Pandas_Exercise.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center>Introduction to Pandas</center>\n",
    "\n",
    "![](https://pandas.pydata.org/_static/pandas_logo.png)\n",
    "\n",
    "\n",
    "## Installation\n",
    "\n",
    "Simply,\n",
    "```\n",
    "pip install pandas\n",
    "```\n",
    "\n",
    "\n",
    "## Reading data from a CSV file\n",
    "\n",
    "You can read data from a CSV file using the ``read_csv`` function. By default, it assumes that the fields are comma-separated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import pandas\n",
    "import pandas as pd\n",
    "from collections import Counter\n",
    "import statistics as st"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">The `imdb.csv` dataset contains Highest Rated IMDb \"Top 1000\" Titles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load imdb dataset as pandas dataframe\n",
    "imdb_df = pd.read_csv(\"C:\\\\Users\\\\Ayus Das\\\\Downloads\\\\imdb_1000.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>genre</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>9.2</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>175</td>\n",
       "      <td>[u'Marlon Brando', u'Al Pacino', u'James Caan']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>9.1</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>200</td>\n",
       "      <td>[u'Al Pacino', u'Robert De Niro', u'Robert Duv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>9.0</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Action</td>\n",
       "      <td>152</td>\n",
       "      <td>[u'Christian Bale', u'Heath Ledger', u'Aaron E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>8.9</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>R</td>\n",
       "      <td>Crime</td>\n",
       "      <td>154</td>\n",
       "      <td>[u'John Travolta', u'Uma Thurman', u'Samuel L....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   star_rating                     title content_rating   genre  duration  \\\n",
       "0          9.3  The Shawshank Redemption              R   Crime       142   \n",
       "1          9.2             The Godfather              R   Crime       175   \n",
       "2          9.1    The Godfather: Part II              R   Crime       200   \n",
       "3          9.0           The Dark Knight          PG-13  Action       152   \n",
       "4          8.9              Pulp Fiction              R   Crime       154   \n",
       "\n",
       "                                         actors_list  \n",
       "0  [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...  \n",
       "1    [u'Marlon Brando', u'Al Pacino', u'James Caan']  \n",
       "2  [u'Al Pacino', u'Robert De Niro', u'Robert Duv...  \n",
       "3  [u'Christian Bale', u'Heath Ledger', u'Aaron E...  \n",
       "4  [u'John Travolta', u'Uma Thurman', u'Samuel L....  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show first 5 rows of imdb_df\n",
    "imdb_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">The `bikes.csv` dataset contains information about the number of bicycles that used certain bicycle lanes in Montreal in the year 2012."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load bikes dataset as pandas dataframe\n",
    "bikes_df = pd.read_csv(\"C:\\\\Users\\\\Ayus Das\\\\Downloads\\\\bikes.csv\",sep = ';',parse_dates=['Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>Rachel / Papineau</th>\n",
       "      <th>Berri1</th>\n",
       "      <th>Maisonneuve_2</th>\n",
       "      <th>Maisonneuve_1</th>\n",
       "      <th>Brébeuf</th>\n",
       "      <th>Parc</th>\n",
       "      <th>PierDup</th>\n",
       "      <th>CSC (Côte Sainte-Catherine)</th>\n",
       "      <th>Pont_Jacques_Cartier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>16</td>\n",
       "      <td>35</td>\n",
       "      <td>51</td>\n",
       "      <td>38</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2012-02-01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>43</td>\n",
       "      <td>83</td>\n",
       "      <td>153</td>\n",
       "      <td>68</td>\n",
       "      <td>11.0</td>\n",
       "      <td>53</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2012-03-01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>58</td>\n",
       "      <td>135</td>\n",
       "      <td>248</td>\n",
       "      <td>104</td>\n",
       "      <td>2.0</td>\n",
       "      <td>89</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date Unnamed: 1  Rachel / Papineau  Berri1  Maisonneuve_2  \\\n",
       "0 2012-01-01      00:00                 16      35             51   \n",
       "1 2012-02-01      00:00                 43      83            153   \n",
       "2 2012-03-01      00:00                 58     135            248   \n",
       "\n",
       "   Maisonneuve_1  Brébeuf  Parc  PierDup  CSC (Côte Sainte-Catherine)  \\\n",
       "0             38      5.0    26       10                            0   \n",
       "1             68     11.0    53        6                            1   \n",
       "2            104      2.0    89        3                            2   \n",
       "\n",
       "   Pont_Jacques_Cartier  \n",
       "0                  27.0  \n",
       "1                  21.0  \n",
       "2                  15.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show first 3 rows of bikes_df\n",
    "bikes_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting columns\n",
    "\n",
    "When you read a CSV, you get a kind of object called a DataFrame, which is made up of rows and columns. You get columns out of a DataFrame the same way you get elements out of a dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['star_rating', 'title', 'content_rating', 'genre', 'duration',\n",
       "       'actors_list'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# list columns of imdb_df\n",
    "imdb_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "star_rating       float64\n",
       "title              object\n",
       "content_rating     object\n",
       "genre              object\n",
       "duration            int64\n",
       "actors_list        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what are the datatypes of values in columns\n",
    "imdb_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    The Shawshank Redemption\n",
       "1               The Godfather\n",
       "2      The Godfather: Part II\n",
       "3             The Dark Knight\n",
       "4                Pulp Fiction\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# list first 5 movie titles\n",
    "imdb_df['title'].head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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",
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       "    }\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>title</th>\n",
       "      <th>genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>Crime</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      title   genre\n",
       "0  The Shawshank Redemption   Crime\n",
       "1             The Godfather   Crime\n",
       "2    The Godfather: Part II   Crime\n",
       "3           The Dark Knight  Action\n",
       "4              Pulp Fiction   Crime"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show only movie title and genre\n",
    "imdb_df[['title', 'genre']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Understanding columns\n",
    "\n",
    "On the inside, the type of a column is ``pd.Series`` and pandas Series are internally numpy arrays. If you add ``.values`` to the end of any Series, you'll get its internal **numpy array**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n"
     ]
    }
   ],
   "source": [
    "# show the type of duration column\n",
    "imdb_df['duration'].dtype\n",
    "a = imdb_df['duration']\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([142, 175, 200, 152, 154,  96, 161, 201, 195, 139, 178, 148, 124,\n",
       "       142, 179, 169, 133, 207, 146, 121, 136, 130, 130, 106, 127, 116,\n",
       "       175, 118, 110,  87, 125, 112, 102, 107, 119,  87, 169, 115, 112,\n",
       "       109, 189, 110, 150, 165, 155, 137, 113, 165,  95, 151, 155, 153,\n",
       "       125, 130, 116,  89, 137, 117,  88, 165, 170,  89, 146,  99,  98,\n",
       "       116, 156, 122, 149, 134, 122, 136, 157, 123, 119, 137, 128, 120,\n",
       "       229, 107, 134, 103, 177, 129, 102, 216, 136,  93,  68, 189,  99,\n",
       "       108, 113, 181, 103, 138, 110, 129,  88, 160, 126,  91, 116, 125,\n",
       "       143,  93, 102, 132, 153, 183, 160, 120, 138, 140, 153, 170, 129,\n",
       "        81, 127, 131, 172, 115, 108, 107, 129, 156,  96,  91,  95, 162,\n",
       "       130,  86, 186, 151,  96, 170, 118, 161, 131, 126, 131, 129, 224,\n",
       "       180, 105, 117, 140, 119, 124, 130, 139, 107, 132, 117, 126, 122,\n",
       "       178, 238, 149, 172,  98, 116, 116, 123, 148, 123, 182,  92,  93,\n",
       "       100, 135, 105,  94, 140,  83,  95,  98, 143,  99,  98, 121, 163,\n",
       "       121, 167, 188, 121, 109, 110, 129, 127,  94, 107, 100, 117, 129,\n",
       "       120, 121, 133, 111, 122, 101, 134, 165, 138, 212, 154,  89, 134,\n",
       "        93, 114,  88, 130, 101, 158,  99, 108, 124, 132, 113, 131, 191,\n",
       "       167, 130, 147, 102,  88, 165, 132, 118, 101, 108, 174,  98,  92,\n",
       "        98, 106,  85, 101, 105, 115, 115, 124, 105, 103, 138, 184, 120,\n",
       "        99, 131, 138,  98, 123, 118, 114, 118, 112, 124, 160,  67, 146,\n",
       "       125, 115, 134, 141, 129, 104,  94, 124, 150, 119, 128, 143,  85,\n",
       "       151, 118, 101,  99,  92, 125, 102, 106, 107,  91,  80, 122, 102,\n",
       "       112,  92, 135, 136, 153, 105, 126,  68,  84, 103, 145,  80, 106,\n",
       "       127, 178, 137, 172,  76, 130,  96,  82, 115,  95, 143, 125, 120,\n",
       "       127, 112, 104, 113, 189, 127, 188,  96, 113, 132, 122, 126, 140,\n",
       "       133, 112, 102,  93, 109,  81, 108, 111, 119,  96, 197, 127, 138,\n",
       "        66, 181, 141, 144, 128,  83, 121,  98, 117,  94, 174, 112, 108,\n",
       "        70,  99,  96, 137, 136, 100,  90,  96, 161, 115, 181, 169,  98,\n",
       "       136, 138, 119, 123, 112, 120, 103,  97, 109, 165, 156, 147, 100,\n",
       "       126, 115, 105, 144, 102, 107, 119,  90, 197,  86, 113, 133,  64,\n",
       "       141, 113, 122, 105, 119, 102, 122, 123, 113,  97, 117, 111,  85,\n",
       "        99, 134,  75, 109, 117,  91, 128, 111, 119, 100, 114,  92, 141,\n",
       "       101, 115, 127,  96, 129, 135, 109, 157, 193,  94, 155, 113, 130,\n",
       "       117, 159, 141, 112, 162, 126, 120, 144, 120, 109,  97, 108, 115,\n",
       "       136,  90, 170, 220, 116, 134, 124,  91, 103,  96, 119,  98, 101,\n",
       "        93, 179, 155, 121, 103, 127, 103, 107, 100,  92,  94, 158,  86,\n",
       "       115, 130, 107, 100, 108, 124, 131, 122, 242, 127, 141, 126,  89,\n",
       "       113, 152, 107,  92, 145,  84, 126, 132,  78, 117, 128, 100, 128,\n",
       "       100, 143, 107, 100, 125, 106, 157,  94, 104,  94, 153, 123, 120,\n",
       "       105, 166, 112,  94, 111,  87,  80, 108, 102, 105, 136, 101, 100,\n",
       "       108, 101, 106, 105,  88, 129, 138, 129, 118, 139, 123, 150, 132,\n",
       "        80, 178,  79, 163, 114, 144, 130, 154,  81,  95, 101, 120,  93,\n",
       "       115, 106, 120, 110, 123, 142,  99, 112, 120, 122, 130, 139, 129,\n",
       "       141, 127, 130, 118, 110, 115, 101, 112, 108, 143, 152, 117, 121,\n",
       "       119, 114, 122, 105, 110, 116, 139, 121, 109, 146, 113, 100, 121,\n",
       "       113, 113, 117,  93, 101,  90, 131,  98,  93, 121,  82, 124, 100,\n",
       "       117,  99, 116, 123, 114, 133, 105, 127, 144,  90, 118, 122, 102,\n",
       "       187,  87, 154,  89,  88, 129,  95, 118,  98, 194, 114,  80, 130,\n",
       "       135, 101, 105, 129, 134, 143, 202,  89, 106,  92, 137, 124, 122,\n",
       "       113, 112, 110, 135,  88, 146, 104, 125, 131,  91, 142, 129, 158,\n",
       "       102,  99, 101, 104, 119, 103,  88, 100, 146, 150, 140, 140, 110,\n",
       "        97, 102, 152, 100,  94,  85, 104, 112, 191, 119, 111,  94, 103,\n",
       "       134, 157, 158, 127, 101, 109,  98, 134, 168,  93, 145, 111,  88,\n",
       "       123, 121, 144, 116, 124, 147, 106, 113, 129,  94, 126, 128, 111,\n",
       "       146,  85, 105, 132, 130, 162, 113, 110, 113, 162, 110,  78,  92,\n",
       "        95, 138, 102, 128,  96, 164, 126, 110, 109, 122, 124, 128, 157,\n",
       "       120, 102, 152, 170, 102, 116, 164,  85, 104,  99,  81, 131, 101,\n",
       "       121,  69,  92,  94, 141, 116,  98, 135, 121, 108, 114, 102, 112,\n",
       "       140, 157, 128, 108, 139,  83, 131, 113, 136,  96, 118, 108,  83,\n",
       "       205, 124, 111, 137, 104, 109, 115,  99, 114, 133, 131, 131, 123,\n",
       "       126,  97, 126,  89, 122, 121, 125, 105, 118,  81, 115, 126, 113,\n",
       "       107, 126, 111,  85, 120,  93, 100, 107, 126, 131, 116, 143,  93,\n",
       "        96, 160, 137, 119, 114,  98, 111, 138, 144, 107, 114, 125, 146,\n",
       "       113,  85,  97,  93, 113, 128, 114, 147, 127, 167, 124, 109, 124,\n",
       "       102, 130, 125,  98, 154,  97, 128,  98, 101, 147, 172, 125,  88,\n",
       "       125, 121, 112, 120, 133, 110, 135, 110,  80, 135, 101, 112, 124,\n",
       "       129, 104,  96, 105, 109, 117,  78, 138, 106,  90, 106,  91, 112,\n",
       "       134, 112, 104, 101, 120, 123, 133, 110, 129, 120,  83,  88,  96,\n",
       "       139, 113,  84, 106, 170, 144, 104, 153,  85, 130,  93, 148, 115,\n",
       "       102, 125, 106, 121, 143, 116,  99, 116, 128, 119, 104, 114, 152,\n",
       "       129, 103, 112,  92, 141, 106, 109, 104, 122, 111, 112, 116, 130,\n",
       "       133, 134,  92, 104, 110,  97, 100, 118, 112, 138,  92, 118, 140,\n",
       "       128, 101,  75,  97, 111, 175,  94,  97, 132, 120, 107,  89,  86,\n",
       "       103, 108, 105, 117, 102, 104, 157, 104,  98, 109,  96, 103, 114,\n",
       "        99, 118, 150, 105,  87, 136, 162, 109, 107,  90, 112, 126, 116,\n",
       "       118, 138, 114, 126], dtype=int64)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show duration values of movies as numpy arrays\n",
    "imdb_df['duration'].values[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applying functions to columns\n",
    "\n",
    "Use `.apply` function to apply any function to each element of a column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    THE SHAWSHANK REDEMPTION\n",
       "1               THE GODFATHER\n",
       "2      THE GODFATHER: PART II\n",
       "3             THE DARK KNIGHT\n",
       "4                PULP FICTION\n",
       "Name: title, dtype: object"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert all the movie titles to uppercase\n",
    "to_uppercase = lambda x: x.upper()\n",
    "imdb_df['title'].apply(to_uppercase).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting a column\n",
    "\n",
    "Use ``.plot()`` function!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# plot the bikers travelling to Berri1 over the year\n",
    "import matplotlib.pyplot as plt\n",
    "bikes_df['Berri1'].plot()\n",
    "plt.title(\"Berri1\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# plot all the columns of bikes_df\n",
    "bikes_df['Rachel / Papineau'].plot()\n",
    "plt.title(\"Rachel / Papineau\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['Maisonneuve_2'].plot()\n",
    "plt.title(\"Maisonneuve_2\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['Maisonneuve_1'].plot()\n",
    "plt.title(\"Maisonneuve_1\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['Brébeuf'].plot()\n",
    "plt.title(\"Brébeuf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['Parc'].plot()\n",
    "plt.title(\"Parc\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['CSC (Côte Sainte-Catherine)'].plot()\n",
    "plt.title(\"CSC (Côte Sainte-Catherine)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "bikes_df['PierDup'].plot()\n",
    "plt.title(\"PierDup\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LE2nLQCmVAA0GARLXMtBgoJRKgAaDQNFJZ0qp5GgwCJCYgUhIvOdKKdVXGgwCxBhD2AYD7TNQSiVCg0GAGPCCgaaJlFKJ0GAQIMb4goG2DJRSCdBgECAxY0gLh+zzQa6MUiqlaDAIEgMhsX0GGg2UUgnoNRiIyBIRKReRdb6yYhFZJiKb7WORLRcRuV1EtojIGhE5yfeexXb7zSKy2Fd+soiste+5XcSezVTCDP7RRBoMlFJ915eWwX3AxR3KbgCWG2OmAcvt9wCXANPs13XAXeAED+Am4DTgVOAmN4DYba7zva/jz1J95B9NpMFAKZWIXoOBMeZFoKpD8SLgfvv8fuAyX/kDxrECKBSRUcACYJkxpsoYcwhYBlxsX8s3xrxmnPWXH/DtSyXIP5pI00RKqUQk22cwwhizD8A+ltryMcBu33Zltqyn8rIuyrskIteJyGoRWX3w4MEkqx5cMWO8NJE2DJRSiRjoDuSu8v0mifIuGWPuMcbMN8bMHz58eJJVDC7/0FJtGSilEpFsMDhgUzzYx3JbXgaM8203FtjbS/nYLspVEuImnWnTQCmVgGSDwVLAHRG0GHjCV36NHVV0OlBj00hPAxeJSJHtOL4IeNq+Vicip9tRRNf49qUSpZPOlFJJivS2gYg8DJwHlIhIGc6ooB8Cj4rItcAu4KN28yeBhcAWoAH4FIAxpkpEvg+8brf7njHG7ZT+PM6IpSzgKfulkmAwRHTSmVIqCb0GA2PMld28dEEX2xrg+m72swRY0kX5amB2b/VQvYsZCNteGO0zUEolQmcgB4gxhkjIbRloMFBK9Z0GgwCJX7V0cOuilEotGgwCxBiIhPV+BkqpxGkwCAhjT/7uQnWaJlJKJUKDQUC45/6I3txGKZUEDQYB4Z76Q3oPZKVUEjQYBISbJorochRKqSRoMAgI99Qf9haq02CglOo7DQYBEevYMtBgoJRKgAaDgHDP/eGQLkehlEqcBoOA0dFESqlkaDAICK9lENYOZKVU4jQYBITbZxDWSWdKqSRoMAiIjqOJNBgopRKhwSAg3KGkYZ10ppRKggaDgHDP/TrpTCmVDA0GAdE+tFQnnSmlEqfBICCCuBzF3upGWqN6YwaljgYNBgHhNgSCslBdU2uUC376Ao+/uWewq6LUMUGDQUB07DNI9dFEDS1RGlujHKxvHuyqKHVM0GAQEF6aKByMeyC76aGWNk0TKXU0aDAICDct5E46S/VUuxcMUv2DKJUiNBgEhKHjPIPUbhm0RZ36a8tAqaNDg0FQuLe9DAdjoTpNEyl1dGkwCIiOy1Gk+v0MWrVloNRRpcEgILyhpRKMoaXaZ6DU0aXBICDcPgIBQpL6aaK2mKaJlDqaNBgEhHvqF3FSRanegeymiZo1GCh1VGgwCAh3noGIICIB6DPQNJFSR5MGg4Bwz/2CM9cgxWOBb2hpdJBrotSxQYNBwIgI4ZCk/EJ1LTq0VKmjSoNBQPg7kEVSf9VSr2WgaSKljgoNBgHRvmqp04Gc6vcz0NFESh1dGgwCwhtNhBAKQAeyGwQ0GCh1dPQrGIjIDhFZKyJvi8hqW1YsIstEZLN9LLLlIiK3i8gWEVkjIif59rPYbr9ZRBb37yMdm9pHEzkTz1I8S0RbTGcgK3U0DUTL4HxjzDxjzHz7/Q3AcmPMNGC5/R7gEmCa/boOuAuc4AHcBJwGnArc5AYQ1Xf+k38QJp3p0FKljq4jkSZaBNxvn98PXOYrf8A4VgCFIjIKWAAsM8ZUGWMOAcuAi49AvQKufZ6BTjpTSiWqv8HAAM+IyBsicp0tG2GM2QdgH0tt+Rhgt++9Zbasu/JOROQ6EVktIqsPHjzYz6oHS/vaRE6aKNUvqNt0aGlCNuytZXdVw2BXQ6WwSD/ff5YxZq+IlALLROTdHraVLspMD+WdC425B7gHYP78+al96TvA4jqQQ6T8aCJ/msgYg0hXfybKtfD2lwDY8cMPDnJNVKrqV8vAGLPXPpYDj+Pk/A/Y9A/2sdxuXgaM8719LLC3h3KVAG8GstsySPlg4NTfmPbOZKXUkZN0MBCRHBHJc58DFwHrgKWAOyJoMfCEfb4UuMaOKjodqLFppKeBi0SkyHYcX2TLVAL8k87CkvozkN15BjB0UkVv7jrE2T96jprG1sGuilIDrj9pohHA47b5HgEeMsb8U0ReBx4VkWuBXcBH7fZPAguBLUAD8CkAY0yViHwfeN1u9z1jTFU/6nVMam8ZCKFQ6q9N5LYMwAkGORmDWBlrw95ayg41sre6kYKstMGujscfLGsaW4dU3VTqSDoYGGO2AXO7KK8ELuii3ADXd7OvJcCSZOui2u+B7KSJUn85ilZfD/hQGV5a39wGwGH7OFTU++qz59DQClQqdegM5IDwr1rqTDoLUDAYImkiNwjU9zMYrNtTQ2V980BUCYD6Jl8wqG4csP0ORTWNrZz+g+W8sVOTBwNNg0FAxKWJAhAM2vxpoiHXMkh+WW1jDB/635f52D0rBqpa1Da192GUHQr28NL9NU3sr21i84H6wa5K4GgwCAg3TRTy7nQ2yBXqp459BkNBe8sg+Q7kysMtAGwpH7iTWcc0UZA1tDifVScjDjwNBgERP7Q0YH0GQ+Qfv94LBsm3DMqOwMm6zpcmqg74SKfGFufYN+tNjwacBoOAiJ90FoA0UWwodiA7J6D+dCC7aZzs9PCA1AnaWyrpkVBc/0EQNbbaYNA6NP4mgkSDQUAYXw9yEPoMWtqGcpqoP8HAaRnkZiQ2kG9NWXW3V8NuABhdkEldP1JYqaDBaxkMjb+JINFgEBAx32iisAixFP9fGYqTzgYmGDgtg0TSeOW1TVx25ys88VbXE/NrbTAYVZAVlzIKIk0THTkaDALD7UAW57aXKd4yaIsaL5UyVK4C3RNtMmmiA7VN7Kw87LUMahpb+7x+1I7KBmKm+2Gj9c1tpIWFYbnpgU8TuR3ITZomGnAaDALC34EcDknK38+gJRojOz3iPR8KDrf0LRjUNbXygyc30tTafvX6gZ+9wLk/eZ4dFYcBZ70lN+XRG7c1UWHnJlTWN/O7V7az6UCd9/PyMtPIy0zzWgmJXjmvKavmmiWrePC1HUN6kcOGVm0ZHCkaDALC34EchPsZtEVj5Gc6waCpw0mzNRqLO9EeLW4Q6C0V88qWSu55cRurdxzyytyT9I7KBo4bkQvQ7RpH5XVNcctRu62JynpnWOpDK3dxy982sPCXL7HtYD31TW3kZkTIy4xQ19TKjX9Zy4z/+ifLNx7oto43/mUtf3vHSTtVHW7h/9y3mhVbK/mvJ9azdk9N3LbGGL7717W8uqWix8/d0ZG4IGnUPoMjRoNBQPhbBiJCNLVjAa1RQ1FOOhA/qQrg6ntXMvum/q1l2BaN8ec3ymhui7KmrJrbntqIMYYNe2t5a9chb5s7ntvM1oP1NLdFvbkPbguhO94V/OGuZxl/9GRnkd7qhvjP9cqWCr712BrO/fHznPPjf3nl7tyBysPN1DS0sn5vLenhEFlpYW79x0bq3GCQEaG5LcbDq3YRM/Dbl7Z3+fONMTz2xm6etcFi1fZKKuqbuf3KE4mEhKfW7Y/bfm9NE79fsYurfruyx8/tt7+miRNueYZ7Xtza5/f0hdeBrGmiAdff+xmoISLmuwdyWIJxP4MR+c7qdB2vxFdsc5YiiMUMoVBy9zm46/mt/HTZJirqm7ntKec2HBfOGMGnfvc6IYHXbryA25dv5tcvbmPbwcN854MzvPeu21PLbU9t5OsXTSct3Pl6yr2Cr7CP/jkTs0bnM2t0PtC5ZfD8e+X8cXX7fZ6a26JkRMKUVTuthNd3HGLu954B4JLZIxlZkMkfVu5izpgC8jIj5Ga2/zufOWUYr26tZHvFYSaV5ACwu6qBf67bz4Rh2bRGDQfrnGC1s9LZ/xlThnHGlGH85c0y5owpYOGcUQC8s7va2+97++uYPjKv02d+b38dMWOYMcr5bC9vqaC+uY0fPPkuZ08dzkz7mfurUdNER4y2DAKifWSp2DudpXYwaIsZMiJhcjMicS2Dvb5OVHc2b1dqGlp5cVPXd8Nbua2S+17dAcDDq3Z55T95+j2a26LUNrVx/2s7+O3LzpX11oP1bNhXCzhj+QF+/cI2vv/3DXH7fXd/LY0tUa9l4D66J93PnDOJO686iYJsZyG5jsHgcId02Ia9tbRGY11OVJs5Kp/JJTm0tMVYt6eGsUXZccNV/2O+0/rYaOtd09DKFfes4NYnN/KVP74dV78dlQ0U56RTkJXGJ8+cSHNbjK89+raX5vEHA/eYGmOos7+X1miMBb94kUt++ZK33artld7zt3a3p8v6S9NER44Gg4CIW7U0xZajeGnzQX70z/ib5LVGY0TCQn5mJK5l8PqO9gXK3NE1L20+SHltU9z7739tB4t/t4rqhviAUd/cxpW/WeEFkh2V7bn5reX1TB+Zx9yxBfzi2c1EY4Y5Ywp4p6yGq+9dBUBxdrq3/d/X7ANg9Y4qXth0kA/e/jK3P7c5rqMXYL+t2xlThjGxJMdbVbSmMb5uDR06pj/yq1e5/g9vsre6kUiHFtC0EbmMK84GnBPjxGHZ5GW2r1Z60vgioD143v3iVvbXNjFjVL6XanGD1K6qw0wY5uzrghkj+M+LptPUGqPcvv727mrmjiskPRKiwqa+7nphK3NufoZDh1tY+nbnIa+rtldx4YxSstPD3tIbLW0xahr6Nw9Cl6M4cjQYBEXcqqVHpvPuSLn63lXc9Xx8brktakgLh5wRMr4r6OUby73ne6sbeXjVLq6+dxX//cR6rr53pXcVu/VgPcbAt/68hi8/8hbgXOG+sfMQMQPfXzSL6SPi0x2Vh1soyk7nIyeOoaUtRiQkfPqcSXHbuCf2ycNzqG5oIRYzXH73ayxesopozPC3d/Z6J1k3TeQGqhH5mQBeMFi3pzYundfVMhfPbDhAa9Qwb1yhVza5JIdTJw3zggHAhJIc8nxponHFWeSkh72AuauygQnDsrl07mhvm0MNrbRGY+yoaGCCb18TbWD4zuNrueO5zazdU8OJ4wopyUmnos75TD99ZhMAOyoPe62s4XlOWu+tXYfYUdnAGVNKmDI81wsG197/upfmSlaDzjM4YjQYBIR77g+FUnc0kT+33hqNkRYW8rPaWwaV9c38c91+/u3EMYATDP53+WYAntmwn5c2V7DozlcwxnhDOJ9ef4An7JXrZx98g2/86R0AppbmMbrQOTm7OXWAwux0Fp4wipDACWMLOPe44ZTkZngn46tOGw84OfuYgXpfZ3JJbjplhxpZvfOQV9/y2ibuf3Un0B4McjMiLJwzkgdX7OS/n1jvBYSGHjqmz5k2HIB54wp57uvnUZyTzpjCLO91p2XQHgxEhDFFWV7nc0V9MyU5GYz3nfQB9lU3sa+mkQnD2o/BhGLn+fJ3y/nFs5tpaIkyd1wBw3IznE7sxlYvDblswwHW7qkhPRyirsmZO3HL3zZQmpfBx04Zx9TS9mDw0mZnNFI0Znh9RxUb9tZ2+3m706gdyEeMBoOA8NJEuKOJUi8YNPiujJ1g4LQM3CUW7vzXVlqiMT5/3hTvqtddmM3fEFq981Bc+gegqTXK/tomL/UxIj+DMUXOyfSEsQXedkXZaZTmZfKNBcfz+fOmUpidzurvXshfrz+Ll755Pj/4yBy2/mChd/J0WwH/duIY/vGlcwj70jkV9S189dG3eW2bkz93U0wiwh1XnsRnzpnEgyt28uCKnXz78bVxo4vOmDzMC3rp4ZA3HNWtM0BmWtjrZJ8wLKfTEhejC7PYW+MEg6rDLQzLTWdccVbcNs9vKidm4gOiGySh/f7Tc8cWUpKbzqtbKpl7S/vV/a+e30p6OMQ1Z0ygqTXGuj21vL27muvPn0puRoSppbnsq2mKm7Vd29jKV//4Nj94ciOJ0uUojhwNBgERN+lMUmfSmT9N4h+y2RY1REIh8jIj1Da28dLmgyx5ZTtXnz6BaSPyGF2Yxe6qBhpaoowqcE5eRbZj9l/vlnfqnN1uWwqu0vxMxhQ6V8lzxrQHg0J7wv78eVP4wMwRce9x0zLhkFBoUz07K539njihiBH5mcy2o2ZC4vRpvL7daSUcPyZrgU0AABbNSURBVDIvbuRTKCR8Y8HxZKWF+e8n1vPQyl1eJzXAZSeO5gvnTwGc/oHzjy/l6tMncPOHZ8XVaXxxttf56+8zABhTmOUbltpCcU56p5bBzUvXk58Z4f0zSr2ySIcRUnmZESYOy2FYboY3AfDCGaVkpjnbnTC2gPE2tfTo6t2IwCVzRgIwZbgTxDbbCXIAO6saKDvU2Ol3ArCvppGfL9tEm6+VGI0ZryWio4mOHA0GAdF+SpWUup/BId/VsH9mb4ubJspMo66plT+/UUZhdhr/9aGZAIwsyGSzTT+cOqkYgHOPG86ogkyeXOt07Pqv0jf6TrS5GRFyMyLeFfC0EXneic0NKL1x50DsqHBaIG5wmG0DS45v9vRjnzuDpV88u9M+0iMhTp5Q1OX+8zPTmDgsh6y0MLNHF5CZFub7l8328vKuS+eN4WOnOCOH3DRRuj2Zjy7M4lBDK3VNrRxqaGFYboYTNDIijLUtjJiB6943mfzMrj/3yPxM5o0rJBQSSnKdn50WFu7+xMleOmnuuELv/Y+9UcYpE4opzXOOrdsxvXJ7e8f/q1uddNHemkbvpL5hby1NrVF+9swmfrl8M89saJ8wd97/+xcf+dUrgI4mOpJ0nkFAGN88AzmK9zOIxQx3/GsLHzlxTFyHZl/5h4q6Qyt3VTbQ3BZjdGEWB2qbONTQyvJ3y7l41khvaGdxTjqvbXXSL/MnFvPa1krOP76UuqY2lr/rdDKfPKGIVfYk9O7+9ivTUptaOe+4Uj511kROnVhMQVYaTa3NFPlGC/WkY8ug0AaRfz95LH9YuYtL543mDyt3cfGskZw8oQiRrudDnDapmJe7mNmbl5lGJBziwWtPZWxR98f16tMneM8zIiG+dME0LrItGrdPYcPeWoxx+jREhLOnlTC2KIvf2Elpn3nf5E77/ev1Z3GwrplRBZnk2PRTSa5zbIqy04mEQzS0OsF77rhCcjOcdaQaW6OcOKG9s9v9m3hpc/sw31e3OL83Y7AzrYWFt79ESW6GNx/hH2v2efMcdlc1sruqkVjMtI8m0j6DAafBICDcbEtIhLAIe6obeWHTQc49bvgR/bmvbq3kZ8s28d7+Ou78+El9es+asmpmjS4gHBL21bQPCXVbBi9tcU4cZ08r4Zn1zhViXVMbC2aN9LYtyk738tnDczNY9Z0LAWfy0/J3y5kyPIf/uWw2v3h2E0+u3R/XMhhhr1oLstO4yaZdCrLSOFDb7J3Ue+POFdhe6bYMnBPlSeOL2PC9BWRGwlxzxkSOG5HbbSAA+MCsEfx02aZO5flZzr/m/InFfaoPOH0RX/vAcd73btBz00/FtjVz1ydOBmBaaR7zJxaREel8bwX/6CWX2zLIt4EwGnX7Ewq8vhOA0QXt/RK5GRFKctN5ZUv7vINXt1Yg4vzN7qho4FCDO0mv2ZvHsGzDgU6r1W7cXxuXJjLG9HhsVWI0TRQQ8R3ITtniJasGdCZyXVOrN0qnpqGVw81tPGevwgv6cBLdWXmYjftqufSOV7hp6ToA9vju2esFg00VjC7IZHJJjndSBDhz6jDvuTs8E4gbRXOcHS766XMmc9yIPD51ljM0dOO+Oq+D1e109XP319eWQUE3LQOA7PQIoZAwfWReryer40fms+F7CzqVd5e2SYSbqnED4bCc+M/9H6eMY7LN6feF+xndNaN+9YmT+eSZExlfnO0FCMDrw3F1bDHGDJww1gk2OyoPs25PDdnpYUptCiw3I0JLNEZFfTMHfPNHXtpcQWvUkBEJETPxt0ZV/afBICD8Hcj+BdJ2Vg7cDdK/8ac1fPiOl2lqjfLvd7/K537/Bv9c5+Tne7vnQFs0xgdvf5mbl64H4PcrdlHf3Ma9r7Svn3O4pQ1jDKt2VHHm1BJExOsUzcuIeKuYQnxu3x8MLp07mj997gyu6JBHr6hvZubofEbkZzBtROflFAqy2lMgfZERCZOdHvaOb19bFF3JSgt7eX6X/zMly20ZuCkyN82TLDeYzhrt9IvMG1fIzZfOQkTigteogvgRS26aa+Gc9pbdCWMKKMhKY0flYdbuqWH26ALeZ1uxZ9mgX17X7M3rgPa1lton22kn8kDSYBAQ/uUoZvlGx7y5a2CWAli/t4Z/rt9PXVMbP392E1vK63lpcwV7bZrnUA9LQwDsrXaGF/rr8z9/38DuqkbuuOpEAA43R6mob6HqcAsz7Ro37knSXfPGVeg7aftH0YRCwikTi70rcv9rY4uyWPa1c7muixy5e6VfmNP3k7rbbxAOScJ3LvMTkU4tq44jg5KRlxEhMy3ktQzcNFGyTp5QxO1Xnhi3TpP3s3zBa1RhfMvAHdl1/vT2EUvji7MZVZDJ3uomNuyrZfaYAu919/FgXbOXRrz+/ClU1DczIj+Dj548FtBO5IGmwSAg/AvV/eTyE1j17QvIy4jELd/QH4+/uYeMSIhISPj1C9vslXqYUycWc/bUEqoaeg4GO2w6xd+0/8fafWSlhTnP/vMfbm7zhiC66R43peOOmHEVdtMy6Mj/2tjCLPIz07pcXK44J430cIi8BE7qBTYgFWal9Tt37QaWkEBmWsjrKO8PEaE0L5PWqCEtLHEBNNn9XTp3NJlpnfsY/Pd0Lu7wcz515kRE4Pzj24PBuOIsSvMzeWd3NU2tMaaNyGXhnJH840tnc+50p4VwsK6Z/XaexHXnTGHRvNHccuks73evwWBgaQdyQHj3MxBnMlJmWphzpw/nkdd3c9qkYVxmJzB1Z9OBOgS6TKEAvFNWzewxBUwqyeHxt/bwXx+ayQnjCijJzeB7f9vg3YClOzt96/PnpIdpixnqmtqYMSqfbHtycVcPBThupJPLPnF8Ea/d+P5OqYf4lkH3f8a56RGvs7KnUTmfPGsSZ04pSeik7p7A+5Micrktk5mj8xnIe/mU5mWwq6qB6SPz4obaDjT/ceu4kuz5x5ey/bYPxpWNLcpmRF4GL9oW5ZjCLESEWaMLvJno5XVN1DS2kpsRoSA7jV9e4bQg//rWHgCaB+GeFkGmwSAg/Gki108un8uGfbX86Y3dPQaD6oYWLvr5iwBsv21hpxNiWzTG2j01XHXqBG645Hi+v2g2Wf4rwZx0qnpJE+30TTAaWZBJeiTMxn21TC7JIRQSctLDcat2Ds9t7+zsGAigvc8gPRLqcjSMK2RTOHVNbXGzdzsaU5gVt7xDX8wbX8hr2yoHpF/GDSjfvmQGJ3Uz9yAZ7ryEOWM6jw4aTOOHZXt9GuDMiXClhUMU56RzsK6ZyvoWRnbokM6wrSZtGQwsDQaB0Z4mcmWlOxOWeus3+N/ntnjPv/boO3zslHGcPrl95M6mA/U0tcaYO66gy/RFUXY6tU1t3hIS4HQo3/fqdtLDIT551qS4lsHIgkwKs9PZuK+WiSXO1Xp2RiQuGPR2he4O5czvQ0erM3GtLeGTfW++euFxbD5Qx/Ej+79Wv9uBnZ+V1mUaJlnuCdO/5MaR8tlzJ8cF8Z7kZ6Z5azVB/BIY4LRoyuua2V/TFBcoAO/4aDAYWBoMAsI/mshvwrBs/r5mb9yJuqM3dh5i+og83jtQx+Nv7eG5d8t5+ivvY2RBJq3RGHe/4Kwo2tXYc3Dy7eDcucu9Ev35s5u8lUg/cfoEdlYeJistTGNrlBF5mYy1I0ImlTjpIPc2lu87bjhfvmBqr583LzNCSPrW0ZqX6aSKOnZs9ld6JMRvF58yIPtyWwb+3PtAcGfsHtdN+m8g3XhJ547ljn718ZO8ZSjcoaRF2WlxI8XAadEcrGum7FBDp0DmtQw0TTSgtAM5IGK+SWd+44uziZn2Wyd2ZIxh68F6Tp1UzGfOmWQXHIvy82WbWLmtkifX7mPpO3v58gXT4la29HOXZjjk60R+1recwCOv72bTgXoume0MLSzNz/QWXpsy3NmnuzLpJ8+cwMkTep9oFQo5HaJ9GYKZlxmhNC+jx3TSYHP7H3L6MSqpK9+/bDaLz5jA3KPQMuiLhXNGcf35TrAvtS2Djlf+4ASD7RWHOdTQ2mmeQoZdOqRBg8GA0pZBQPgnnfm5J/CdVQ1MLIk/mW87WM9bu6qpa2pjyvAcPmknaLVGYzy8ajd/XL2bkfmZhEPiLZrWFXf0iNtvUF7bxObyeq4+fQIPrtjJd/+6jmE56dy4cAbPbjzAjFF5LJg1kl9ffXKn1kbHhdR6UpiV1qchnbNGF3gnnqHqpAlFzB1b0Od5Dn01tTSXWxbNHtB9DhS3ZdBVMBhbmOUNSR3boa9nvF0TaWt5fdxwVdU/GgwCwr2y7pjTd0+uu6riOzmXbzzAtfev9r6fUto+E/WaMyby8CrnXrz7a5uYMjynx6tqt2Xg3uHrFbsQ2cdOGceDK5y1/L+xYDrD85xlIzIiIUQkbnkJV08jfjpaNG+Ml6Lqyc2Xzup1m8F21tQSnuhiMbsgc1OKows6B+oTfZ3o4zr8TQzPy2Bkfibrk7gfguqeBoMUF4sZHnujjOUbyynJ7bxEcWleBplpIVbvqOKRVbsYlpvBbf82h1uf3EheRoQ6uwTEFN+yBDNG5fPUl8/hhr+s5Z3d1Uwr7TnfPKkkh4xIiJc3V3C4uY0XNh1kWE46M0fl85lzJrG/ttmbJ9Bb52ginadfvnBan7dVQ09GJMz3Fs3itEnDOr3m3rYTOrcMAGaPyWftnpojWr9jjQaDFPf8pnK++ec1ACyaN7rTKJxQSLhgxgjvbl8AV/92JdsqDnP3J07ic79/E3CWKvabMSqfUyYU8c7uai+/353MtDCnTirmkdd388jrToviY/PHEQoJ3/ngzD59jme/dq7XslDHjmvOmNhluX/tqa5mTs8eU8Dyd8upsvdpUP03ZDqQReRiEXlPRLaIyA2DVY9ozPDcuwe80S1D0cG6ZnZUHMYYw1Nr93vl7rr+HX3p/c4V9MI5I/ngCaPYVnGYWaPzWTBrJC9983we+vRpnSYKAcyxnY5T+zAS5ZQOq2teNGtEN1t2bWppbtxwVqW+sWA6l3VxgQPOneCMgQt++nzcYnYqeUOiZSAiYeBO4ANAGfC6iCw1xmzo7j0xY2hpc26A4v6xxGKGtphhT3Uj6ZEQowsyex2v3twWpby2mfzMNEIheOC1nfzk6fe48tTx3LjweJpaonGdj2/vrmbPoUbmjClgTFEWbTFnrHNGJEwsZjqdVKMxw/KNByjKSWf6yDwvNZNrV7bsi5a2GAfrm8lOC/Po6t38bNkmmttinDyhiM0H6jhv+nAmleTwYd/Nzv2mj8zjoU+fxvGj8tl0oI6n1u7j6wumIyKMK87u9j4E5x9fyidOH9+nZbAXzRvNn98s4wvnTeGVLZWcNbWkT59Nqe64o466ctrkYTz06dP4+L0reWjlLr7qW7pbJUcGconjpCshcgZwszFmgf3+RgBjzG3dvSdj1DQzavEvAIiEnHv+dvwoIs6Y5IxI2M5UDdEWNVQ1tJCfmUbMGOqb2rxb+bkKs9Pi7kc7Ij+DkAitUdNtKsMdQ++OmW5sjdLYEkWk/b6t4HTwtrTFCInT/A2JUN/cRlik01Ag99um1lhcHS+aOYLTJg/jjuc2kxEJc881J3tLAvdFdUNLv9epUWoo+NTvVvHatspOncxHyy2LZnHmlNS68BGRN4wx8zuWD4mWATAG2O37vgw4reNGInIdcB3AsDGT+PpFx9HSFqM1ZoiEhEgoRCQslOSm09Qa42BdMy3RGM2tUefRzlgclpNOfXMbIXGWKpg8PMcbxpYWDrFo3hhe3HSQ/bVNCM4M3JA4q1POHJ3PyROKWLGtisPNbc4tJmOG6sZWctLDVDW00NASJTs9TGYkTHNbjFMnFZMeCbG94jAVdc2U5mdQ19RGRX0L0VjMBqb24aFAXGDLTAszvjibxtYok0qyOX96KSLiLQCW6CJpGghUUHx9wXTuen6rt1Dj0ZaTPlROof03VFoGHwUWGGM+bb+/GjjVGPN/u3vP/PnzzerVq7t7WSmlVBe6axkMlQ7kMsC/RvFYYG832yqllBpgQyUYvA5ME5FJIpIOXAEsHeQ6KaXUMWNIJLyMMW0i8kXgaSAMLDHGrB/kaiml1DFjSAQDAGPMk8CTg10PpZQ6Fg2VNJFSSqlBpMFAKaWUBgOllFIaDJRSSjFEJp0lQ0TqgPcGux5JKAEqBrsSCUrFOoPW+2jTeh9dydZ7gjGm04JjQ2Y0URLe62oW3VAnIqtTrd6pWGfQeh9tWu+ja6DrrWkipZRSGgyUUkqldjC4Z7ArkKRUrHcq1hm03keb1vvoGtB6p2wHslJKqYGTyi0DpZRSA0SDgVJKqdQLBiJysYi8JyJbROSGwa5PT0Rkh4isFZG3RWS1LSsWkWUistk+Fg2Bei4RkXIRWecr67Ke4rjdHv81InLSEKv3zSKyxx7zt0Vkoe+1G2293xORBYNU53Ei8i8R2Sgi60Xky7Z8SB/vHuo91I93poisEpF3bL1vseWTRGSlPd5/tEvnIyIZ9vst9vWJQ6ze94nIdt/xnmfL+/93YoxJmS+c5a23ApOBdOAdYOZg16uH+u4ASjqU/Ri4wT6/AfjREKjn+4CTgHW91RNYCDyFc4vm04GVQ6zeNwNf72LbmfbvJQOYZP+OwoNQ51HASfZ5HrDJ1m1IH+8e6j3Uj7cAufZ5GrDSHsdHgSts+d3A5+3zLwB32+dXAH8cpOPdXb3vAy7vYvt+/52kWsvgVGCLMWabMaYFeARYNMh1StQi4H77/H7gskGsCwDGmBeBqg7F3dVzEfCAcawACkVk1NGpabxu6t2dRcAjxphmY8x2YAvO39NRZYzZZ4x50z6vAzbi3AN8SB/vHurdnaFyvI0xpt5+m2a/DPB+4DFb3vF4u7+Hx4ALJNGbjA+AHurdnX7/naRaMBgD7PZ9X0bPf5CDzQDPiMgbInKdLRthjNkHzj8YUDpotetZd/VMhd/BF21TeYkvDTfk6m1TECfiXPWlzPHuUG8Y4sdbRMIi8jZQDizDaaVUG2PauqibV2/7eg0w7OjW2NGx3sYY93jfao/3z0Ukw5b1+3inWjDoKkIP5bGxZxljTgIuAa4XkfcNdoUGwFD/HdwFTAHmAfuAn9ryIVVvEckF/gx8xRhT29OmXZQNpXoP+eNtjIkaY+bh3Fv9VGBGV5vZxyFbbxGZDdwIHA+cAhQD37Kb97veqRYMyoBxvu/HAnsHqS69MsbstY/lwOM4f4gH3OabfSwfvBr2qLt6DunfgTHmgP0nigG/oT01MWTqLSJpOCfUPxhj/mKLh/zx7qreqXC8XcaYauB5nJx6oYi4a7P56+bV275eQN9TkUeEr94X23SdMcY0A79jAI93qgWD14FpdiRAOk4Hz9JBrlOXRCRHRPLc58BFwDqc+i62my0GnhicGvaqu3ouBa6xoxdOB2rc9MZQ0CFP+hGcYw5Ova+wo0UmAdOAVYNQPwHuBTYaY37me2lIH+/u6p0Cx3u4iBTa51nAhTj9Hf8CLrebdTze7u/hcuA5Y3toj6Zu6v2u74JBcPo5/Me7f38ng9FT3p8vnF7zTTh5v+8Mdn16qOdknNEU7wDr3bri5B+XA5vtY/EQqOvDOE38VpwrjGu7qydOc/ROe/zXAvOHWL0ftPVaY/9BRvm2/46t93vAJYNU57Nxmu9rgLft18Khfrx7qPdQP94nAG/Z+q0D/tuWT8YJTluAPwEZtjzTfr/Fvj55iNX7OXu81wG/p33EUb//TnQ5CqWUUimXJlJKKXUEaDBQSimlwUAppZQGA6WUUmgwUEophQYDpZRSaDBQSikF/H/viRaW8Wz7mgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bikes_df['Pont_Jacques_Cartier'].plot()\n",
    "plt.title(\"Pont_Jacques_Cartier\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Value counts\n",
    "\n",
    "Get count of unique values in a particular column/Series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Drama        278\n",
       "Comedy       156\n",
       "Action       136\n",
       "Crime        124\n",
       "Biography     77\n",
       "Adventure     75\n",
       "Animation     62\n",
       "Horror        29\n",
       "Mystery       16\n",
       "Western        9\n",
       "Thriller       5\n",
       "Sci-Fi         5\n",
       "Film-Noir      3\n",
       "Family         2\n",
       "History        1\n",
       "Fantasy        1\n",
       "Name: genre, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what are the unique genre in imdb_df?\n",
    "imdb_df['genre'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d6affb5c8>"
      ]
     },
     "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": [
    "# plotting value counts of unique genres as a bar chart\n",
    "imdb_df['genre'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d6b094ec8>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting value counts of unique genres as a pie chart\n",
    "imdb_df['genre'].value_counts().plot.pie()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Index\n",
    "\n",
    "### DATAFRAME = COLUMNS + INDEX + ND DATA\n",
    "\n",
    "### SERIES = INDEX + 1-D DATA\n",
    "\n",
    "**Index** or (**row labels**) is one of the fundamental data structure of pandas. It can be thought of as an **immutable array** and an **ordered set**.\n",
    "\n",
    "> Every row is uniquely identified by its index value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=366, step=1)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show index of bikes_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>Date</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>Rachel / Papineau</th>\n",
       "      <th>Berri1</th>\n",
       "      <th>Maisonneuve_2</th>\n",
       "      <th>Maisonneuve_1</th>\n",
       "      <th>Brébeuf</th>\n",
       "      <th>Parc</th>\n",
       "      <th>PierDup</th>\n",
       "      <th>CSC (Côte Sainte-Catherine)</th>\n",
       "      <th>Pont_Jacques_Cartier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>16</td>\n",
       "      <td>35</td>\n",
       "      <td>51</td>\n",
       "      <td>38</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date Unnamed: 1  Rachel / Papineau  Berri1  Maisonneuve_2  \\\n",
       "0 2012-01-01      00:00                 16      35             51   \n",
       "\n",
       "   Maisonneuve_1  Brébeuf  Parc  PierDup  CSC (Côte Sainte-Catherine)  \\\n",
       "0             38      5.0    26       10                            0   \n",
       "\n",
       "   Pont_Jacques_Cartier  \n",
       "0                  27.0  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get row for date 2012-01-01\n",
    "bikes_df[bikes_df.Date == '2012-01-01' ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### To get row by integer index:\n",
    "\n",
    "Use ``.iloc[]`` for purely integer-location based indexing for selection by position."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date                           2012-01-13 00:00:00\n",
       "Unnamed: 1                                   00:00\n",
       "Rachel / Papineau                                0\n",
       "Berri1                                          75\n",
       "Maisonneuve_2                                  105\n",
       "Maisonneuve_1                                   41\n",
       "Brébeuf                                          4\n",
       "Parc                                            64\n",
       "PierDup                                          2\n",
       "CSC (Côte Sainte-Catherine)                      0\n",
       "Pont_Jacques_Cartier                             1\n",
       "Name: 12, dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# show 11th row of imdb_df using iloc\n",
    "bikes_df.iloc[12]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting rows where column has a particular value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>genre</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8.9</td>\n",
       "      <td>The Lord of the Rings: The Return of the King</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>201</td>\n",
       "      <td>[u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Fellowship of the Ring</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>178</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Orlando Bl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>8.8</td>\n",
       "      <td>The Lord of the Rings: The Two Towers</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>179</td>\n",
       "      <td>[u'Elijah Wood', u'Ian McKellen', u'Viggo Mort...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>8.7</td>\n",
       "      <td>Interstellar</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>169</td>\n",
       "      <td>[u'Matthew McConaughey', u'Anne Hathaway', u'J...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>8.5</td>\n",
       "      <td>Back to the Future</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>116</td>\n",
       "      <td>[u'Michael J. Fox', u'Christopher Lloyd', u'Le...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <td>936</td>\n",
       "      <td>7.4</td>\n",
       "      <td>True Grit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>128</td>\n",
       "      <td>[u'John Wayne', u'Kim Darby', u'Glen Campbell']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>937</td>\n",
       "      <td>7.4</td>\n",
       "      <td>Labyrinth</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>101</td>\n",
       "      <td>[u'David Bowie', u'Jennifer Connelly', u'Toby ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>943</td>\n",
       "      <td>7.4</td>\n",
       "      <td>The Bucket List</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>97</td>\n",
       "      <td>[u'Jack Nicholson', u'Morgan Freeman', u'Sean ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>953</td>\n",
       "      <td>7.4</td>\n",
       "      <td>The NeverEnding Story</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>102</td>\n",
       "      <td>[u'Noah Hathaway', u'Barret Oliver', u'Tami St...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>975</td>\n",
       "      <td>7.4</td>\n",
       "      <td>Back to the Future Part III</td>\n",
       "      <td>PG</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>118</td>\n",
       "      <td>[u'Michael J. Fox', u'Christopher Lloyd', u'Ma...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>75 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     star_rating                                              title  \\\n",
       "7            8.9      The Lord of the Rings: The Return of the King   \n",
       "10           8.8  The Lord of the Rings: The Fellowship of the Ring   \n",
       "14           8.8              The Lord of the Rings: The Two Towers   \n",
       "15           8.7                                       Interstellar   \n",
       "54           8.5                                 Back to the Future   \n",
       "..           ...                                                ...   \n",
       "936          7.4                                          True Grit   \n",
       "937          7.4                                          Labyrinth   \n",
       "943          7.4                                    The Bucket List   \n",
       "953          7.4                              The NeverEnding Story   \n",
       "975          7.4                        Back to the Future Part III   \n",
       "\n",
       "    content_rating      genre  duration  \\\n",
       "7            PG-13  Adventure       201   \n",
       "10           PG-13  Adventure       178   \n",
       "14           PG-13  Adventure       179   \n",
       "15           PG-13  Adventure       169   \n",
       "54              PG  Adventure       116   \n",
       "..             ...        ...       ...   \n",
       "936            NaN  Adventure       128   \n",
       "937             PG  Adventure       101   \n",
       "943          PG-13  Adventure        97   \n",
       "953             PG  Adventure       102   \n",
       "975             PG  Adventure       118   \n",
       "\n",
       "                                           actors_list  \n",
       "7    [u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...  \n",
       "10   [u'Elijah Wood', u'Ian McKellen', u'Orlando Bl...  \n",
       "14   [u'Elijah Wood', u'Ian McKellen', u'Viggo Mort...  \n",
       "15   [u'Matthew McConaughey', u'Anne Hathaway', u'J...  \n",
       "54   [u'Michael J. Fox', u'Christopher Lloyd', u'Le...  \n",
       "..                                                 ...  \n",
       "936    [u'John Wayne', u'Kim Darby', u'Glen Campbell']  \n",
       "937  [u'David Bowie', u'Jennifer Connelly', u'Toby ...  \n",
       "943  [u'Jack Nicholson', u'Morgan Freeman', u'Sean ...  \n",
       "953  [u'Noah Hathaway', u'Barret Oliver', u'Tami St...  \n",
       "975  [u'Michael J. Fox', u'Christopher Lloyd', u'Ma...  \n",
       "\n",
       "[75 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select only those movies where genre is adventure\n",
    "imdb_df.loc[imdb_df.genre == \"Adventure\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drama\n"
     ]
    }
   ],
   "source": [
    "# which genre has highest number of movies with star rating above 8 and duration more than 130 minutes?\n",
    "best = imdb_df[(imdb_df.star_rating > 8) & (imdb_df.duration > 130)]\n",
    "maxgenre = Counter(best['genre'])\n",
    "Keymax = max(maxgenre, key=maxgenre.get) \n",
    "print(Keymax) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding a new column to DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add a weekday column to bikes_df\n",
    "bikes_df.insert(0,\"weekday\",True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deleting an existing column from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>8</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "     weekday       Date  Rachel / Papineau  Berri1  Maisonneuve_2  \\\n",
       "0       True 2012-01-01                 16      35             51   \n",
       "1       True 2012-02-01                 43      83            153   \n",
       "2       True 2012-03-01                 58     135            248   \n",
       "3       True 2012-04-01                 61     144            318   \n",
       "4       True 2012-05-01                 95     197            330   \n",
       "..       ...        ...                ...     ...            ...   \n",
       "361     True 2012-12-27                  8      12              7   \n",
       "362     True 2012-12-28                  0      35              3   \n",
       "363     True 2012-12-29                  0      27              8   \n",
       "364     True 2012-12-30                  0       5              1   \n",
       "365     True 2012-12-31                  0       4              3   \n",
       "\n",
       "     Maisonneuve_1  Brébeuf  Parc  PierDup  CSC (Côte Sainte-Catherine)  \\\n",
       "0               38      5.0    26       10                            0   \n",
       "1               68     11.0    53        6                            1   \n",
       "2              104      2.0    89        3                            2   \n",
       "3              116      2.0   111        8                            1   \n",
       "4              124      6.0    97       13                            2   \n",
       "..             ...      ...   ...      ...                          ...   \n",
       "361              4      NaN     1        2                            0   \n",
       "362             38      NaN     0        0                            0   \n",
       "363             42      NaN     9        0                            0   \n",
       "364              5      NaN     6        0                            0   \n",
       "365              8      NaN    12        0                            0   \n",
       "\n",
       "     Pont_Jacques_Cartier  \n",
       "0                    27.0  \n",
       "1                    21.0  \n",
       "2                    15.0  \n",
       "3                    19.0  \n",
       "4                    16.0  \n",
       "..                    ...  \n",
       "361                   NaN  \n",
       "362                   NaN  \n",
       "363                   NaN  \n",
       "364                   NaN  \n",
       "365                   NaN  \n",
       "\n",
       "[366 rows x 11 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove column 'Unnamed: 1' from bikes_df\n",
    "bikes_df.drop('Unnamed: 1',axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deleting a row in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>97</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-06-01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>75</td>\n",
       "      <td>146</td>\n",
       "      <td>244</td>\n",
       "      <td>98</td>\n",
       "      <td>4.0</td>\n",
       "      <td>86</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>361</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-12-27</td>\n",
       "      <td>00:00</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>362</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-12-28</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>3</td>\n",
       "      <td>38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>363</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-12-29</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>8</td>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>364</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-12-30</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>365</td>\n",
       "      <td>True</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     weekday       Date Unnamed: 1  Rachel / Papineau  Berri1  Maisonneuve_2  \\\n",
       "1       True 2012-02-01      00:00                 43      83            153   \n",
       "2       True 2012-03-01      00:00                 58     135            248   \n",
       "3       True 2012-04-01      00:00                 61     144            318   \n",
       "4       True 2012-05-01      00:00                 95     197            330   \n",
       "5       True 2012-06-01      00:00                 75     146            244   \n",
       "..       ...        ...        ...                ...     ...            ...   \n",
       "361     True 2012-12-27      00:00                  8      12              7   \n",
       "362     True 2012-12-28      00:00                  0      35              3   \n",
       "363     True 2012-12-29      00:00                  0      27              8   \n",
       "364     True 2012-12-30      00:00                  0       5              1   \n",
       "365     True 2012-12-31      00:00                  0       4              3   \n",
       "\n",
       "     Maisonneuve_1  Brébeuf  Parc  PierDup  CSC (Côte Sainte-Catherine)  \\\n",
       "1               68     11.0    53        6                            1   \n",
       "2              104      2.0    89        3                            2   \n",
       "3              116      2.0   111        8                            1   \n",
       "4              124      6.0    97       13                            2   \n",
       "5               98      4.0    86        4                            0   \n",
       "..             ...      ...   ...      ...                          ...   \n",
       "361              4      NaN     1        2                            0   \n",
       "362             38      NaN     0        0                            0   \n",
       "363             42      NaN     9        0                            0   \n",
       "364              5      NaN     6        0                            0   \n",
       "365              8      NaN    12        0                            0   \n",
       "\n",
       "     Pont_Jacques_Cartier  \n",
       "1                    21.0  \n",
       "2                    15.0  \n",
       "3                    19.0  \n",
       "4                    16.0  \n",
       "5                    17.0  \n",
       "..                    ...  \n",
       "361                   NaN  \n",
       "362                   NaN  \n",
       "363                   NaN  \n",
       "364                   NaN  \n",
       "365                   NaN  \n",
       "\n",
       "[365 rows x 12 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove row no. 1 from bikes_df\n",
    "bikes_df.drop(bikes_df.index[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Group By\n",
    "\n",
    "Any groupby operation involves one of the following operations on the original object. They are −\n",
    "\n",
    "- Splitting the Object\n",
    "\n",
    "- Applying a function\n",
    "\n",
    "- Combining the results\n",
    "\n",
    "In many situations, we split the data into sets and we apply some functionality on each subset. In the apply functionality, we can perform the following operations −\n",
    "\n",
    "- **Aggregation** − computing a summary statistic\n",
    "\n",
    "- **Transformation** − perform some group-specific operation\n",
    "\n",
    "- **Filtration** − discarding the data with some condition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "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>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre</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",
       "      <td>Action</td>\n",
       "      <td>9.0</td>\n",
       "      <td>The Dark Knight</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>152</td>\n",
       "      <td>[u'Christian Bale', u'Heath Ledger', u'Aaron E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Adventure</td>\n",
       "      <td>8.9</td>\n",
       "      <td>The Lord of the Rings: The Return of the King</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>201</td>\n",
       "      <td>[u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Animation</td>\n",
       "      <td>8.6</td>\n",
       "      <td>Spirited Away</td>\n",
       "      <td>PG</td>\n",
       "      <td>125</td>\n",
       "      <td>[u'Daveigh Chase', u'Suzanne Pleshette', u'Miy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Biography</td>\n",
       "      <td>8.9</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>R</td>\n",
       "      <td>195</td>\n",
       "      <td>[u'Liam Neeson', u'Ralph Fiennes', u'Ben Kings...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Comedy</td>\n",
       "      <td>8.6</td>\n",
       "      <td>Life Is Beautiful</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>116</td>\n",
       "      <td>[u'Roberto Benigni', u'Nicoletta Braschi', u'G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Crime</td>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Drama</td>\n",
       "      <td>8.9</td>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>96</td>\n",
       "      <td>[u'Henry Fonda', u'Lee J. Cobb', u'Martin Bals...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Family</td>\n",
       "      <td>7.9</td>\n",
       "      <td>E.T. the Extra-Terrestrial</td>\n",
       "      <td>PG</td>\n",
       "      <td>115</td>\n",
       "      <td>[u'Henry Thomas', u'Drew Barrymore', u'Peter C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Fantasy</td>\n",
       "      <td>7.7</td>\n",
       "      <td>The City of Lost Children</td>\n",
       "      <td>R</td>\n",
       "      <td>112</td>\n",
       "      <td>[u'Ron Perlman', u'Daniel Emilfork', u'Judith ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Film-Noir</td>\n",
       "      <td>8.3</td>\n",
       "      <td>The Third Man</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>93</td>\n",
       "      <td>[u'Orson Welles', u'Joseph Cotten', u'Alida Va...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>History</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Battleship Potemkin</td>\n",
       "      <td>UNRATED</td>\n",
       "      <td>66</td>\n",
       "      <td>[u'Aleksandr Antonov', u'Vladimir Barsky', u'G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Horror</td>\n",
       "      <td>8.6</td>\n",
       "      <td>Psycho</td>\n",
       "      <td>R</td>\n",
       "      <td>109</td>\n",
       "      <td>[u'Anthony Perkins', u'Janet Leigh', u'Vera Mi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Mystery</td>\n",
       "      <td>8.6</td>\n",
       "      <td>Rear Window</td>\n",
       "      <td>APPROVED</td>\n",
       "      <td>112</td>\n",
       "      <td>[u'James Stewart', u'Grace Kelly', u'Wendell C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Sci-Fi</td>\n",
       "      <td>8.2</td>\n",
       "      <td>Blade Runner</td>\n",
       "      <td>R</td>\n",
       "      <td>117</td>\n",
       "      <td>[u'Harrison Ford', u'Rutger Hauer', u'Sean You...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Thriller</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Shadow of a Doubt</td>\n",
       "      <td>APPROVED</td>\n",
       "      <td>108</td>\n",
       "      <td>[u'Teresa Wright', u'Joseph Cotten', u'Macdona...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Western</td>\n",
       "      <td>8.9</td>\n",
       "      <td>The Good, the Bad and the Ugly</td>\n",
       "      <td>NOT RATED</td>\n",
       "      <td>161</td>\n",
       "      <td>[u'Clint Eastwood', u'Eli Wallach', u'Lee Van ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           star_rating                                          title  \\\n",
       "genre                                                                   \n",
       "Action             9.0                                The Dark Knight   \n",
       "Adventure          8.9  The Lord of the Rings: The Return of the King   \n",
       "Animation          8.6                                  Spirited Away   \n",
       "Biography          8.9                               Schindler's List   \n",
       "Comedy             8.6                              Life Is Beautiful   \n",
       "Crime              9.3                       The Shawshank Redemption   \n",
       "Drama              8.9                                   12 Angry Men   \n",
       "Family             7.9                     E.T. the Extra-Terrestrial   \n",
       "Fantasy            7.7                      The City of Lost Children   \n",
       "Film-Noir          8.3                                  The Third Man   \n",
       "History            8.0                            Battleship Potemkin   \n",
       "Horror             8.6                                         Psycho   \n",
       "Mystery            8.6                                    Rear Window   \n",
       "Sci-Fi             8.2                                   Blade Runner   \n",
       "Thriller           8.0                              Shadow of a Doubt   \n",
       "Western            8.9                 The Good, the Bad and the Ugly   \n",
       "\n",
       "          content_rating  duration  \\\n",
       "genre                                \n",
       "Action             PG-13       152   \n",
       "Adventure          PG-13       201   \n",
       "Animation             PG       125   \n",
       "Biography              R       195   \n",
       "Comedy             PG-13       116   \n",
       "Crime                  R       142   \n",
       "Drama          NOT RATED        96   \n",
       "Family                PG       115   \n",
       "Fantasy                R       112   \n",
       "Film-Noir      NOT RATED        93   \n",
       "History          UNRATED        66   \n",
       "Horror                 R       109   \n",
       "Mystery         APPROVED       112   \n",
       "Sci-Fi                 R       117   \n",
       "Thriller        APPROVED       108   \n",
       "Western        NOT RATED       161   \n",
       "\n",
       "                                                 actors_list  \n",
       "genre                                                         \n",
       "Action     [u'Christian Bale', u'Heath Ledger', u'Aaron E...  \n",
       "Adventure  [u'Elijah Wood', u'Viggo Mortensen', u'Ian McK...  \n",
       "Animation  [u'Daveigh Chase', u'Suzanne Pleshette', u'Miy...  \n",
       "Biography  [u'Liam Neeson', u'Ralph Fiennes', u'Ben Kings...  \n",
       "Comedy     [u'Roberto Benigni', u'Nicoletta Braschi', u'G...  \n",
       "Crime      [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...  \n",
       "Drama      [u'Henry Fonda', u'Lee J. Cobb', u'Martin Bals...  \n",
       "Family     [u'Henry Thomas', u'Drew Barrymore', u'Peter C...  \n",
       "Fantasy    [u'Ron Perlman', u'Daniel Emilfork', u'Judith ...  \n",
       "Film-Noir  [u'Orson Welles', u'Joseph Cotten', u'Alida Va...  \n",
       "History    [u'Aleksandr Antonov', u'Vladimir Barsky', u'G...  \n",
       "Horror     [u'Anthony Perkins', u'Janet Leigh', u'Vera Mi...  \n",
       "Mystery    [u'James Stewart', u'Grace Kelly', u'Wendell C...  \n",
       "Sci-Fi     [u'Harrison Ford', u'Rutger Hauer', u'Sean You...  \n",
       "Thriller   [u'Teresa Wright', u'Joseph Cotten', u'Macdona...  \n",
       "Western    [u'Clint Eastwood', u'Eli Wallach', u'Lee Van ...  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group imdb_df by movie genres\n",
    "genre = imdb_df.groupby('genre')\n",
    "genre.first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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>star_rating</th>\n",
       "      <th>title</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>duration</th>\n",
       "      <th>actors_list</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genre</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",
       "      <td>Crime</td>\n",
       "      <td>9.3</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>R</td>\n",
       "      <td>142</td>\n",
       "      <td>[u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       star_rating                     title content_rating  duration  \\\n",
       "genre                                                                   \n",
       "Crime          9.3  The Shawshank Redemption              R       142   \n",
       "\n",
       "                                             actors_list  \n",
       "genre                                                     \n",
       "Crime  [u'Tim Robbins', u'Morgan Freeman', u'Bob Gunt...  "
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get crime movies group\n",
    "crime = imdb_df[imdb_df.genre == 'Crime'].groupby('genre')\n",
    "crime.first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "genre\n",
       "Action       126.485294\n",
       "Adventure    134.840000\n",
       "Animation     96.596774\n",
       "Biography    131.844156\n",
       "Comedy       107.602564\n",
       "Crime        122.298387\n",
       "Drama        126.539568\n",
       "Family       107.500000\n",
       "Fantasy      112.000000\n",
       "Film-Noir     97.333333\n",
       "History       66.000000\n",
       "Horror       102.517241\n",
       "Mystery      115.625000\n",
       "Sci-Fi       109.000000\n",
       "Thriller     114.200000\n",
       "Western      136.666667\n",
       "Name: duration, dtype: float64"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get mean of movie durations for each group\n",
    "imdb_df.groupby('genre').duration.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "genre\n",
       "Action       126.485294\n",
       "Adventure    134.840000\n",
       "Animation     96.596774\n",
       "Biography    131.844156\n",
       "Comedy       107.602564\n",
       "Crime        122.298387\n",
       "Drama        126.539568\n",
       "Family       107.500000\n",
       "Fantasy      112.000000\n",
       "Film-Noir     97.333333\n",
       "History       66.000000\n",
       "Horror       102.517241\n",
       "Mystery      115.625000\n",
       "Sci-Fi       109.000000\n",
       "Thriller     114.200000\n",
       "Western      136.666667\n",
       "Name: duration, dtype: float64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# change duration of all movies in a particular genre to mean duration of the group\n",
    "imdb_df.groupby('genre').duration.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop groups/genres that do not have average movie duration greater than 120.\n",
    "#imdb_df.drop((imdb_df.groupby('genre').duration.mean()) < 120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# group weekday wise bikers count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get weekday wise biker count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot weekday wise biker count for 'Berri1'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://memegenerator.net/img/instances/500x/73988569/pythonpandas-is-easy-import-and-go.jpg)"
   ]
  }
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