "      <td>6854</td>\n",
       "      <td>6598</td>\n",
       "      <td>8075</td>\n",
       "      <td>6722</td>\n",
       "      <td>8492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>8475</td>\n",
       "      <td>7593</td>\n",
       "      <td>8050</td>\n",
       "      <td>7514</td>\n",
       "      <td>7223</td>\n",
       "      <td>8198</td>\n",
       "      <td>7748</td>\n",
       "      <td>6111</td>\n",
       "      <td>6566</td>\n",
       "      <td>6609</td>\n",
       "      <td>6773</td>\n",
       "      <td>8592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>7478</td>\n",
       "      <td>6452</td>\n",
       "      <td>6766</td>\n",
       "      <td>6865</td>\n",
       "      <td>6694</td>\n",
       "      <td>6837</td>\n",
       "      <td>7859</td>\n",
       "      <td>5275</td>\n",
       "      <td>5956</td>\n",
       "      <td>6316</td>\n",
       "      <td>5196</td>\n",
       "      <td>7165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thu</th>\n",
       "      <td>9055</td>\n",
       "      <td>7997</td>\n",
       "      <td>8849</td>\n",
       "      <td>7722</td>\n",
       "      <td>8740</td>\n",
       "      <td>9489</td>\n",
       "      <td>8378</td>\n",
       "      <td>7508</td>\n",
       "      <td>6954</td>\n",
       "      <td>7482</td>\n",
       "      <td>8358</td>\n",
       "      <td>8151</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Month          1     2      3     4     5     6     7     8     9     10  \\\n",
       "Day of Week                                                                \n",
       "Fri          9309  8255  10941  7997  8904  9207  8681  7336  7694  6934   \n",
       "Mon          8896  8747   8060  8410  7881  8511  9499  6854  6598  8075   \n",
       "Sat          8475  7593   8050  7514  7223  8198  7748  6111  6566  6609   \n",
       "Sun          7478  6452   6766  6865  6694  6837  7859  5275  5956  6316   \n",
       "Thu          9055  7997   8849  7722  8740  9489  8378  7508  6954  7482   \n",
       "\n",
       "Month          11    12  \n",
       "Day of Week              \n",
       "Fri          8379  9305  \n",
       "Mon          6722  8492  \n",
       "Sat          6773  8592  \n",
       "Sun          5196  7165  \n",
       "Thu          8358  8151  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dayMonth = df.groupby(by=['Day of Week','Month']).count()['Reason'].unstack()\n",
    "dayMonth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "a2c7fbf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Month', ylabel='Day of Week'>"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.heatmap(dayMonth, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "10c3c205",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x22c0d65cb20>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(dayMonth, cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "057b5c41",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}