investigate-TMDb.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Investigate TMDb\n",
    "\n",
    "## Table of Contents\n",
    "<ul>\n",
    "<li><a href=\"#intro\">Introduction</a></li>\n",
    "<li><a href=\"#wrangling\">Data Wrangling</a></li>\n",
    "<li><a href=\"#eda\">Exploratory Data Analysis</a></li>\n",
    "<li><a href=\"#conclusions\">Conclusions</a></li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='intro'></a>\n",
    "## Introduction\n",
    "\n",
    "This data set contains informationa about 10,000 movies collected from The Movie Database (TMDb),including user ratings and revenue.\n",
    "\n",
    "[Kaggle summary](https://www.kaggle.com/tmdb/tmdb-movie-metadata)\n",
    ">What can we say about the success of a movie before it is released? Are there certain companies (Pixar?) that have found a consistent formula? Given that major films costing over $100 million to produce can still flop, this question is more important than ever to the industry. Film aficionados might have different interests. Can we predict which films will be highly rated, whether or not they are a commercial success?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import statement\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "# for showing graphs inside the same window\n",
    "%matplotlib inline\n",
    "# for setting decimal places while diplaying dataframe numbers\n",
    "pd.options.display.float_format = \"{:.2f}\".format\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling\n",
    "\n",
    "### General Properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the data\n",
    "file_name = 'tmdb-movies.csv'\n",
    "df = pd.read_csv(file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\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>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>homepage</th>\n",
       "      <th>director</th>\n",
       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
       "      <th>overview</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>tt0369610</td>\n",
       "      <td>32.99</td>\n",
       "      <td>150000000</td>\n",
       "      <td>1513528810</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...</td>\n",
       "      <td>http://www.jurassicworld.com/</td>\n",
       "      <td>Colin Trevorrow</td>\n",
       "      <td>The park is open.</td>\n",
       "      <td>...</td>\n",
       "      <td>Twenty-two years after the events of Jurassic ...</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6/9/15</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.50</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>1392445892.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.42</td>\n",
       "      <td>150000000</td>\n",
       "      <td>378436354</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...</td>\n",
       "      <td>http://www.madmaxmovie.com/</td>\n",
       "      <td>George Miller</td>\n",
       "      <td>What a Lovely Day.</td>\n",
       "      <td>...</td>\n",
       "      <td>An apocalyptic story set in the furthest reach...</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Village Roadshow Pictures|Kennedy Miller Produ...</td>\n",
       "      <td>5/13/15</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>348161292.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.11</td>\n",
       "      <td>110000000</td>\n",
       "      <td>295238201</td>\n",
       "      <td>Insurgent</td>\n",
       "      <td>Shailene Woodley|Theo James|Kate Winslet|Ansel...</td>\n",
       "      <td>http://www.thedivergentseries.movie/#insurgent</td>\n",
       "      <td>Robert Schwentke</td>\n",
       "      <td>One Choice Can Destroy You</td>\n",
       "      <td>...</td>\n",
       "      <td>Beatrice Prior must confront her inner demons ...</td>\n",
       "      <td>119</td>\n",
       "      <td>Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Summit Entertainment|Mandeville Films|Red Wago...</td>\n",
       "      <td>3/18/15</td>\n",
       "      <td>2480</td>\n",
       "      <td>6.30</td>\n",
       "      <td>2015</td>\n",
       "      <td>101199955.47</td>\n",
       "      <td>271619025.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id    imdb_id  popularity     budget     revenue      original_title  \\\n",
       "0  135397  tt0369610       32.99  150000000  1513528810      Jurassic World   \n",
       "1   76341  tt1392190       28.42  150000000   378436354  Mad Max: Fury Road   \n",
       "2  262500  tt2908446       13.11  110000000   295238201           Insurgent   \n",
       "\n",
       "                                                cast  \\\n",
       "0  Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...   \n",
       "1  Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...   \n",
       "2  Shailene Woodley|Theo James|Kate Winslet|Ansel...   \n",
       "\n",
       "                                         homepage          director  \\\n",
       "0                   http://www.jurassicworld.com/   Colin Trevorrow   \n",
       "1                     http://www.madmaxmovie.com/     George Miller   \n",
       "2  http://www.thedivergentseries.movie/#insurgent  Robert Schwentke   \n",
       "\n",
       "                      tagline  ...  \\\n",
       "0           The park is open.  ...   \n",
       "1          What a Lovely Day.  ...   \n",
       "2  One Choice Can Destroy You  ...   \n",
       "\n",
       "                                            overview runtime  \\\n",
       "0  Twenty-two years after the events of Jurassic ...     124   \n",
       "1  An apocalyptic story set in the furthest reach...     120   \n",
       "2  Beatrice Prior must confront her inner demons ...     119   \n",
       "\n",
       "                                      genres  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller   \n",
       "1  Action|Adventure|Science Fiction|Thriller   \n",
       "2         Adventure|Science Fiction|Thriller   \n",
       "\n",
       "                                production_companies release_date vote_count  \\\n",
       "0  Universal Studios|Amblin Entertainment|Legenda...       6/9/15       5562   \n",
       "1  Village Roadshow Pictures|Kennedy Miller Produ...      5/13/15       6185   \n",
       "2  Summit Entertainment|Mandeville Films|Red Wago...      3/18/15       2480   \n",
       "\n",
       "   vote_average  release_year   budget_adj   revenue_adj  \n",
       "0          6.50          2015 137999939.28 1392445892.52  \n",
       "1          7.10          2015 137999939.28  348161292.49  \n",
       "2          6.30          2015 101199955.47  271619025.41  \n",
       "\n",
       "[3 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exploring the data\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10866 entries, 0 to 10865\n",
      "Data columns (total 21 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   id                    10866 non-null  int64  \n",
      " 1   imdb_id               10856 non-null  object \n",
      " 2   popularity            10866 non-null  float64\n",
      " 3   budget                10866 non-null  int64  \n",
      " 4   revenue               10866 non-null  int64  \n",
      " 5   original_title        10866 non-null  object \n",
      " 6   cast                  10790 non-null  object \n",
      " 7   homepage              2936 non-null   object \n",
      " 8   director              10822 non-null  object \n",
      " 9   tagline               8042 non-null   object \n",
      " 10  keywords              9373 non-null   object \n",
      " 11  overview              10862 non-null  object \n",
      " 12  runtime               10866 non-null  int64  \n",
      " 13  genres                10843 non-null  object \n",
      " 14  production_companies  9836 non-null   object \n",
      " 15  release_date          10866 non-null  object \n",
      " 16  vote_count            10866 non-null  int64  \n",
      " 17  vote_average          10866 non-null  float64\n",
      " 18  release_year          10866 non-null  int64  \n",
      " 19  budget_adj            10866 non-null  float64\n",
      " 20  revenue_adj           10866 non-null  float64\n",
      "dtypes: float64(4), int64(6), object(11)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                         0\n",
       "imdb_id                   10\n",
       "popularity                 0\n",
       "budget                     0\n",
       "revenue                    0\n",
       "original_title             0\n",
       "cast                      76\n",
       "homepage                7930\n",
       "director                  44\n",
       "tagline                 2824\n",
       "keywords                1493\n",
       "overview                   4\n",
       "runtime                    0\n",
       "genres                    23\n",
       "production_companies    1030\n",
       "release_date               0\n",
       "vote_count                 0\n",
       "vote_average               0\n",
       "release_year               0\n",
       "budget_adj                 0\n",
       "revenue_adj                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking for null values in each columns\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "      <td>10866.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>66064.18</td>\n",
       "      <td>0.65</td>\n",
       "      <td>14625701.09</td>\n",
       "      <td>39823319.79</td>\n",
       "      <td>102.07</td>\n",
       "      <td>217.39</td>\n",
       "      <td>5.97</td>\n",
       "      <td>2001.32</td>\n",
       "      <td>17551039.82</td>\n",
       "      <td>51364363.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>92130.14</td>\n",
       "      <td>1.00</td>\n",
       "      <td>30913213.83</td>\n",
       "      <td>117003486.58</td>\n",
       "      <td>31.38</td>\n",
       "      <td>575.62</td>\n",
       "      <td>0.94</td>\n",
       "      <td>12.81</td>\n",
       "      <td>34306155.72</td>\n",
       "      <td>144632485.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1960.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10596.25</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>90.00</td>\n",
       "      <td>17.00</td>\n",
       "      <td>5.40</td>\n",
       "      <td>1995.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20669.00</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>99.00</td>\n",
       "      <td>38.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>2006.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75610.00</td>\n",
       "      <td>0.71</td>\n",
       "      <td>15000000.00</td>\n",
       "      <td>24000000.00</td>\n",
       "      <td>111.00</td>\n",
       "      <td>145.75</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2011.00</td>\n",
       "      <td>20853251.08</td>\n",
       "      <td>33697095.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.00</td>\n",
       "      <td>32.99</td>\n",
       "      <td>425000000.00</td>\n",
       "      <td>2781505847.00</td>\n",
       "      <td>900.00</td>\n",
       "      <td>9767.00</td>\n",
       "      <td>9.20</td>\n",
       "      <td>2015.00</td>\n",
       "      <td>425000000.00</td>\n",
       "      <td>2827123750.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  popularity       budget       revenue  runtime  vote_count  \\\n",
       "count  10866.00    10866.00     10866.00      10866.00 10866.00    10866.00   \n",
       "mean   66064.18        0.65  14625701.09   39823319.79   102.07      217.39   \n",
       "std    92130.14        1.00  30913213.83  117003486.58    31.38      575.62   \n",
       "min        5.00        0.00         0.00          0.00     0.00       10.00   \n",
       "25%    10596.25        0.21         0.00          0.00    90.00       17.00   \n",
       "50%    20669.00        0.38         0.00          0.00    99.00       38.00   \n",
       "75%    75610.00        0.71  15000000.00   24000000.00   111.00      145.75   \n",
       "max   417859.00       32.99 425000000.00 2781505847.00   900.00     9767.00   \n",
       "\n",
       "       vote_average  release_year   budget_adj   revenue_adj  \n",
       "count      10866.00      10866.00     10866.00      10866.00  \n",
       "mean           5.97       2001.32  17551039.82   51364363.25  \n",
       "std            0.94         12.81  34306155.72  144632485.04  \n",
       "min            1.50       1960.00         0.00          0.00  \n",
       "25%            5.40       1995.00         0.00          0.00  \n",
       "50%            6.00       2006.00         0.00          0.00  \n",
       "75%            6.60       2011.00  20853251.08   33697095.72  \n",
       "max            9.20       2015.00 425000000.00 2827123750.41  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Columns Description**\n",
    "\n",
    "|Columns|Description|\n",
    "|:---|:---|\n",
    "|imdb_id:|ID in IMDB site|\n",
    "|popularity|Metric to help boost search results based on votes, vies, favorites, and votes|\n",
    "|budget|Budget spent on movie when it's made|\n",
    "|revenue|Revenue for the movie when it's released|\n",
    "|original_title|Movie Name|\n",
    "|cast|Cast members|\n",
    "|homepage|Movie site|\n",
    "|director|Movie Director|\n",
    "|tagline|Movie tagline|\n",
    "|keywords|Movie keywords|\n",
    "|overview|Brief movie description|\n",
    "|runtime|Movie duration in minutes|\n",
    "|genres|Movie genre/s|\n",
    "|production_companies|Production company/ies|\n",
    "|release_date|release date (mm/dd/yy)|\n",
    "|vote_count|number of voters|\n",
    "|vote_average|Avg vote (10 point score)|\n",
    "|release_year|Realse year (dddd)|\n",
    "|budget_adj|Budget spent on movie in terms of 2010 dollars, accounting for inflation overtime|\n",
    "|revenue_adj|Revenue for the movie in terms of 2010 dollars, accounting for inflation overtime|\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking for Issues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>homepage</th>\n",
       "      <th>director</th>\n",
       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
       "      <th>overview</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2090</th>\n",
       "      <td>42194</td>\n",
       "      <td>tt0411951</td>\n",
       "      <td>0.60</td>\n",
       "      <td>30000000</td>\n",
       "      <td>967000</td>\n",
       "      <td>TEKKEN</td>\n",
       "      <td>Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dwight H. Little</td>\n",
       "      <td>Survival is no game</td>\n",
       "      <td>...</td>\n",
       "      <td>In the year of 2039, after World Wars destroy ...</td>\n",
       "      <td>92</td>\n",
       "      <td>Crime|Drama|Action|Thriller|Science Fiction</td>\n",
       "      <td>Namco|Light Song Films</td>\n",
       "      <td>3/20/10</td>\n",
       "      <td>110</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2010</td>\n",
       "      <td>30000000.00</td>\n",
       "      <td>967000.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id    imdb_id  popularity    budget  revenue original_title  \\\n",
       "2090  42194  tt0411951        0.60  30000000   967000         TEKKEN   \n",
       "\n",
       "                                                   cast homepage  \\\n",
       "2090  Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...      NaN   \n",
       "\n",
       "              director              tagline  ...  \\\n",
       "2090  Dwight H. Little  Survival is no game  ...   \n",
       "\n",
       "                                               overview runtime  \\\n",
       "2090  In the year of 2039, after World Wars destroy ...      92   \n",
       "\n",
       "                                           genres    production_companies  \\\n",
       "2090  Crime|Drama|Action|Thriller|Science Fiction  Namco|Light Song Films   \n",
       "\n",
       "     release_date vote_count  vote_average  release_year  budget_adj  \\\n",
       "2090      3/20/10        110          5.00          2010 30000000.00   \n",
       "\n",
       "      revenue_adj  \n",
       "2090    967000.00  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking dulicate rows\n",
    "df[df.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>...</th>\n",
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       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2089</th>\n",
       "      <td>42194</td>\n",
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       "      <td>0.60</td>\n",
       "      <td>30000000</td>\n",
       "      <td>967000</td>\n",
       "      <td>TEKKEN</td>\n",
       "      <td>Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dwight H. Little</td>\n",
       "      <td>Survival is no game</td>\n",
       "      <td>...</td>\n",
       "      <td>In the year of 2039, after World Wars destroy ...</td>\n",
       "      <td>92</td>\n",
       "      <td>Crime|Drama|Action|Thriller|Science Fiction</td>\n",
       "      <td>Namco|Light Song Films</td>\n",
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       "      <td>5.00</td>\n",
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       "      <td>30000000.00</td>\n",
       "      <td>967000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090</th>\n",
       "      <td>42194</td>\n",
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       "      <td>0.60</td>\n",
       "      <td>30000000</td>\n",
       "      <td>967000</td>\n",
       "      <td>TEKKEN</td>\n",
       "      <td>Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dwight H. Little</td>\n",
       "      <td>Survival is no game</td>\n",
       "      <td>...</td>\n",
       "      <td>In the year of 2039, after World Wars destroy ...</td>\n",
       "      <td>92</td>\n",
       "      <td>Crime|Drama|Action|Thriller|Science Fiction</td>\n",
       "      <td>Namco|Light Song Films</td>\n",
       "      <td>3/20/10</td>\n",
       "      <td>110</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2010</td>\n",
       "      <td>30000000.00</td>\n",
       "      <td>967000.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id    imdb_id  popularity    budget  revenue original_title  \\\n",
       "2089  42194  tt0411951        0.60  30000000   967000         TEKKEN   \n",
       "2090  42194  tt0411951        0.60  30000000   967000         TEKKEN   \n",
       "\n",
       "                                                   cast homepage  \\\n",
       "2089  Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...      NaN   \n",
       "2090  Jon Foo|Kelly Overton|Cary-Hiroyuki Tagawa|Ian...      NaN   \n",
       "\n",
       "              director              tagline  ...  \\\n",
       "2089  Dwight H. Little  Survival is no game  ...   \n",
       "2090  Dwight H. Little  Survival is no game  ...   \n",
       "\n",
       "                                               overview runtime  \\\n",
       "2089  In the year of 2039, after World Wars destroy ...      92   \n",
       "2090  In the year of 2039, after World Wars destroy ...      92   \n",
       "\n",
       "                                           genres    production_companies  \\\n",
       "2089  Crime|Drama|Action|Thriller|Science Fiction  Namco|Light Song Films   \n",
       "2090  Crime|Drama|Action|Thriller|Science Fiction  Namco|Light Song Films   \n",
       "\n",
       "     release_date vote_count  vote_average  release_year  budget_adj  \\\n",
       "2089      3/20/10        110          5.00          2010 30000000.00   \n",
       "2090      3/20/10        110          5.00          2010 30000000.00   \n",
       "\n",
       "      revenue_adj  \n",
       "2089    967000.00  \n",
       "2090    967000.00  \n",
       "\n",
       "[2 rows x 21 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.id==42194]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
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       "      <th>original_title</th>\n",
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       "      <th>homepage</th>\n",
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       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
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       "      <th>genres</th>\n",
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       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>370687</td>\n",
       "      <td>tt3608646</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Mythica: The Necromancer</td>\n",
       "      <td>Melanie Stone|Adam Johnson|Kevin Sorbo|Nicola ...</td>\n",
       "      <td>http://www.mythicamovie.com/#!blank/y9ake</td>\n",
       "      <td>A. Todd Smith</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Mallister takes Thane prisoner and forces Mare...</td>\n",
       "      <td>0</td>\n",
       "      <td>Fantasy|Action|Adventure</td>\n",
       "      <td>Arrowstorm Entertainment|Camera 40 Productions...</td>\n",
       "      <td>12/19/15</td>\n",
       "      <td>11</td>\n",
       "      <td>5.40</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4829</th>\n",
       "      <td>110490</td>\n",
       "      <td>tt1910605</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rags</td>\n",
       "      <td>Keke Palmer|Avan Jogia|Drake Bell|Burkely Duff...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bille Woodruff</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Rags follows the story of Charlie Prince, an o...</td>\n",
       "      <td>0</td>\n",
       "      <td>TV Movie|Comedy|Drama</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5/28/12</td>\n",
       "      <td>24</td>\n",
       "      <td>5.70</td>\n",
       "      <td>2012</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1289</th>\n",
       "      <td>286372</td>\n",
       "      <td>tt1791681</td>\n",
       "      <td>0.04</td>\n",
       "      <td>3250000</td>\n",
       "      <td>0</td>\n",
       "      <td>Treehouse</td>\n",
       "      <td>J. Michael Trautmann|Dana Melanie|Daniel Fredr...</td>\n",
       "      <td>http://www.imdb.com/title/tt1791681/</td>\n",
       "      <td>Michael G. Bartlett</td>\n",
       "      <td>No kids allowed</td>\n",
       "      <td>...</td>\n",
       "      <td>A teenage boy discovers the perpetrators of se...</td>\n",
       "      <td>0</td>\n",
       "      <td>Thriller|Horror|Mystery</td>\n",
       "      <td>Tiberius Film</td>\n",
       "      <td>10/20/14</td>\n",
       "      <td>16</td>\n",
       "      <td>3.40</td>\n",
       "      <td>2014</td>\n",
       "      <td>2993545.92</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id    imdb_id  popularity   budget  revenue  \\\n",
       "92    370687  tt3608646        1.88        0        0   \n",
       "4829  110490  tt1910605        0.14        0        0   \n",
       "1289  286372  tt1791681        0.04  3250000        0   \n",
       "\n",
       "                original_title  \\\n",
       "92    Mythica: The Necromancer   \n",
       "4829                      Rags   \n",
       "1289                 Treehouse   \n",
       "\n",
       "                                                   cast  \\\n",
       "92    Melanie Stone|Adam Johnson|Kevin Sorbo|Nicola ...   \n",
       "4829  Keke Palmer|Avan Jogia|Drake Bell|Burkely Duff...   \n",
       "1289  J. Michael Trautmann|Dana Melanie|Daniel Fredr...   \n",
       "\n",
       "                                       homepage             director  \\\n",
       "92    http://www.mythicamovie.com/#!blank/y9ake        A. Todd Smith   \n",
       "4829                                        NaN       Bille Woodruff   \n",
       "1289       http://www.imdb.com/title/tt1791681/  Michael G. Bartlett   \n",
       "\n",
       "              tagline  ...                                           overview  \\\n",
       "92                NaN  ...  Mallister takes Thane prisoner and forces Mare...   \n",
       "4829              NaN  ...  Rags follows the story of Charlie Prince, an o...   \n",
       "1289  No kids allowed  ...  A teenage boy discovers the perpetrators of se...   \n",
       "\n",
       "     runtime                    genres  \\\n",
       "92         0  Fantasy|Action|Adventure   \n",
       "4829       0     TV Movie|Comedy|Drama   \n",
       "1289       0   Thriller|Horror|Mystery   \n",
       "\n",
       "                                   production_companies release_date  \\\n",
       "92    Arrowstorm Entertainment|Camera 40 Productions...     12/19/15   \n",
       "4829                                                NaN      5/28/12   \n",
       "1289                                      Tiberius Film     10/20/14   \n",
       "\n",
       "     vote_count  vote_average  release_year  budget_adj  revenue_adj  \n",
       "92           11          5.40          2015        0.00         0.00  \n",
       "4829         24          5.70          2012        0.00         0.00  \n",
       "1289         16          3.40          2014  2993545.92         0.00  \n",
       "\n",
       "[3 rows x 21 columns]"
      ]
     },
     "execution_count": 380,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for invalid values\n",
    "df[df.runtime==0].sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "      <td>Boccaccio '70</td>\n",
       "      <td>Marisa Solinas|Germano Gilioli|Anita Ekberg|So...</td>\n",
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       "      <td>Vittorio De Sica|Federico Fellini|Luchino Visc...</td>\n",
       "      <td>The First 3-Act Motion Picture Ever Presented!</td>\n",
       "      <td>...</td>\n",
       "      <td>Four directors tell tales of Eros fit for a 19...</td>\n",
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       "      <td>Alexander SkarsgÃ¥rd|James Ransone|Lee Tergese...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Susanna White|Simon Cellan Jones</td>\n",
       "      <td>The New Face Of American War</td>\n",
       "      <td>...</td>\n",
       "      <td>Marines prepare to invade Iraq at the beginnin...</td>\n",
       "      <td>470</td>\n",
       "      <td>Drama|War|History</td>\n",
       "      <td>Company Pictures</td>\n",
       "      <td>7/13/08</td>\n",
       "      <td>28</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>373977</td>\n",
       "      <td>tt4146128</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Childhood's End</td>\n",
       "      <td>Mike Vogel|Osy Ikhile|Daisy Betts|Georgina Hai...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nick Hurran</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>After peaceful aliens invade earth, humanity f...</td>\n",
       "      <td>246</td>\n",
       "      <td>Thriller|TV Movie|Science Fiction|Drama</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12/14/15</td>\n",
       "      <td>21</td>\n",
       "      <td>6.20</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id    imdb_id  popularity    budget  revenue  \\\n",
       "9666   40724  tt0092571        0.30         0        0   \n",
       "5163  192936  tt0287839        0.21  20000000        0   \n",
       "9867   45267  tt0055805        0.24       126        0   \n",
       "3141   54102  tt0995832        0.34         0        0   \n",
       "559   373977  tt4146128        0.03         0        0   \n",
       "\n",
       "                        original_title  \\\n",
       "9666                   Anne of Avonlea   \n",
       "5163  Frank Herbert's Children of Dune   \n",
       "9867                     Boccaccio '70   \n",
       "3141                   Generation Kill   \n",
       "559                    Childhood's End   \n",
       "\n",
       "                                                   cast homepage  \\\n",
       "9666  Colleen Dewhurst|Patricia Hamilton|Megan Follo...      NaN   \n",
       "5163  Alec Newman|Susan Sarandon|James McAvoy|Julie ...      NaN   \n",
       "9867  Marisa Solinas|Germano Gilioli|Anita Ekberg|So...      NaN   \n",
       "3141  Alexander SkarsgÃ¥rd|James Ransone|Lee Tergese...      NaN   \n",
       "559   Mike Vogel|Osy Ikhile|Daisy Betts|Georgina Hai...      NaN   \n",
       "\n",
       "                                               director  \\\n",
       "9666                                     Kevin Sullivan   \n",
       "5163                                      Greg Yaitanes   \n",
       "9867  Vittorio De Sica|Federico Fellini|Luchino Visc...   \n",
       "3141                   Susanna White|Simon Cellan Jones   \n",
       "559                                         Nick Hurran   \n",
       "\n",
       "                                                tagline  ...  \\\n",
       "9666                                                NaN  ...   \n",
       "5163  Born to rule an empire. Destined to tear it ap...  ...   \n",
       "9867     The First 3-Act Motion Picture Ever Presented!  ...   \n",
       "3141                       The New Face Of American War  ...   \n",
       "559                                                 NaN  ...   \n",
       "\n",
       "                                               overview runtime  \\\n",
       "9666  Anne Shirley, now a schoolteacher, has begun w...     230   \n",
       "5163  The twins of Paul \"Muad'dib\" Atreides become e...     248   \n",
       "9867  Four directors tell tales of Eros fit for a 19...     208   \n",
       "3141  Marines prepare to invade Iraq at the beginnin...     470   \n",
       "559   After peaceful aliens invade earth, humanity f...     246   \n",
       "\n",
       "                                       genres  \\\n",
       "9666                     Drama|Romance|Family   \n",
       "5163  Drama|Science Fiction|Fantasy|Adventure   \n",
       "9867     Fantasy|Drama|Comedy|Romance|Foreign   \n",
       "3141                        Drama|War|History   \n",
       "559   Thriller|TV Movie|Science Fiction|Drama   \n",
       "\n",
       "                                   production_companies release_date  \\\n",
       "9666                                                NaN      5/19/87   \n",
       "5163  New Amsterdam Entertainment|Blixa Film Product...      3/25/03   \n",
       "9867                                            Cineriz      2/22/62   \n",
       "3141                                   Company Pictures      7/13/08   \n",
       "559                                                 NaN     12/14/15   \n",
       "\n",
       "     vote_count  vote_average  release_year  budget_adj  revenue_adj  \n",
       "9666         17          7.40          1987        0.00         0.00  \n",
       "5163         35          6.50          2003 23707052.90         0.00  \n",
       "9867         12          6.50          1962      908.26         0.00  \n",
       "3141         28          6.60          2008        0.00         0.00  \n",
       "559          21          6.20          2015        0.00         0.00  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.runtime>200].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>homepage</th>\n",
       "      <th>director</th>\n",
       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
       "      <th>overview</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>125336</td>\n",
       "      <td>tt2044056</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>The Story of Film: An Odyssey</td>\n",
       "      <td>Mark Cousins|Jean-Michel Frodon|Cari Beauchamp...</td>\n",
       "      <td>http://www.channel4.com/programmes/the-story-o...</td>\n",
       "      <td>Mark Cousins</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>The Story of Film: An Odyssey, written and dir...</td>\n",
       "      <td>900</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9/3/11</td>\n",
       "      <td>14</td>\n",
       "      <td>9.20</td>\n",
       "      <td>2011</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id    imdb_id  popularity  budget  revenue  \\\n",
       "3894  125336  tt2044056        0.01       0        0   \n",
       "\n",
       "                     original_title  \\\n",
       "3894  The Story of Film: An Odyssey   \n",
       "\n",
       "                                                   cast  \\\n",
       "3894  Mark Cousins|Jean-Michel Frodon|Cari Beauchamp...   \n",
       "\n",
       "                                               homepage      director tagline  \\\n",
       "3894  http://www.channel4.com/programmes/the-story-o...  Mark Cousins     NaN   \n",
       "\n",
       "      ...                                           overview runtime  \\\n",
       "3894  ...  The Story of Film: An Odyssey, written and dir...     900   \n",
       "\n",
       "           genres production_companies release_date vote_count  vote_average  \\\n",
       "3894  Documentary                  NaN       9/3/11         14          9.20   \n",
       "\n",
       "      release_year  budget_adj  revenue_adj  \n",
       "3894          2011        0.00         0.00  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.runtime==900]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the max number of genres per movie\n",
    "max(df.genres.str.count('\\|')+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the min number of genres per movie\n",
    "min(df.genres.str.count('\\|')+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the max number of cast member per movie\n",
    "max(df.cast.str.count('\\|')+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the min number of cast member per movie\n",
    "min(df.cast.str.count('\\|')+1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**Data issues**\n",
    "- Remove redundant columns, 20 columns are too much to explore\n",
    "- Drop duplicated row (1)\n",
    "- Solve runtime, revenue, budget 0 values\n",
    "- Genres column have multiple values in one cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# copy of original dataframe\n",
    "df_clean = df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove redundant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'imdb_id', 'popularity', 'budget', 'revenue', 'original_title',\n",
       "       'cast', 'homepage', 'director', 'tagline', 'keywords', 'overview',\n",
       "       'runtime', 'genres', 'production_companies', 'release_date',\n",
       "       'vote_count', 'vote_average', 'release_year', 'budget_adj',\n",
       "       'revenue_adj'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_columns = ['imdb_id', 'popularity','budget', \n",
    "                'revenue', 'cast', 'homepage', \n",
    "                'director', 'tagline', 'keywords', \n",
    "                'overview', 'release_date', 'vote_count']\n",
    "df_clean.drop(drop_columns, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10866 entries, 0 to 10865\n",
      "Data columns (total 9 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   id                    10866 non-null  int64  \n",
      " 1   original_title        10866 non-null  object \n",
      " 2   runtime               10866 non-null  int64  \n",
      " 3   genres                10843 non-null  object \n",
      " 4   production_companies  9836 non-null   object \n",
      " 5   vote_average          10866 non-null  float64\n",
      " 6   release_year          10866 non-null  int64  \n",
      " 7   budget_adj            10866 non-null  float64\n",
      " 8   revenue_adj           10866 non-null  float64\n",
      "dtypes: float64(3), int64(3), object(3)\n",
      "memory usage: 764.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df_clean.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Drop duplicated row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clean.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Solve runtime, revenue_adj, budget_adj low values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**runtime**  \n",
    "only 0 runtime will be addressed, as this clearly missing info.  \n",
    "other small values are most likely true"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[df_clean.runtime==0].id.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# runtime with 0 value is so low, it can be safely dropped\n",
    "df_clean = df_clean[df_clean.runtime!=0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[df_clean.runtime==0].id.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**budget_adj**  \n",
    "all low budget values will be replaced with np.nan as it's illogical and are skewing the statistical measures too much. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5726"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[df_clean.budget_adj < 1000].id.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                                                                 280996\n",
       "original_title                                                 Mr. Holmes\n",
       "runtime                                                               103\n",
       "genres                                                      Mystery|Drama\n",
       "production_companies    BBC Films|See-Saw Films|FilmNation Entertainme...\n",
       "vote_average                                                         6.40\n",
       "release_year                                                         2015\n",
       "budget_adj                                                           0.00\n",
       "revenue_adj                                                   27006774.88\n",
       "Name: 30, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.loc[30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>id</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65750.13</td>\n",
       "      <td>102.36</td>\n",
       "      <td>5.98</td>\n",
       "      <td>2001.30</td>\n",
       "      <td>17598956.85</td>\n",
       "      <td>51515987.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>91819.99</td>\n",
       "      <td>30.95</td>\n",
       "      <td>0.94</td>\n",
       "      <td>12.82</td>\n",
       "      <td>34344214.71</td>\n",
       "      <td>144818992.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1960.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10586.25</td>\n",
       "      <td>90.00</td>\n",
       "      <td>5.40</td>\n",
       "      <td>1995.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20551.00</td>\n",
       "      <td>99.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>2006.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75055.00</td>\n",
       "      <td>112.00</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2011.00</td>\n",
       "      <td>20942458.66</td>\n",
       "      <td>33896668.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.00</td>\n",
       "      <td>900.00</td>\n",
       "      <td>9.20</td>\n",
       "      <td>2015.00</td>\n",
       "      <td>425000000.00</td>\n",
       "      <td>2827123750.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  runtime  vote_average  release_year   budget_adj  \\\n",
       "count  10834.00 10834.00      10834.00      10834.00     10834.00   \n",
       "mean   65750.13   102.36          5.98       2001.30  17598956.85   \n",
       "std    91819.99    30.95          0.94         12.82  34344214.71   \n",
       "min        5.00     2.00          1.50       1960.00         0.00   \n",
       "25%    10586.25    90.00          5.40       1995.00         0.00   \n",
       "50%    20551.00    99.00          6.00       2006.00         0.00   \n",
       "75%    75055.00   112.00          6.60       2011.00  20942458.66   \n",
       "max   417859.00   900.00          9.20       2015.00 425000000.00   \n",
       "\n",
       "        revenue_adj  \n",
       "count      10834.00  \n",
       "mean    51515987.09  \n",
       "std    144818992.37  \n",
       "min            0.00  \n",
       "25%            0.00  \n",
       "50%            0.00  \n",
       "75%     33896668.98  \n",
       "max   2827123750.41  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# low revenue and budget values are too much to be dropped, will be filled with NA\n",
    "# Leaving it 0 affect the average and min values\n",
    "df_clean['budget_adj'] = df_clean['budget_adj'].apply(lambda x: np.nan if x<1000 else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5108"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.budget_adj.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[df_clean.budget_adj < 0].id.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**revenue**  \n",
    "same as budget, but will adress 0 values only, as some movies might actually produce revenue so small (<1000 USD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5985"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[df_clean.revenue_adj == 0].id.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clean['revenue_adj'].replace(0, np.nan, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>id</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>5108.00</td>\n",
       "      <td>4849.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65750.13</td>\n",
       "      <td>102.36</td>\n",
       "      <td>5.98</td>\n",
       "      <td>2001.30</td>\n",
       "      <td>37327151.85</td>\n",
       "      <td>115100887.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>91819.99</td>\n",
       "      <td>30.95</td>\n",
       "      <td>0.94</td>\n",
       "      <td>12.82</td>\n",
       "      <td>42017548.78</td>\n",
       "      <td>198855667.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1960.00</td>\n",
       "      <td>1307.35</td>\n",
       "      <td>2.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10586.25</td>\n",
       "      <td>90.00</td>\n",
       "      <td>5.40</td>\n",
       "      <td>1995.00</td>\n",
       "      <td>8608686.39</td>\n",
       "      <td>10465848.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20551.00</td>\n",
       "      <td>99.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>2006.00</td>\n",
       "      <td>23088908.00</td>\n",
       "      <td>43956661.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75055.00</td>\n",
       "      <td>112.00</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2011.00</td>\n",
       "      <td>50456518.10</td>\n",
       "      <td>131648235.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.00</td>\n",
       "      <td>900.00</td>\n",
       "      <td>9.20</td>\n",
       "      <td>2015.00</td>\n",
       "      <td>425000000.00</td>\n",
       "      <td>2827123750.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  runtime  vote_average  release_year   budget_adj  \\\n",
       "count  10834.00 10834.00      10834.00      10834.00      5108.00   \n",
       "mean   65750.13   102.36          5.98       2001.30  37327151.85   \n",
       "std    91819.99    30.95          0.94         12.82  42017548.78   \n",
       "min        5.00     2.00          1.50       1960.00      1307.35   \n",
       "25%    10586.25    90.00          5.40       1995.00   8608686.39   \n",
       "50%    20551.00    99.00          6.00       2006.00  23088908.00   \n",
       "75%    75055.00   112.00          6.60       2011.00  50456518.10   \n",
       "max   417859.00   900.00          9.20       2015.00 425000000.00   \n",
       "\n",
       "        revenue_adj  \n",
       "count       4849.00  \n",
       "mean   115100887.63  \n",
       "std    198855667.98  \n",
       "min            2.37  \n",
       "25%     10465848.09  \n",
       "50%     43956661.16  \n",
       "75%    131648235.91  \n",
       "max   2827123750.41  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Genres splitting\n",
    "Split genres values into multiple rows, split into a new dataframe and preserve the original format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_genres = df_clean.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_genres = df_genres.assign(genres=df_genres.genres.str.split('|')).explode('genres')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>id</th>\n",
       "      <th>original_title</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Action</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6.50</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>1392445892.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6.50</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>1392445892.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Science Fiction</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6.50</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>1392445892.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Thriller</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6.50</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>1392445892.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>120</td>\n",
       "      <td>Action</td>\n",
       "      <td>Village Roadshow Pictures|Kennedy Miller Produ...</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2015</td>\n",
       "      <td>137999939.28</td>\n",
       "      <td>348161292.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id      original_title  runtime           genres  \\\n",
       "0  135397      Jurassic World      124           Action   \n",
       "0  135397      Jurassic World      124        Adventure   \n",
       "0  135397      Jurassic World      124  Science Fiction   \n",
       "0  135397      Jurassic World      124         Thriller   \n",
       "1   76341  Mad Max: Fury Road      120           Action   \n",
       "\n",
       "                                production_companies  vote_average  \\\n",
       "0  Universal Studios|Amblin Entertainment|Legenda...          6.50   \n",
       "0  Universal Studios|Amblin Entertainment|Legenda...          6.50   \n",
       "0  Universal Studios|Amblin Entertainment|Legenda...          6.50   \n",
       "0  Universal Studios|Amblin Entertainment|Legenda...          6.50   \n",
       "1  Village Roadshow Pictures|Kennedy Miller Produ...          7.10   \n",
       "\n",
       "   release_year   budget_adj   revenue_adj  \n",
       "0          2015 137999939.28 1392445892.52  \n",
       "0          2015 137999939.28 1392445892.52  \n",
       "0          2015 137999939.28 1392445892.52  \n",
       "0          2015 137999939.28 1392445892.52  \n",
       "1          2015 137999939.28  348161292.49  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_genres.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Saving the dataframe**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name = 'tmdb_movies_cleaned.csv'\n",
    "df_clean.to_csv(file_name, encoding = 'utf-8', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "## Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>id</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>10834.00</td>\n",
       "      <td>5108.00</td>\n",
       "      <td>4849.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65750.13</td>\n",
       "      <td>102.36</td>\n",
       "      <td>5.98</td>\n",
       "      <td>2001.30</td>\n",
       "      <td>37327151.85</td>\n",
       "      <td>115100887.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>91819.99</td>\n",
       "      <td>30.95</td>\n",
       "      <td>0.94</td>\n",
       "      <td>12.82</td>\n",
       "      <td>42017548.78</td>\n",
       "      <td>198855667.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1960.00</td>\n",
       "      <td>1307.35</td>\n",
       "      <td>2.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10586.25</td>\n",
       "      <td>90.00</td>\n",
       "      <td>5.40</td>\n",
       "      <td>1995.00</td>\n",
       "      <td>8608686.39</td>\n",
       "      <td>10465848.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20551.00</td>\n",
       "      <td>99.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>2006.00</td>\n",
       "      <td>23088908.00</td>\n",
       "      <td>43956661.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>75055.00</td>\n",
       "      <td>112.00</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2011.00</td>\n",
       "      <td>50456518.10</td>\n",
       "      <td>131648235.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.00</td>\n",
       "      <td>900.00</td>\n",
       "      <td>9.20</td>\n",
       "      <td>2015.00</td>\n",
       "      <td>425000000.00</td>\n",
       "      <td>2827123750.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  runtime  vote_average  release_year   budget_adj  \\\n",
       "count  10834.00 10834.00      10834.00      10834.00      5108.00   \n",
       "mean   65750.13   102.36          5.98       2001.30  37327151.85   \n",
       "std    91819.99    30.95          0.94         12.82  42017548.78   \n",
       "min        5.00     2.00          1.50       1960.00      1307.35   \n",
       "25%    10586.25    90.00          5.40       1995.00   8608686.39   \n",
       "50%    20551.00    99.00          6.00       2006.00  23088908.00   \n",
       "75%    75055.00   112.00          6.60       2011.00  50456518.10   \n",
       "max   417859.00   900.00          9.20       2015.00 425000000.00   \n",
       "\n",
       "        revenue_adj  \n",
       "count       4849.00  \n",
       "mean   115100887.63  \n",
       "std    198855667.98  \n",
       "min            2.37  \n",
       "25%     10465848.09  \n",
       "50%     43956661.16  \n",
       "75%    131648235.91  \n",
       "max   2827123750.41  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the correlation between vote, budget, and revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_var = df_clean.copy()\n",
    "df_var.drop(['id', 'release_year', 'original_title', 'production_companies', 'genres'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(8, 8))\n",
    "sns.heatmap(df_var.corr(), annot=True,\n",
    "            xticklabels=['Duration', 'Vote', 'Budget', 'Revenue'], yticklabels=['Duration', 'Vote', 'Budget', 'Revenue'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**  \n",
    "- the strongest correlation among the variables is found between the budget and the revenue\n",
    "- A weaker correlation is found between revenue and both duration and vote\n",
    "- Almost no correlation between vote and both duration and budget. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Impact of voting score on revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize = (15,6))\n",
    "sns.regplot(data=df_clean, x='vote_average', y = 'revenue_adj')\n",
    "plt.xlabel('Vote Score', size=14)\n",
    "plt.ylabel('Revenue (in terms of 2010 USD)', size=14)\n",
    "plt.title('Impact of Vote on Revenue', size=16)\n",
    "plt.xticks(ticks=[2,3,4,5,6,7,8,9])\n",
    "sns.despine()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What's the distribution of genres\n",
    "What genres have significant more releases compared to the overall number of releases. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "genre_names=df_genres.genres.value_counts().index.str.title()\n",
    "genre_count=df_genres.genres.value_counts().values\n",
    "genre_percent = genre_count/(genre_count.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "explode_v = np.array(0.05).repeat(len(genre_names))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = ['{} - {:.1%}'.format(i,j) for i,j in zip(genre_names, genre_percent)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.pie(genre_count, labels=genre_names, explode = explode_v, textprops={'fontsize': 8})\n",
    "plt.title('Genres Distribution').set_fontsize(20)\n",
    "plt.legend(labels, loc='center left', fontsize=12, bbox_to_anchor=(-0.5, 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**  \n",
    "Out of 20 genre, only 4 genres (Drama, Comedy, Thriller, Action) represent more than half of released movies for the studied period (1960 to 2015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How did the top 4 genres change through the years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "gp_1 = df_genres.groupby(['genres', 'release_year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "select_gen = ['Drama', 'Comedy', 'Thriller', 'Action']\n",
    "df_new = pd.DataFrame(gp_1.count().id.reset_index()).rename(columns={'genres': 'Genres'\n",
    "                                                                   , 'release_year': 'Release'\n",
    "                                                                   , 'id': 'Count'})\n",
    "df_new = df_new[df_new.Genres.apply(lambda x: True if x in select_gen else False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_act = df_new[df_new.Genres=='Action'].drop('Genres', axis=1)\n",
    "df_com = df_new[df_new.Genres=='Comedy'].drop('Genres', axis=1)\n",
    "df_dra = df_new[df_new.Genres=='Drama'].drop('Genres', axis=1)\n",
    "df_thr = df_new[df_new.Genres=='Thriller'].drop('Genres', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(12, 4))\n",
    "df_act.plot(kind='line', x='Release',y='Count', label='Action',ax=ax)\n",
    "df_com.plot(kind='line', x='Release',y='Count', label='Comedy',ax=ax)\n",
    "df_dra.plot(kind='line', x='Release',y='Count', label='Drama',ax=ax)\n",
    "df_thr.plot(kind='line', x='Release',y='Count', label='Thriller',ax=ax)\n",
    "plt.title('Genres Change Through The Years').set_fontsize(20)\n",
    "plt.xlabel('Release Year', size=14)\n",
    "plt.ylabel('Number of movies / year',  size=14)\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "plt.legend(ncol=1, frameon=False, loc='center left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**  \n",
    "Out of the top 4 genres:\n",
    "- Drama saw a significant increase in numbers over the years, going from ~20 movies uo to more than 250 movie in 2015\n",
    "- Thriller and Comedy had a moderate rise and are similar in numbers, starting from ~10 and ending with ~180 movie per year\n",
    "- Action movies had the least growth, from 8 movies in 1960 to over 100 movies in 2015"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Genre effect on revenue in last year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "gp_2=df_genres.groupby(['release_year', 'genres'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new2 = pd.DataFrame(gp_2.mean().revenue_adj.reset_index()).rename(columns={'genres': 'Genres',\n",
    "                                                                              'release_year': 'Release',\n",
    "                                                                              'revenue_adj': 'Revenue'})\n",
    "df_new2 = df_new2[df_new2.Release == 2015]\n",
    "df_new2=df_new2.sort_values(by=['Revenue'], ascending=False).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_labels = ['50M', '100M', '150M', '200M', '250M', '300M', '350M']\n",
    "f_ticks = [50000000, 100000000, 150000000, 200000000, 250000000, 300000000, 350000000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize = (15,6))\n",
    "sns.barplot(data =df_new2,  x='Revenue', y='Genres')\n",
    "sns.set_style('whitegrid')\n",
    "plt.xlabel('Revenue (in terms of 2010 USD)', size=14)\n",
    "plt.ylabel('')\n",
    "plt.title('Average Revenue Per Movie Genre In 2015', size=16)\n",
    "plt.xticks(labels=f_labels, ticks= f_ticks)\n",
    "sns.despine(bottom=True, right=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**  \n",
    "- Surprisngly, none of the 4 most common genres hold the best average revenue\n",
    "- Best average revenue for a movie in 2015 was for the adventure movies\n",
    "- Documentry movies have an underwhelming revenue with less than 10 Million USD"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analysis**  \n",
    "- Voting has a clear corelation with revenue, higher voted movies yielded a higher revenue.\n",
    "- The highest revenue was not for the highest rated movies, but was for movies rated between 7 to 8.5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "## Conclusions\n",
    "**Analysis**  \n",
    "This investigation is perfomed to analyze different aspects of movie release through the period of 1960 to 2015. After addressing some minor issue with the quality of the data, the analysis focused on two main variables: revenue and genres.\n",
    "- Between vote, duration, budget and revenue, the strongest correletion is between the budget and the revenue.  \n",
    "- Also, vote had a steady and moderate impact on revenue.  \n",
    "- Through the last 55 years, four major genres dominated the market in terms of number of releases. Drama, Comedy, Thriller, and Action constitute more than 50% of movie releases through the studied period.  \n",
    "- Drama also had a significant increase in movie releases over the years, up to more than 250 movie in 2015.  \n",
    "- Although the high nummber of releases and significant growth in Drama, this genre did poorly in revenues and was not among the top genres to produce income. The best average revenue for a genre in 2015 was for the Adventure movies.  \n",
    "  \n",
    "**Limitations**  \n",
    "- The provided dataset doesn't include every movie released in the studied period. So, the missing movies might actually cause a major change the average vote or revenue.\n",
    "- The popularity column in the initial data provided was too abigious to include in the analysis.\n",
    "- More than half the entries have no values for revenue and budget, this greatly reduces the accuracy of the results.\n",
    "- [(From the kaggle page)](https://www.kaggle.com/tmdb/tmdb-movie-metadata) Are the budgets and revenues all in US dollars? Do they consistently show the global revenues?\n",
    "- The revenues that show cumulative worldwide gross doesn't show how much is domestic and how much is foreign, some movies might do better in USA than in the rest of the world, and others might gain more revenue worldwide.\n",
    "- Revenue is calculated based on box office profit, it doesn't include the profit from selling the movie through streaming services. This could affect the revenue especially in the recent years starting from 2010.  "
   ]
  }
 ],
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