6. Python 101 - Files - Skeleton before filming.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iLfi8gKMoAd6"
   },
   "source": [
    "# 1. TEXT FILES"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "r2IjrNQmoFxC"
   },
   "source": [
    "- open() is the key function to handle files \n",
    "- open() function takes two parameters: (1) filename (2) mode.\n",
    "- Modes for files opening: \n",
    "\n",
    "    - \"r\" - Read - Default value. Opens a file for reading, error if the file does not exist\n",
    "    - \"a\" - Append - Opens a file for appending, creates the file if it does not exist\n",
    "    - \"w\" - Write - Opens a file for writing, creates the file if it does not exist\n",
    "    - \"x\" - Create - Creates the specified file, returns an error if the file exists\n",
    "\n",
    "- files can be used in a binary or text mode\n",
    "\n",
    "    - \"t\" - Text - Default value. Text mode\n",
    "    - \"b\" - Binary - Binary mode (e.g. images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 32081,
     "status": "ok",
     "timestamp": 1602741398312,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "xEbqa95ArXlE",
    "outputId": "1c88d6aa-56ab-4591-d6c5-0d1833e9e141"
   },
   "outputs": [],
   "source": [
    "# In order to access data on Google Drive, you need to mount the drive to access it's content\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "executionInfo": {
     "elapsed": 2627,
     "status": "ok",
     "timestamp": 1602741684717,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "zqk6rO37oC_g",
    "outputId": "2ece1ca1-c5df-4c9a-cf87-8640ae4eda0d"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "First Name,Last Name,Email,Postal Code,Net Worth\nJoseph,Patton,daafeja@boh.jm,M6U 5U7,\"$2,629.13 \"\nNoah,Moran,guutodi@bigwoc.kw,K2D 4M9,\"$8,626.96 \"\nNina,Keller,azikez@gahew.mr,S1T 4E6,\"$9,072.02 \"\n\n"
     ]
    }
   ],
   "source": [
    "# Open and read text file\n",
    "f=open('G:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\sample_text_file.txt','r')\n",
    "print(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "executionInfo": {
     "elapsed": 1377,
     "status": "ok",
     "timestamp": 1602741870902,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "m1596TUCoInJ",
    "outputId": "eb1672cf-69e2-417a-9b35-c50be6299333"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am learning python now!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# readline will be used to read the first line\n",
    "f=open('D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\sample_text_file.txt','r')\n",
    "print(f.readline())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 1442,
     "status": "ok",
     "timestamp": 1602741943800,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "-2Y52n0UoIpX",
    "outputId": "9b83b943-d14e-4080-9fe0-f633934aca59"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "44"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# You can open the file and append content to it\n",
    "f=open('D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\sample_text_file.txt','a')\n",
    "f.write('THis is a new line that I added to the file!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "executionInfo": {
     "elapsed": 1394,
     "status": "ok",
     "timestamp": 1602742017228,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "6twyC3vfoIrU"
   },
   "outputs": [],
   "source": [
    "# close the file and let's check its content\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "executionInfo": {
     "elapsed": 1305,
     "status": "ok",
     "timestamp": 1602742071730,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "sEQ6zDLaoOga"
   },
   "outputs": [],
   "source": [
    "# Let's open the updated file after writing new content to it\n",
    "with open('D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\sample_text_file.txt','r') as f:\n",
    "  text_data= f.readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "executionInfo": {
     "elapsed": 1363,
     "status": "ok",
     "timestamp": 1602742080872,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "HqnHR33noOiZ",
    "outputId": "f5166af2-7ce6-4827-9935-ab66f03d0f38"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['I am learning python now!\\n',\n",
       " 'It is super fun to learn Python programming \\n',\n",
       " 'I am learning how to handle files in python!THis is a new line that I added to the file!THis is a new line that I added to the file!THis is a new line that I added to the file!THis is a new line that I added to the file!THis is a new line that I added to the file!THis is a new line that I added to the file!THis is a new line that I added to the file!']"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "executionInfo": {
     "elapsed": 1586,
     "status": "ok",
     "timestamp": 1602743298526,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "GJAfep33oOke",
    "outputId": "1f85d038-7c48-47c3-e41c-1f03bd6d2f6b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['I', 'am', 'learning', 'python', 'now!']\n",
      "['It', 'is', 'super', 'fun', 'to', 'learn', 'Python', 'programming']\n",
      "['I', 'am', 'learning', 'how', 'to', 'handle', 'files', 'in', 'python!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!THis', 'is', 'a', 'new', 'line', 'that', 'I', 'added', 'to', 'the', 'file!']\n"
     ]
    }
   ],
   "source": [
    "# split into a list of words\n",
    "for line in text_data:\n",
    "  words=line.split()\n",
    "  print(words)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_9ihcna1v0Y9"
   },
   "source": [
    "**MINI CHALLENGE #1:**\n",
    "- **Read the file 'fruits_input.txt'**\n",
    "- **compare the text file content to the list my_fruits = [\"Apple\", \"Pepper\", \"Orange\", \"Watermelon\", \"Tomatoes\"]**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 1636,
     "status": "ok",
     "timestamp": 1602744452990,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "FwqzbVBhx5Se",
    "outputId": "3dc3de15-7d04-4275-fe10-56b41891a75c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Apple', 'Watermelon', 'Orange']\n"
     ]
    }
   ],
   "source": [
    "my_fruits = [\"Apple\", \"Pepper\", \"Orange\", \"Watermelon\", \"Tomatoes\"]\n",
    "with open('D:\\Python+for+Financial+Analysis+-+Course+Package/Part 1. Python Programming Fundamentals/fruits_input.txt','r') as f:\n",
    "  all_fruits= f.readlines()\n",
    "all_fruits=[char.rstrip('\\n') for char in all_fruits]\n",
    "selected_fruits=[i for i in all_fruits if i in my_fruits]\n",
    "print(selected_fruits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mVEBiOmtnCp4"
   },
   "source": [
    "# 2. CSV FILES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "executionInfo": {
     "elapsed": 2075,
     "status": "ok",
     "timestamp": 1602747931723,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "C6-0bqrqmZS-"
   },
   "outputs": [],
   "source": [
    "# you can read csv files using \"csv.reader\"\n",
    "import csv\n",
    "with open('D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\sample_csv_file.csv','r') as f:\n",
    "  readCSV=csv.reader(f,delimiter=',')\n",
    "  data=list(readCSV)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "executionInfo": {
     "elapsed": 1339,
     "status": "ok",
     "timestamp": 1602747941229,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "JlyWKV6fmng9",
    "outputId": "45117899-0fc1-4cde-ec3d-b40fc165c2e8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['first', ' last', ' email', ' postal', ' gender', ' dollar'],\n",
       " ['Joseph', 'Patton', 'daafeja@boh.jm', 'M6U 5U7', 'Male', '$2,629.13 '],\n",
       " ['Noah', 'Moran', 'guutodi@bigwoc.kw', 'K2D 4M9', 'Male', '$8,626.96 '],\n",
       " ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 ']]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's view the data\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 1421,
     "status": "ok",
     "timestamp": 1602748004475,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "SuYdDHQpnZxL",
    "outputId": "b7ce0d6d-91e2-444d-d9e1-4a65b1301290"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['first', ' last', ' email', ' postal', ' gender', ' dollar']"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's view the first row\n",
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 1657,
     "status": "ok",
     "timestamp": 1602748016168,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "iPiq2lkMnbjW",
    "outputId": "cdf8af7f-f247-4fd4-d4bd-5568bf04e001"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Joseph', 'Patton', 'daafeja@boh.jm', 'M6U 5U7', 'Male', '$2,629.13 ']"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's view the second row\n",
    "data[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 1649,
     "status": "ok",
     "timestamp": 1602752182310,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "1EbBeptqm1XY",
    "outputId": "2c9b7307-07cc-407d-fc43-0407e68956a5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Joseph Patton', 'Noah Moran', 'Nina Keller']\n"
     ]
    }
   ],
   "source": [
    "# Combine first and last names together to generate full_name\n",
    "full_name=[]\n",
    "for i in data[1:4]:\n",
    "  full_name.append(i[0]+\" \"+i[1])\n",
    "print(full_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "executionInfo": {
     "elapsed": 3263,
     "status": "ok",
     "timestamp": 1602753203411,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "gD3H86PLm3FO",
    "outputId": "fcb4b92a-d78d-48d9-cea6-15da9de37ca6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[' dollar', '$2,629.13 ', '$8,626.96 ', '$9,072.02 ']\n"
     ]
    }
   ],
   "source": [
    "dollar=[]\n",
    "for r in data:\n",
    "  dollar.append(r[5])\n",
    "print(dollar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "cjLRTZfcm5_I"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "wTXefzJAm6Wv"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fxYxNeqJxEmR"
   },
   "source": [
    "**MINI CHALLENGE #2:**\n",
    "- **Read the CSV file entitled \"S&P500_Stock_data.csv\" and print out the heading**\n",
    "- **Print out the first 5 rows of data**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "executionInfo": {
     "elapsed": 1591,
     "status": "ok",
     "timestamp": 1602756377521,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "yzmHo9AHxhff",
    "outputId": "5c6cc009-5aa2-4a83-b4d6-f8570bc8752f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Interest Rates', 'Employment', 'S&P 500 Price']\n",
      "[['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '], ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '], ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '], ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 ']]\n"
     ]
    }
   ],
   "source": [
    "with open('D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\S_P500_Stock_Data.csv') as f:\n",
    "  CSV=list(csv.reader(f,delimiter=','))\n",
    "print(CSV[0])\n",
    "s=[]\n",
    "for row in CSV[1:5]:\n",
    "  s.append(i)\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "executionInfo": {
     "elapsed": 1374,
     "status": "ok",
     "timestamp": 1602756412354,
     "user": {
      "displayName": "Kishalay Pandey",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj2tFsmd8Ez-c0OPNkR8sUrBNBZ7p7l6gLebnZE=s64",
      "userId": "15833743162450854740"
     },
     "user_tz": -330
    },
    "id": "QP6oNliEue8E",
    "outputId": "85f85167-62d9-411a-8031-5f8686280d34"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '],\n",
       " ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '],\n",
       " ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 '],\n",
       " ['Nina', 'Keller', 'azikez@gahew.mr', 'S1T 4E6', 'Male', '$9,072.02 ']]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1YIpbzx8wrYj"
   },
   "source": [
    "# EXCELLENT JOB!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JOWd-_I8xlze"
   },
   "source": [
    "# MINI CHALLENGE SOLUTIONS:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PiBxzSjVxr4u"
   },
   "source": [
    "**MINI CHALLENGE #1:**\n",
    "- **Read the file 'fruits_input.txt'**\n",
    "- **compare the text file content to the list my_fruits = [\"Apple\", \"Pepper\", \"Orange\", \"Watermelon\", \"Tomatoes\"]**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "id": "45oMJBA2xvC5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Apple', 'Watermelon', 'Orange']\n"
     ]
    }
   ],
   "source": [
    "my_fruits = [\"Apple\", \"Pepper\", \"Orange\", \"Watermelon\", \"Tomatoes\"]\n",
    "\n",
    "with open(\"D:\\Python+for+Financial+Analysis+-+Course+Package/Part 1. Python Programming Fundamentals/fruits_input.txt\", \"r\") as file:\n",
    "    all_fruits = file.readlines()\n",
    "\n",
    "all_fruits = [char.rstrip('\\n') for char in all_fruits]\n",
    "Selected_fruits = [i for i in all_fruits if i in my_fruits]\n",
    "\n",
    "print(Selected_fruits)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E-Ab25tzxuQU"
   },
   "source": [
    "**MINI CHALLENGE #2:**\n",
    "- **Read the CSV file entitled \"S&P500_Stock_data.csv\" and print out the heading**\n",
    "- **Print out the first 5 rows of data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "id": "RKGDASZTxVYK"
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "with open(\"D:\\Python+for+Financial+Analysis+-+Course+Package\\Part 1. Python Programming Fundamentals\\S_P500_Stock_Data.csv\", \"r\") as csvfile:\n",
    "    readCSV = csv.reader(csvfile, delimiter=',')\n",
    "    stock = list(readCSV)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "id": "f38DGWN6xXz7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['Interest Rates', 'Employment', 'S&P 500 Price'], ['1.943859273', '55.41357113', '2206.680582'], ['2.258228944', '59.54630512', '2486.474488'], ['2.215862783', '57.41468676', '2405.868337'], ['1.977959542', '49.90835272', '2140.434475'], ['2.437722808', '52.03549192', '2411.275663'], ['2.143636835', '56.06059825', '2187.344909'], ['2.148646786', '51.51320834', '2263.049249'], ['2.176183572', '53.4759086', '2281.496374'], ['2.125351611', '63.66842224', '2355.163011'], ['2.225681934', '56.99339607', '2326.330337'], ['1.814687751', '55.36178043', '2078.553895'], ['2.281897215', '58.48475241', '2337.504507'], ['2.426737871', '55.7093282', '2485.774097'], ['2.259270476', '61.8872018', '2478.413528'], ['2.38801924', '66.55127056', '2665.00807'], ['1.715103596', '60.20251695', '2057.393366'], ['2.392425284', '60.57381954', '2423.590565'], ['2.388766722', '58.26132918', '2605.470983'], ['2.25666065', '52.77316693', '2303.851816'], ['2.089815376', '48.80721748', '2095.440317'], 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['1.899767635', '51.66533062', '2078.402807'], ['2.596025229', '45.2297572', '2501.037865'], ['2.388921827', '51.54657931', '2448.857146'], ['2.153722831', '50.38376778', '2216.204284'], ['2.436165002', '58.13743269', '2407.286008'], ['2.260276597', '59.76097238', '2365.05488'], ['2.226735047', '53.92317349', '2243.020143'], ['2.223555886', '61.20900519', '2413.405436'], ['2.277362034', '48.05239186', '2327.118323'], ['2.515491714', '56.37156228', '2459.594821'], ['2.231591254', '52.22823712', '2251.008179'], ['2.363503947', '53.75737859', '2372.607567'], ['2.238497577', '50.13480893', '2202.78846'], ['2.136525879', '59.92960062', '2281.937307'], ['2.004483901', '61.46176254', '2297.7046'], ['2.105029913', '55.67970958', '2260.624767'], ['2.275097277', '55.76692426', '2392.676408'], ['2.208297517', '61.09418383', '2384.179176'], ['2.275088386', '69.34912808', '2501.427597'], ['2.370507948', '55.88874159', '2496.53316'], ['1.914893978', '56.8882964', '2003.662905'], ['2.237709683', '64.43507354', '2515.617516'], ['2.008648994', '60.6452049', '2249.143193'], ['2.274847315', '60.54573091', '2355.530545'], ['2.717694357', '47.21045102', '2525.690522'], ['1.953190182', '56.14335675', '2080.965218'], ['2.03019553', '49.39332474', '2111.40646'], ['2.114780319', '54.75295264', '2251.535894'], ['2.075683586', '55.18960541', '2261.823407'], ['2.118580185', '47.28653992', '2132.422606'], ['2.083593049', '57.19186986', '2267.728149'], ['2.414705881', '63.6843222', '2562.221602'], ['2.012987514', '52.38643359', '2066.88301'], ['2.342075884', '54.8971472', '2298.40842'], ['2.152267368', '52.78905848', '2184.239973'], ['2.280004565', '62.20720827', '2407.651574'], ['2.359131297', '58.38356606', '2425.346848'], ['2.158017102', '55.38812486', '2320.10946'], ['2.336074187', '60.38485622', '2493.524016'], ['2.03904827', '57.03407583', '2170.111976'], ['2.056312376', '61.00912913', '2257.475721'], ['2.549962994', '56.33255888', '2501.091265'], ['2.544971113', '60.35532264', '2629.144318'], ['2.397617891', '52.57133959', '2393.6995'], ['2.647340685', '62.9026545', '2759.794164'], ['2.223084266', '52.600729', '2303.949594'], ['2.382675945', '52.45534793', '2488.765356'], ['1.925090936', '59.86557508', '2138.845178'], ['1.747024305', '58.05627914', '1991.212551'], ['2.292148182', '51.72476286', '2291.2935'], ['2.608824603', '53.13936061', '2536.891206'], ['2.097135938', '54.64775341', '2270.299791'], ['2.648733632', '51.64355259', '2626.603566'], ['2.416879206', '61.1986722', '2568.983069'], ['2.445709056', '54.52668912', '2477.600217'], ['2.06889631', '58.16528714', '2238.115791'], ['2.177616247', '51.91413929', '2217.463777'], ['2.280081317', '54.77217469', '2328.660552'], ['2.210951553', '61.37856457', '2382.124246'], ['2.656899047', '57.63198962', '2683.591162'], ['2.166261959', '61.84313722', '2292.435485'], ['2.17722559', '55.35685606', '2269.050696'], ['2.347453507', '56.40898909', '2436.035353'], ['1.789873187', '62.63646983', '2012.319387'], ['2.149252121', '55.73141739', '2280.042398'], ['1.908838152', '64.07911541', '2244.844913'], ['2.31568533', '58.33219464', '2397.910751'], ['2.279557435', '56.39436143', '2457.089375'], ['2.296955281', '67.43056085', '2593.225146'], ['2.17792756', '52.04833766', '2175.357361'], ['2.188355767', '60.845993', '2404.984701'], ['2.434014523', '56.51243838', '2474.302139'], ['2.480717306', '64.67854601', '2567.280465'], ['2.334237516', '60.87265779', '2492.335968'], ['2.056016697', '47.91353901', '2096.998302'], ['2.289291258', '60.03299313', '2355.225478'], ['2.09703388', '58.16663777', '2234.581817'], ['2.384734134', '57.73295368', '2582.27948'], ['2.403348148', '51.95338945', '2381.789544'], ['2.165565035', '62.62315891', '2467.307182'], ['2.05926956', '59.01009038', '2300.848035'], ['2.46488364', '56.58808128', '2562.764485'], ['2.186663214', '55.27693605', '2224.040699'], ['2.04399899', '51.35432872', '2131.219474'], ['1.971307623', '53.13122237', '2031.346274'], ['2.131514623', '50.96812444', '2245.59405'], ['1.942980688', '57.04593254', '2120.948889'], ['2.436750441', '61.18556452', '2508.751044'], ['1.99273054', '65.10406704', '2269.322372'], ['1.990452219', '52.51102279', '2085.534307'], ['2.38459603', '57.74013178', '2497.913238'], ['2.327413919', '56.9363765', '2405.684511'], ['2.816497184', '45.03986697', '2718.811585'], ['2.134476489', '68.01064417', '2533.151582'], ['2.171113726', '61.92005319', '2378.392345'], ['2.018199743', '56.92961587', '2206.94618'], ['1.936747824', '52.96752441', '2086.159182'], ['2.59152853', '57.28103007', '2686.211789'], ['1.740441475', '55.09864486', '1922.893274'], ['1.868835087', '60.54337734', '2065.424594'], ['2.528420416', '52.39082811', '2578.699184'], ['2.643570716', '54.62620358', '2573.865933'], ['2.009643674', '57.00435706', '2004.911218'], ['2.201655964', '62.44779038', '2344.098981'], ['2.180637971', '46.29703432', '2156.133786']]\n"
     ]
    }
   ],
   "source": [
    "print(stock)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "id": "H6wfbUS4xX2Y"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Interest Rates', 'Employment', 'S&P 500 Price']\n"
     ]
    }
   ],
   "source": [
    "print(stock[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "id": "vPW5JHLExaJG"
   },
   "outputs": [],
   "source": [
    "selected = []\n",
    "for row in stock[1:6]:\n",
    "    selected.append(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "id": "X7R2RDmkxaLQ"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['1.943859273', '55.41357113', '2206.680582'],\n",
       " ['2.258228944', '59.54630512', '2486.474488'],\n",
       " ['2.215862783', '57.41468676', '2405.868337'],\n",
       " ['1.977959542', '49.90835272', '2140.434475'],\n",
       " ['2.437722808', '52.03549192', '2411.275663']]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "yfrWoZwxwojy"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "6. Python 101 - Files - Skeleton before filming.ipynb",
   "provenance": []
  },
  "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": "3.9.0-final"
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 },
 "nbformat": 4,
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}