investigate-a-dataset-template.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project: tmdb-movies Data Analysis\n",
    "\n",
    "BY : DAVID KAYODE OLUWADARE\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 information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. In this report, the data analysis process will be used to answer the following questions: \n",
    "        \n",
    "         ● What is the relationship between runtime and vote average?\n",
    "         ● What is the correlation between vote average, popularity and release year\n",
    "         ● What is the yearly revenue change?\n",
    "         ● Checking the percantage distribution of the genre.\n",
    "          \n",
    "   \n",
    "   \n",
    "   As i go on to perform my analysis, some of these columns would neither take a new shape and dimensions as well as get deleted if not needed. The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time\n",
    "   \n",
    "   This report will use some libaries of Python including Numpy, Pandas, and Matplotlib. The import statement of these libraries is stated below:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages and the libraries needed\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling\n",
    "\n",
    "\n",
    "\n",
    "### Data Loading\n",
    "\n",
    "This Data was downloaded and read from the file directory (r'Path where the CSV file is stored\\File name.csv') on my machine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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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>32.985763</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>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.419936</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>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.112507</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>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>tt2488496</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>200000000</td>\n",
       "      <td>2068178225</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...</td>\n",
       "      <td>http://www.starwars.com/films/star-wars-episod...</td>\n",
       "      <td>J.J. Abrams</td>\n",
       "      <td>Every generation has a story.</td>\n",
       "      <td>...</td>\n",
       "      <td>Thirty years after defeating the Galactic Empi...</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>Lucasfilm|Truenorth Productions|Bad Robot</td>\n",
       "      <td>12/15/15</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>168259</td>\n",
       "      <td>tt2820852</td>\n",
       "      <td>9.335014</td>\n",
       "      <td>190000000</td>\n",
       "      <td>1506249360</td>\n",
       "      <td>Furious 7</td>\n",
       "      <td>Vin Diesel|Paul Walker|Jason Statham|Michelle ...</td>\n",
       "      <td>http://www.furious7.com/</td>\n",
       "      <td>James Wan</td>\n",
       "      <td>Vengeance Hits Home</td>\n",
       "      <td>...</td>\n",
       "      <td>Deckard Shaw seeks revenge against Dominic Tor...</td>\n",
       "      <td>137</td>\n",
       "      <td>Action|Crime|Thriller</td>\n",
       "      <td>Universal Pictures|Original Film|Media Rights ...</td>\n",
       "      <td>4/1/15</td>\n",
       "      <td>2947</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.747999e+08</td>\n",
       "      <td>1.385749e+09</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",
       "0  135397  tt0369610   32.985763  150000000  1513528810   \n",
       "1   76341  tt1392190   28.419936  150000000   378436354   \n",
       "2  262500  tt2908446   13.112507  110000000   295238201   \n",
       "3  140607  tt2488496   11.173104  200000000  2068178225   \n",
       "4  168259  tt2820852    9.335014  190000000  1506249360   \n",
       "\n",
       "                 original_title  \\\n",
       "0                Jurassic World   \n",
       "1            Mad Max: Fury Road   \n",
       "2                     Insurgent   \n",
       "3  Star Wars: The Force Awakens   \n",
       "4                     Furious 7   \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",
       "3  Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...   \n",
       "4  Vin Diesel|Paul Walker|Jason Statham|Michelle ...   \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",
       "3  http://www.starwars.com/films/star-wars-episod...       J.J. Abrams   \n",
       "4                           http://www.furious7.com/         James Wan   \n",
       "\n",
       "                         tagline  ...  \\\n",
       "0              The park is open.  ...   \n",
       "1             What a Lovely Day.  ...   \n",
       "2     One Choice Can Destroy You  ...   \n",
       "3  Every generation has a story.  ...   \n",
       "4            Vengeance Hits Home  ...   \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",
       "3  Thirty years after defeating the Galactic Empi...     136   \n",
       "4  Deckard Shaw seeks revenge against Dominic Tor...     137   \n",
       "\n",
       "                                      genres  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller   \n",
       "1  Action|Adventure|Science Fiction|Thriller   \n",
       "2         Adventure|Science Fiction|Thriller   \n",
       "3   Action|Adventure|Science Fiction|Fantasy   \n",
       "4                      Action|Crime|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",
       "3          Lucasfilm|Truenorth Productions|Bad Robot     12/15/15       5292   \n",
       "4  Universal Pictures|Original Film|Media Rights ...       4/1/15       2947   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2           6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3           7.5          2015  1.839999e+08  1.902723e+09  \n",
       "4           7.3          2015  1.747999e+08  1.385749e+09  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading data,and Performing operations to inspect data\n",
    "\n",
    "df = pd.read_csv(r'C:\\Users\\Owner\\Desktop\\Project Folder\\movie\\tmdb-movies.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10866, 21)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the whole dimension of the data\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "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": [
    "#information encompassing the data set\n",
    "\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for duplicates and dropping them \n",
    "\n",
    "df.duplicated().sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "  <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>32.985763</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>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.419936</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>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.112507</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>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>tt2488496</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>200000000</td>\n",
       "      <td>2068178225</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...</td>\n",
       "      <td>http://www.starwars.com/films/star-wars-episod...</td>\n",
       "      <td>J.J. Abrams</td>\n",
       "      <td>Every generation has a story.</td>\n",
       "      <td>...</td>\n",
       "      <td>Thirty years after defeating the Galactic Empi...</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>Lucasfilm|Truenorth Productions|Bad Robot</td>\n",
       "      <td>12/15/15</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>168259</td>\n",
       "      <td>tt2820852</td>\n",
       "      <td>9.335014</td>\n",
       "      <td>190000000</td>\n",
       "      <td>1506249360</td>\n",
       "      <td>Furious 7</td>\n",
       "      <td>Vin Diesel|Paul Walker|Jason Statham|Michelle ...</td>\n",
       "      <td>http://www.furious7.com/</td>\n",
       "      <td>James Wan</td>\n",
       "      <td>Vengeance Hits Home</td>\n",
       "      <td>...</td>\n",
       "      <td>Deckard Shaw seeks revenge against Dominic Tor...</td>\n",
       "      <td>137</td>\n",
       "      <td>Action|Crime|Thriller</td>\n",
       "      <td>Universal Pictures|Original Film|Media Rights ...</td>\n",
       "      <td>4/1/15</td>\n",
       "      <td>2947</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.747999e+08</td>\n",
       "      <td>1.385749e+09</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",
       "0  135397  tt0369610   32.985763  150000000  1513528810   \n",
       "1   76341  tt1392190   28.419936  150000000   378436354   \n",
       "2  262500  tt2908446   13.112507  110000000   295238201   \n",
       "3  140607  tt2488496   11.173104  200000000  2068178225   \n",
       "4  168259  tt2820852    9.335014  190000000  1506249360   \n",
       "\n",
       "                 original_title  \\\n",
       "0                Jurassic World   \n",
       "1            Mad Max: Fury Road   \n",
       "2                     Insurgent   \n",
       "3  Star Wars: The Force Awakens   \n",
       "4                     Furious 7   \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",
       "3  Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...   \n",
       "4  Vin Diesel|Paul Walker|Jason Statham|Michelle ...   \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",
       "3  http://www.starwars.com/films/star-wars-episod...       J.J. Abrams   \n",
       "4                           http://www.furious7.com/         James Wan   \n",
       "\n",
       "                         tagline  ...  \\\n",
       "0              The park is open.  ...   \n",
       "1             What a Lovely Day.  ...   \n",
       "2     One Choice Can Destroy You  ...   \n",
       "3  Every generation has a story.  ...   \n",
       "4            Vengeance Hits Home  ...   \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",
       "3  Thirty years after defeating the Galactic Empi...     136   \n",
       "4  Deckard Shaw seeks revenge against Dominic Tor...     137   \n",
       "\n",
       "                                      genres  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller   \n",
       "1  Action|Adventure|Science Fiction|Thriller   \n",
       "2         Adventure|Science Fiction|Thriller   \n",
       "3   Action|Adventure|Science Fiction|Fantasy   \n",
       "4                      Action|Crime|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",
       "3          Lucasfilm|Truenorth Productions|Bad Robot     12/15/15       5292   \n",
       "4  Universal Pictures|Original Film|Media Rights ...       4/1/15       2947   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2           6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3           7.5          2015  1.839999e+08  1.902723e+09  \n",
       "4           7.3          2015  1.747999e+08  1.385749e+09  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop_duplicates(inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The duplicate value shows '1' which is arguably not needed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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                7929\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": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking the numbers of missing values \n",
    "\n",
    "df.isnull().sum()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nine (9) columns had Nan value from the isnull() method above.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        False\n",
       "1        False\n",
       "2        False\n",
       "3        False\n",
       "4        False\n",
       "         ...  \n",
       "10861     True\n",
       "10862     True\n",
       "10863     True\n",
       "10864     True\n",
       "10865     True\n",
       "Length: 10865, dtype: bool"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any(axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the midst of the null values, we have irrelevant columns which are not needed for the analysis, as well as \n",
    "the case of the budget and revenue confusing the ones having the '_adj' associated with movie in terms of 2010 dollars, accounting for inflation over time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Removing Columns to make the work easier to analyse using the drop() method\n",
    "\n",
    "df.drop(['imdb_id','homepage','budget','revenue','tagline','overview','release_date','keywords'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>popularity</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>director</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</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>32.985763</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...</td>\n",
       "      <td>Colin Trevorrow</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>28.419936</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...</td>\n",
       "      <td>George Miller</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Village Roadshow Pictures|Kennedy Miller Produ...</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  popularity      original_title  \\\n",
       "0  135397   32.985763      Jurassic World   \n",
       "1   76341   28.419936  Mad Max: Fury Road   \n",
       "\n",
       "                                                cast         director  \\\n",
       "0  Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...  Colin Trevorrow   \n",
       "1  Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...    George Miller   \n",
       "\n",
       "   runtime                                     genres  \\\n",
       "0      124  Action|Adventure|Science Fiction|Thriller   \n",
       "1      120  Action|Adventure|Science Fiction|Thriller   \n",
       "\n",
       "                                production_companies  vote_count  \\\n",
       "0  Universal Studios|Amblin Entertainment|Legenda...        5562   \n",
       "1  Village Roadshow Pictures|Kennedy Miller Produ...        6185   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                         0\n",
       "popularity                 0\n",
       "original_title             0\n",
       "cast                      76\n",
       "director                  44\n",
       "runtime                    0\n",
       "genres                    23\n",
       "production_companies    1030\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": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for missing values again\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9772, 13)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#remove rows with null values\n",
    "\n",
    "df.dropna(inplace = True)\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                      0\n",
       "popularity              0\n",
       "original_title          0\n",
       "cast                    0\n",
       "director                0\n",
       "runtime                 0\n",
       "genres                  0\n",
       "production_companies    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": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally there are no null values anymore, \n",
    "and also the shaped had been reduce from (10866, 21) to (9772, 12) Rows and columns respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>director</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...</td>\n",
       "      <td>Colin Trevorrow</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>28.419936</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...</td>\n",
       "      <td>George Miller</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Village Roadshow Pictures|Kennedy Miller Produ...</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>13.112507</td>\n",
       "      <td>Insurgent</td>\n",
       "      <td>Shailene Woodley|Theo James|Kate Winslet|Ansel...</td>\n",
       "      <td>Robert Schwentke</td>\n",
       "      <td>119</td>\n",
       "      <td>Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Summit Entertainment|Mandeville Films|Red Wago...</td>\n",
       "      <td>2480</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...</td>\n",
       "      <td>J.J. Abrams</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>Lucasfilm|Truenorth Productions|Bad Robot</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>168259</td>\n",
       "      <td>9.335014</td>\n",
       "      <td>Furious 7</td>\n",
       "      <td>Vin Diesel|Paul Walker|Jason Statham|Michelle ...</td>\n",
       "      <td>James Wan</td>\n",
       "      <td>137</td>\n",
       "      <td>Action|Crime|Thriller</td>\n",
       "      <td>Universal Pictures|Original Film|Media Rights ...</td>\n",
       "      <td>2947</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.747999e+08</td>\n",
       "      <td>1.385749e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>281957</td>\n",
       "      <td>9.110700</td>\n",
       "      <td>The Revenant</td>\n",
       "      <td>Leonardo DiCaprio|Tom Hardy|Will Poulter|Domhn...</td>\n",
       "      <td>Alejandro GonzÃ¡lez IÃ±Ã¡rritu</td>\n",
       "      <td>156</td>\n",
       "      <td>Western|Drama|Adventure|Thriller</td>\n",
       "      <td>Regency Enterprises|Appian Way|CatchPlay|Anony...</td>\n",
       "      <td>3929</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.241999e+08</td>\n",
       "      <td>4.903142e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>87101</td>\n",
       "      <td>8.654359</td>\n",
       "      <td>Terminator Genisys</td>\n",
       "      <td>Arnold Schwarzenegger|Jason Clarke|Emilia Clar...</td>\n",
       "      <td>Alan Taylor</td>\n",
       "      <td>125</td>\n",
       "      <td>Science Fiction|Action|Thriller|Adventure</td>\n",
       "      <td>Paramount Pictures|Skydance Productions</td>\n",
       "      <td>2598</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.425999e+08</td>\n",
       "      <td>4.053551e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>286217</td>\n",
       "      <td>7.667400</td>\n",
       "      <td>The Martian</td>\n",
       "      <td>Matt Damon|Jessica Chastain|Kristen Wiig|Jeff ...</td>\n",
       "      <td>Ridley Scott</td>\n",
       "      <td>141</td>\n",
       "      <td>Drama|Adventure|Science Fiction</td>\n",
       "      <td>Twentieth Century Fox Film Corporation|Scott F...</td>\n",
       "      <td>4572</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2015</td>\n",
       "      <td>9.935996e+07</td>\n",
       "      <td>5.477497e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>211672</td>\n",
       "      <td>7.404165</td>\n",
       "      <td>Minions</td>\n",
       "      <td>Sandra Bullock|Jon Hamm|Michael Keaton|Allison...</td>\n",
       "      <td>Kyle Balda|Pierre Coffin</td>\n",
       "      <td>91</td>\n",
       "      <td>Family|Animation|Adventure|Comedy</td>\n",
       "      <td>Universal Pictures|Illumination Entertainment</td>\n",
       "      <td>2893</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>6.807997e+07</td>\n",
       "      <td>1.064192e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>150540</td>\n",
       "      <td>6.326804</td>\n",
       "      <td>Inside Out</td>\n",
       "      <td>Amy Poehler|Phyllis Smith|Richard Kind|Bill Ha...</td>\n",
       "      <td>Pete Docter</td>\n",
       "      <td>94</td>\n",
       "      <td>Comedy|Animation|Family</td>\n",
       "      <td>Walt Disney Pictures|Pixar Animation Studios|W...</td>\n",
       "      <td>3935</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.609999e+08</td>\n",
       "      <td>7.854116e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>206647</td>\n",
       "      <td>6.200282</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>Daniel Craig|Christoph Waltz|LÃ©a Seydoux|Ralp...</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>148</td>\n",
       "      <td>Action|Adventure|Crime</td>\n",
       "      <td>Columbia Pictures|Danjaq|B24</td>\n",
       "      <td>3254</td>\n",
       "      <td>6.2</td>\n",
       "      <td>2015</td>\n",
       "      <td>2.253999e+08</td>\n",
       "      <td>8.102203e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>76757</td>\n",
       "      <td>6.189369</td>\n",
       "      <td>Jupiter Ascending</td>\n",
       "      <td>Mila Kunis|Channing Tatum|Sean Bean|Eddie Redm...</td>\n",
       "      <td>Lana Wachowski|Lilly Wachowski</td>\n",
       "      <td>124</td>\n",
       "      <td>Science Fiction|Fantasy|Action|Adventure</td>\n",
       "      <td>Village Roadshow Pictures|Dune Entertainment|A...</td>\n",
       "      <td>1937</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.619199e+08</td>\n",
       "      <td>1.692686e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>264660</td>\n",
       "      <td>6.118847</td>\n",
       "      <td>Ex Machina</td>\n",
       "      <td>Domhnall Gleeson|Alicia Vikander|Oscar Isaac|S...</td>\n",
       "      <td>Alex Garland</td>\n",
       "      <td>108</td>\n",
       "      <td>Drama|Science Fiction</td>\n",
       "      <td>DNA Films|Universal Pictures International (UP...</td>\n",
       "      <td>2854</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+07</td>\n",
       "      <td>3.391985e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>257344</td>\n",
       "      <td>5.984995</td>\n",
       "      <td>Pixels</td>\n",
       "      <td>Adam Sandler|Michelle Monaghan|Peter Dinklage|...</td>\n",
       "      <td>Chris Columbus</td>\n",
       "      <td>105</td>\n",
       "      <td>Action|Comedy|Science Fiction</td>\n",
       "      <td>Columbia Pictures|Happy Madison Productions</td>\n",
       "      <td>1575</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.095996e+07</td>\n",
       "      <td>2.241460e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>99861</td>\n",
       "      <td>5.944927</td>\n",
       "      <td>Avengers: Age of Ultron</td>\n",
       "      <td>Robert Downey Jr.|Chris Hemsworth|Mark Ruffalo...</td>\n",
       "      <td>Joss Whedon</td>\n",
       "      <td>141</td>\n",
       "      <td>Action|Adventure|Science Fiction</td>\n",
       "      <td>Marvel Studios|Prime Focus|Revolution Sun Studios</td>\n",
       "      <td>4304</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2015</td>\n",
       "      <td>2.575999e+08</td>\n",
       "      <td>1.292632e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>273248</td>\n",
       "      <td>5.898400</td>\n",
       "      <td>The Hateful Eight</td>\n",
       "      <td>Samuel L. Jackson|Kurt Russell|Jennifer Jason ...</td>\n",
       "      <td>Quentin Tarantino</td>\n",
       "      <td>167</td>\n",
       "      <td>Crime|Drama|Mystery|Western</td>\n",
       "      <td>Double Feature Films|The Weinstein Company|Fil...</td>\n",
       "      <td>2389</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.047998e+07</td>\n",
       "      <td>1.432992e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>260346</td>\n",
       "      <td>5.749758</td>\n",
       "      <td>Taken 3</td>\n",
       "      <td>Liam Neeson|Forest Whitaker|Maggie Grace|Famke...</td>\n",
       "      <td>Olivier Megaton</td>\n",
       "      <td>109</td>\n",
       "      <td>Crime|Action|Thriller</td>\n",
       "      <td>Twentieth Century Fox Film Corporation|M6 Film...</td>\n",
       "      <td>1578</td>\n",
       "      <td>6.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>4.415998e+07</td>\n",
       "      <td>2.997096e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>102899</td>\n",
       "      <td>5.573184</td>\n",
       "      <td>Ant-Man</td>\n",
       "      <td>Paul Rudd|Michael Douglas|Evangeline Lilly|Cor...</td>\n",
       "      <td>Peyton Reed</td>\n",
       "      <td>115</td>\n",
       "      <td>Science Fiction|Action|Adventure</td>\n",
       "      <td>Marvel Studios</td>\n",
       "      <td>3779</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.195999e+08</td>\n",
       "      <td>4.771138e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>150689</td>\n",
       "      <td>5.556818</td>\n",
       "      <td>Cinderella</td>\n",
       "      <td>Lily James|Cate Blanchett|Richard Madden|Helen...</td>\n",
       "      <td>Kenneth Branagh</td>\n",
       "      <td>112</td>\n",
       "      <td>Romance|Fantasy|Family|Drama</td>\n",
       "      <td>Walt Disney Pictures|Genre Films|Beagle Pug Fi...</td>\n",
       "      <td>1495</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.739996e+07</td>\n",
       "      <td>4.989630e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>131634</td>\n",
       "      <td>5.476958</td>\n",
       "      <td>The Hunger Games: Mockingjay - Part 2</td>\n",
       "      <td>Jennifer Lawrence|Josh Hutcherson|Liam Hemswor...</td>\n",
       "      <td>Francis Lawrence</td>\n",
       "      <td>136</td>\n",
       "      <td>War|Adventure|Science Fiction</td>\n",
       "      <td>Studio Babelsberg|StudioCanal|Lionsgate|Walt D...</td>\n",
       "      <td>2380</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.471999e+08</td>\n",
       "      <td>5.984813e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  popularity                         original_title  \\\n",
       "0   135397   32.985763                         Jurassic World   \n",
       "1    76341   28.419936                     Mad Max: Fury Road   \n",
       "2   262500   13.112507                              Insurgent   \n",
       "3   140607   11.173104           Star Wars: The Force Awakens   \n",
       "4   168259    9.335014                              Furious 7   \n",
       "5   281957    9.110700                           The Revenant   \n",
       "6    87101    8.654359                     Terminator Genisys   \n",
       "7   286217    7.667400                            The Martian   \n",
       "8   211672    7.404165                                Minions   \n",
       "9   150540    6.326804                             Inside Out   \n",
       "10  206647    6.200282                                Spectre   \n",
       "11   76757    6.189369                      Jupiter Ascending   \n",
       "12  264660    6.118847                             Ex Machina   \n",
       "13  257344    5.984995                                 Pixels   \n",
       "14   99861    5.944927                Avengers: Age of Ultron   \n",
       "15  273248    5.898400                      The Hateful Eight   \n",
       "16  260346    5.749758                                Taken 3   \n",
       "17  102899    5.573184                                Ant-Man   \n",
       "18  150689    5.556818                             Cinderella   \n",
       "19  131634    5.476958  The Hunger Games: Mockingjay - Part 2   \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",
       "3   Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...   \n",
       "4   Vin Diesel|Paul Walker|Jason Statham|Michelle ...   \n",
       "5   Leonardo DiCaprio|Tom Hardy|Will Poulter|Domhn...   \n",
       "6   Arnold Schwarzenegger|Jason Clarke|Emilia Clar...   \n",
       "7   Matt Damon|Jessica Chastain|Kristen Wiig|Jeff ...   \n",
       "8   Sandra Bullock|Jon Hamm|Michael Keaton|Allison...   \n",
       "9   Amy Poehler|Phyllis Smith|Richard Kind|Bill Ha...   \n",
       "10  Daniel Craig|Christoph Waltz|LÃ©a Seydoux|Ralp...   \n",
       "11  Mila Kunis|Channing Tatum|Sean Bean|Eddie Redm...   \n",
       "12  Domhnall Gleeson|Alicia Vikander|Oscar Isaac|S...   \n",
       "13  Adam Sandler|Michelle Monaghan|Peter Dinklage|...   \n",
       "14  Robert Downey Jr.|Chris Hemsworth|Mark Ruffalo...   \n",
       "15  Samuel L. Jackson|Kurt Russell|Jennifer Jason ...   \n",
       "16  Liam Neeson|Forest Whitaker|Maggie Grace|Famke...   \n",
       "17  Paul Rudd|Michael Douglas|Evangeline Lilly|Cor...   \n",
       "18  Lily James|Cate Blanchett|Richard Madden|Helen...   \n",
       "19  Jennifer Lawrence|Josh Hutcherson|Liam Hemswor...   \n",
       "\n",
       "                          director  runtime  \\\n",
       "0                  Colin Trevorrow      124   \n",
       "1                    George Miller      120   \n",
       "2                 Robert Schwentke      119   \n",
       "3                      J.J. Abrams      136   \n",
       "4                        James Wan      137   \n",
       "5   Alejandro GonzÃ¡lez IÃ±Ã¡rritu      156   \n",
       "6                      Alan Taylor      125   \n",
       "7                     Ridley Scott      141   \n",
       "8         Kyle Balda|Pierre Coffin       91   \n",
       "9                      Pete Docter       94   \n",
       "10                      Sam Mendes      148   \n",
       "11  Lana Wachowski|Lilly Wachowski      124   \n",
       "12                    Alex Garland      108   \n",
       "13                  Chris Columbus      105   \n",
       "14                     Joss Whedon      141   \n",
       "15               Quentin Tarantino      167   \n",
       "16                 Olivier Megaton      109   \n",
       "17                     Peyton Reed      115   \n",
       "18                 Kenneth Branagh      112   \n",
       "19                Francis Lawrence      136   \n",
       "\n",
       "                                       genres  \\\n",
       "0   Action|Adventure|Science Fiction|Thriller   \n",
       "1   Action|Adventure|Science Fiction|Thriller   \n",
       "2          Adventure|Science Fiction|Thriller   \n",
       "3    Action|Adventure|Science Fiction|Fantasy   \n",
       "4                       Action|Crime|Thriller   \n",
       "5            Western|Drama|Adventure|Thriller   \n",
       "6   Science Fiction|Action|Thriller|Adventure   \n",
       "7             Drama|Adventure|Science Fiction   \n",
       "8           Family|Animation|Adventure|Comedy   \n",
       "9                     Comedy|Animation|Family   \n",
       "10                     Action|Adventure|Crime   \n",
       "11   Science Fiction|Fantasy|Action|Adventure   \n",
       "12                      Drama|Science Fiction   \n",
       "13              Action|Comedy|Science Fiction   \n",
       "14           Action|Adventure|Science Fiction   \n",
       "15                Crime|Drama|Mystery|Western   \n",
       "16                      Crime|Action|Thriller   \n",
       "17           Science Fiction|Action|Adventure   \n",
       "18               Romance|Fantasy|Family|Drama   \n",
       "19              War|Adventure|Science Fiction   \n",
       "\n",
       "                                 production_companies  vote_count  \\\n",
       "0   Universal Studios|Amblin Entertainment|Legenda...        5562   \n",
       "1   Village Roadshow Pictures|Kennedy Miller Produ...        6185   \n",
       "2   Summit Entertainment|Mandeville Films|Red Wago...        2480   \n",
       "3           Lucasfilm|Truenorth Productions|Bad Robot        5292   \n",
       "4   Universal Pictures|Original Film|Media Rights ...        2947   \n",
       "5   Regency Enterprises|Appian Way|CatchPlay|Anony...        3929   \n",
       "6             Paramount Pictures|Skydance Productions        2598   \n",
       "7   Twentieth Century Fox Film Corporation|Scott F...        4572   \n",
       "8       Universal Pictures|Illumination Entertainment        2893   \n",
       "9   Walt Disney Pictures|Pixar Animation Studios|W...        3935   \n",
       "10                       Columbia Pictures|Danjaq|B24        3254   \n",
       "11  Village Roadshow Pictures|Dune Entertainment|A...        1937   \n",
       "12  DNA Films|Universal Pictures International (UP...        2854   \n",
       "13        Columbia Pictures|Happy Madison Productions        1575   \n",
       "14  Marvel Studios|Prime Focus|Revolution Sun Studios        4304   \n",
       "15  Double Feature Films|The Weinstein Company|Fil...        2389   \n",
       "16  Twentieth Century Fox Film Corporation|M6 Film...        1578   \n",
       "17                                     Marvel Studios        3779   \n",
       "18  Walt Disney Pictures|Genre Films|Beagle Pug Fi...        1495   \n",
       "19  Studio Babelsberg|StudioCanal|Lionsgate|Walt D...        2380   \n",
       "\n",
       "    vote_average  release_year        budget       revenue  \n",
       "0            6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1            7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2            6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3            7.5          2015  1.839999e+08  1.902723e+09  \n",
       "4            7.3          2015  1.747999e+08  1.385749e+09  \n",
       "5            7.2          2015  1.241999e+08  4.903142e+08  \n",
       "6            5.8          2015  1.425999e+08  4.053551e+08  \n",
       "7            7.6          2015  9.935996e+07  5.477497e+08  \n",
       "8            6.5          2015  6.807997e+07  1.064192e+09  \n",
       "9            8.0          2015  1.609999e+08  7.854116e+08  \n",
       "10           6.2          2015  2.253999e+08  8.102203e+08  \n",
       "11           5.2          2015  1.619199e+08  1.692686e+08  \n",
       "12           7.6          2015  1.379999e+07  3.391985e+07  \n",
       "13           5.8          2015  8.095996e+07  2.241460e+08  \n",
       "14           7.4          2015  2.575999e+08  1.292632e+09  \n",
       "15           7.4          2015  4.047998e+07  1.432992e+08  \n",
       "16           6.1          2015  4.415998e+07  2.997096e+08  \n",
       "17           7.0          2015  1.195999e+08  4.771138e+08  \n",
       "18           6.8          2015  8.739996e+07  4.989630e+08  \n",
       "19           6.5          2015  1.471999e+08  5.984813e+08  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rename columns having the _adj\n",
    "\n",
    "df.rename(columns = {'budget_adj':'budget', 'revenue_adj':'revenue'}, inplace=True)\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9772 entries, 0 to 10865\n",
      "Data columns (total 13 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   id                    9772 non-null   int64  \n",
      " 1   popularity            9772 non-null   float64\n",
      " 2   original_title        9772 non-null   object \n",
      " 3   cast                  9772 non-null   object \n",
      " 4   director              9772 non-null   object \n",
      " 5   runtime               9772 non-null   int64  \n",
      " 6   genres                9772 non-null   object \n",
      " 7   production_companies  9772 non-null   object \n",
      " 8   vote_count            9772 non-null   int64  \n",
      " 9   vote_average          9772 non-null   float64\n",
      " 10  release_year          9772 non-null   int64  \n",
      " 11  budget                9772 non-null   float64\n",
      " 12  revenue               9772 non-null   float64\n",
      "dtypes: float64(4), int64(4), object(5)\n",
      "memory usage: 1.0+ MB\n"
     ]
    }
   ],
   "source": [
    "#information encompassing the data set\n",
    "\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9772.000000</td>\n",
       "      <td>9.772000e+03</td>\n",
       "      <td>9.772000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>63189.640810</td>\n",
       "      <td>0.694721</td>\n",
       "      <td>102.926627</td>\n",
       "      <td>239.312014</td>\n",
       "      <td>5.963528</td>\n",
       "      <td>2000.878428</td>\n",
       "      <td>1.941599e+07</td>\n",
       "      <td>5.705309e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>90718.059987</td>\n",
       "      <td>1.036931</td>\n",
       "      <td>27.877432</td>\n",
       "      <td>603.011504</td>\n",
       "      <td>0.913174</td>\n",
       "      <td>13.036794</td>\n",
       "      <td>3.566634e+07</td>\n",
       "      <td>1.514499e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1960.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10221.500000</td>\n",
       "      <td>0.232710</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>18677.500000</td>\n",
       "      <td>0.419762</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2005.000000</td>\n",
       "      <td>3.061342e+05</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>70577.250000</td>\n",
       "      <td>0.776408</td>\n",
       "      <td>112.000000</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>2.464268e+07</td>\n",
       "      <td>4.311848e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.000000</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>877.000000</td>\n",
       "      <td>9767.000000</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>4.250000e+08</td>\n",
       "      <td>2.827124e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id   popularity      runtime   vote_count  vote_average  \\\n",
       "count    9772.000000  9772.000000  9772.000000  9772.000000   9772.000000   \n",
       "mean    63189.640810     0.694721   102.926627   239.312014      5.963528   \n",
       "std     90718.059987     1.036931    27.877432   603.011504      0.913174   \n",
       "min         5.000000     0.000188     0.000000    10.000000      1.500000   \n",
       "25%     10221.500000     0.232710    90.000000    18.000000      5.400000   \n",
       "50%     18677.500000     0.419762   100.000000    46.000000      6.000000   \n",
       "75%     70577.250000     0.776408   112.000000   173.000000      6.600000   \n",
       "max    417859.000000    32.985763   877.000000  9767.000000      8.700000   \n",
       "\n",
       "       release_year        budget       revenue  \n",
       "count   9772.000000  9.772000e+03  9.772000e+03  \n",
       "mean    2000.878428  1.941599e+07  5.705309e+07  \n",
       "std       13.036794  3.566634e+07  1.514499e+08  \n",
       "min     1960.000000  0.000000e+00  0.000000e+00  \n",
       "25%     1994.000000  0.000000e+00  0.000000e+00  \n",
       "50%     2005.000000  3.061342e+05  0.000000e+00  \n",
       "75%     2011.000000  2.464268e+07  4.311848e+07  \n",
       "max     2015.000000  4.250000e+08  2.827124e+09  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the statistics above, the minimum budget, revenue, and runtime is 0, as well as the 25% of budgt and revenue are also 0.\n",
    "So, we need to clean the invalid data and re-check statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>popularity</th>\n",
       "      <th>runtime</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3805.000000</td>\n",
       "      <td>3.805000e+03</td>\n",
       "      <td>3.805000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>40040.372668</td>\n",
       "      <td>1.203784</td>\n",
       "      <td>109.351117</td>\n",
       "      <td>534.159001</td>\n",
       "      <td>6.170565</td>\n",
       "      <td>2001.229172</td>\n",
       "      <td>4.471977e+07</td>\n",
       "      <td>1.387159e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>67585.708616</td>\n",
       "      <td>1.480569</td>\n",
       "      <td>19.845678</td>\n",
       "      <td>883.757588</td>\n",
       "      <td>0.792437</td>\n",
       "      <td>11.329616</td>\n",
       "      <td>4.488697e+07</td>\n",
       "      <td>2.169973e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.010335</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>1960.000000</td>\n",
       "      <td>9.693980e-01</td>\n",
       "      <td>2.370705e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5925.000000</td>\n",
       "      <td>0.470651</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>1995.000000</td>\n",
       "      <td>1.354637e+07</td>\n",
       "      <td>1.925371e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11253.000000</td>\n",
       "      <td>0.810805</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>209.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>3.038360e+07</td>\n",
       "      <td>6.284688e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>38579.000000</td>\n",
       "      <td>1.387163</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>584.000000</td>\n",
       "      <td>6.700000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>6.084153e+07</td>\n",
       "      <td>1.658054e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>417859.000000</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>338.000000</td>\n",
       "      <td>9767.000000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>4.250000e+08</td>\n",
       "      <td>2.827124e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id   popularity      runtime   vote_count  vote_average  \\\n",
       "count    3805.000000  3805.000000  3805.000000  3805.000000   3805.000000   \n",
       "mean    40040.372668     1.203784   109.351117   534.159001      6.170565   \n",
       "std     67585.708616     1.480569    19.845678   883.757588      0.792437   \n",
       "min         5.000000     0.010335    15.000000    10.000000      2.200000   \n",
       "25%      5925.000000     0.470651    96.000000    74.000000      5.700000   \n",
       "50%     11253.000000     0.810805   106.000000   209.000000      6.200000   \n",
       "75%     38579.000000     1.387163   119.000000   584.000000      6.700000   \n",
       "max    417859.000000    32.985763   338.000000  9767.000000      8.400000   \n",
       "\n",
       "       release_year        budget       revenue  \n",
       "count   3805.000000  3.805000e+03  3.805000e+03  \n",
       "mean    2001.229172  4.471977e+07  1.387159e+08  \n",
       "std       11.329616  4.488697e+07  2.169973e+08  \n",
       "min     1960.000000  9.693980e-01  2.370705e+00  \n",
       "25%     1995.000000  1.354637e+07  1.925371e+07  \n",
       "50%     2004.000000  3.038360e+07  6.284688e+07  \n",
       "75%     2010.000000  6.084153e+07  1.658054e+08  \n",
       "max     2015.000000  4.250000e+08  2.827124e+09  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cleaning the invalid data and check the statistics again\n",
    "\n",
    "missing_value = df.query('budget == 0 or revenue == 0 or runtime == 0').index\n",
    "df.drop(missing_value, axis=0, inplace=True)\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the data is ready for EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "## Exploratory Data Analysis\n",
    "\n",
    "\n",
    "\n",
    "### Research Question 1 : What is the relationship between runtime and vote average?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Using the histogram to explore the data\n",
    "\n",
    "df.hist(figsize=(10,8),color='black');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Histogram gave an holistic view of what to expect from the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of these two columns\n",
    "\n",
    "df.plot(x='vote_average', y='runtime', kind='scatter', color ='black', figsize=(10,8))\n",
    "plt.title('Vote vs. Runtime')\n",
    "plt.xlabel('Vote in Stars')\n",
    "plt.ylabel('Runtime (mins)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the plot above : \n",
    "   \n",
    "   The vote of movie with a runtime of around 100 minutes are the best votes run from low to high.\n",
    "   Movies with a runtime above or below 100 minues tend to have mid-to-high votes.\n",
    "   movies with long runtimes consistently get higher-than-average votes.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 2 : What is the correlation between vote average, popularity and release year?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This scatter plot above suggests a weaker relationship between vote average and runtime.\n",
    "Though it appears that the longest movies have a higher vote average, there doesn't seem to be a decisive pattern between the two variables in general."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "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": [
    "#plotting the vote average and popularity to see their relationship\n",
    "\n",
    "df.plot(x='vote_average',y='popularity',kind='scatter', color='black', alpha=0.5)\n",
    "plt.title('Vote Average vs Popularity')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 'popularity' and 'vote_average' rows are the bset rows that can be used to understand the favorability of a movie.\n",
    "The scatter plot above illustrates that both columns are positively correlated. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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E+OckrUe6sIqkT7H4/axlHAnM6kPZzMysBWUC/BHA2cAHJD1N+mXr4WUSl7QWsBdwTl8LaGZmfVPmNsknI2I3ScsDS0XEwl6kfyrwNWBUoxUkTQYmA4wbN64XSZuZWTNlWvBPSJoCbEMvXvAh6ePAvIiY3my9iJiSX+g9saOjo2zyZmbWgzIBfkPg16SumicknS5p+xLbbQfsI2k26X2uu0i6uM8lNTOzXukxwEfEqxHxs4j4J2BzYDTwuxLbHRcRa0XEeNJtlb+JiINaLbCZmZVTpgWPpB0lnQncTXpt3z9XWiozM2tZmXeyPgHMBH4GHBMRrzTf4t0i4hbglt5uZ2ZmfVfmLprNImIBgKT1JB0ATIqIjastmpmZtaJMF83yko6SdBfwADAMOKDaYpmZWasaBnhJn5f0G9IF1VWBzwFzI+JbEXHfQBXQzMz6plkXzRnA7cCBETENQFIMSKnMzKxlzQL8WGB/4BRJq5Musi4zIKUyM7OWNeyiiYjnIuKsiNgB2BV4GZgnaZak7w5YCc3MrE9K3QcfEXMi4qSI2BLYD3it0lKZmVnLytwmuYSIeBj4VgVlMTOzflSqBW9mZkOPA7yZWU2Veem2JB0k6Rt5epykraovmpmZtaJMC/5MYFsW/3p1IekeeTMza2NlLrJuHRFbSJoBEBEvSlq24nKZmVmLyrTg35A0jMUv3e4A3q60VGZm1rIyAf404CpgNUn/CdwGnFhpqczMrGU9dtFExFRJ00m/ZhWwX0TMqrxkZmbWkjIv/LgoIg4GHupmnpmZtakyXTQfLE7k/vgtqymOmZn1l2bPgz9O0kJgU0kLJC3M0/OAXwxYCc3MrE+aPU3yxIgYBfwwIkZHxKg8rBIRx/WUsKQRku6SdI+kByT5+TVmZgOozEXW4yTtA+yQZ90SEdeWSPs1YJeIWCRpGeA2SddFxB0tlNfMzEoq86iCE4EjgQfzcGSe11Qki/LkMnnwG6HMzAZImV+y7gVMiIi3ASRdAMwAynTTDAOmA+8HzoiIO7tZZzIwGWDcuHHlS25mZk2VfZrkioXxMWUTj4i3ImICsBawlaSNu1lnSkRMjIiJHR0dZZM2M7MelGnBnwjMkPRb0g+ddqBE670oIl6SdAuwO3B/bwtpZma91+w2ydMl/WNEXApsA1yZh20j4rKeEpbUIWnFPL4csBuFH0uZmVm1mrXg/wycLGkN4HLg0oiY2Yu01wAuyP3wSwE/K3n3jZmZ9YOGAT4ifgT8SNI6wCTgPEkjgEuByyLikWYJR8S9wOb9WVgzMyuvx4usEfFkRHw/IjYHDgQ+AfhhY2Zmba7MffDLSNpb0lTgOuAR4JOVl8zMzFrSsItG0kdIr+nbC7gLuAyYHBGvDFDZzMysBc0usv47cAnw1Yh4YYDKY2Zm/aTZRdadB7IgZmbWv8r+ktXMzIYYB3gzs5pygDczqykHeDOzmnKANzOrKQd4M7OacoA3M6spB3gzs5pygDczqykHeDOzmnKANzOrKQd4M7OacoA3M6spB3gzs5qqLMBLWlvSbyXNkvSApCOrysvMzN6t2Qs/WvUm8JWIuFvSKGC6pJsi4sEK8zQzs6yyFnxEzI2Iu/P4QtKLutesKj8zM1vSgPTBSxoPbA7c2c2yyZKmSZo2f/78gSiOmdl7QuUBXtIKwH8DR0XEgq7LI2JKREyMiIkdHR1VF8fM7D2j0gAvaRlScJ8aEVdWmZeZmS2pyrtoBPwUmBURp1SVj5mZda/KFvx2wMHALpJm5mHPCvMzM7OCym6TjIjbAFWVvpmZNedfspqZ1ZQDvJlZTTnAm5nVlAO8mVlNOcCbmdWUA7yZWU05wJuZ1ZQDvJlZTTnAm5nVlAO8mVlNOcCbmdWUA7yZWU05wJuZ1ZQDvJlZTTnAm5nVlAO8mVlNOcCbmdWUA7yZWU05wJuZ1VRlAV7SuZLmSbq/qjzMzKyxKlvw5wO7V5i+mZk1UVmAj4hbgReqSt/MzJob9D54SZMlTZM0bf78+YNdHDOz2hj0AB8RUyJiYkRM7OjoGOzimJnVxqAHeDMzq4YDvJlZTVV5m+SlwO3AhpLmSPpsVXmZmdm7LV1VwhFxQFVpm5lZz9xFY2ZWUw7wZmY15QBvZlZTDvBmZjXlAG9mVlMO8GZmNeUAb2ZWUw7wZmY15QBvZlZTDvBmZjXlAG9mVlMO8GZmNeUAb2ZWUw7wZmY15QBvZlZTDvBmZjXlAG9mVlMO8GZmNeUAb2ZWU5UGeEm7S3pY0qOSjq0yLzMzW1JlAV7SMOAMYA9gI+AASRtVlZ+ZmS2pyhb8VsCjEfF4RLwOXAbsW2F+ZmZWoIioJmHpU8DuEfG5PH0wsHVEfKnLepOByXlyQ+DhFrNeFXiuxTTaVV3rVtd6QX3rVtd6wdCr2zoR0dHdgqUrzFTdzHvX0SQipgBT+i1TaVpETOyv9NpJXetW13pBfetW13pBvepWZRfNHGDtwvRawDMV5mdmZgVVBvg/AetLWlfSssAk4JoK8zMzs4LKumgi4k1JXwJuAIYB50bEA1XlV9Bv3T1tqK51q2u9oL51q2u9oEZ1q+wiq5mZDS7/ktXMrKYc4M3MaqrtA7ykcyXNk3R/Yd5mkm6XdJ+kX0oaXVi2aV72QF4+Is/fMk8/Kuk0Sd3dxjmgelM3Sf8qaWZheFvShLysrerWy3otI+mCPH+WpOMK27RVvXKZelO3ZSWdl+ffI2mnwjZtVTdJa0v6bf4MHpB0ZJ6/sqSbJP05/12psM1xufwPS/pYYf6QrpukVfL6iySd3iWttqpbjyKirQdgB2AL4P7CvD8BO+bxw4D/yONLA/cCm+XpVYBhefwuYFvS/fnXAXsMpbp12W4T4PHCdFvVrZef2YHAZXl8JDAbGN+O9epD3Y4AzsvjqwHTgaXasW7AGsAWeXwU8AjpESM/AI7N848Fvp/HNwLuAYYD6wKPtet3rQ91Wx7YHjgcOL1LWm1Vt56Gtm/BR8StwAtdZm8I3JrHbwI+mcc/CtwbEffkbZ+PiLckrQGMjojbI31KFwL7VV74HvSybkUHAJcCtGPdelmvAJaXtDSwHPA6sKAd6wW9rttGwM15u3nAS8DEdqxbRMyNiLvz+EJgFrAm6fEiF+TVLmBxOfclHZhfi4gngEeBrepQt4h4JSJuA/5eTKcd69aTtg/wDdwP7JPH92fxD6o2AELSDZLulvS1PH9N0g+vOs3J89pRo7oV/Qs5wDN06taoXj8HXgHmAn8BToqIFxg69YLGdbsH2FfS0pLWBbbMy9q6bpLGA5sDdwKrR8RcSIGSdCYCqbxPFTbrrEMd6tZIW9etO0M1wB8GHCFpOumU6/U8f2nSqdW/5r+fkLQrJR+b0CYa1Q0ASVsDf4uIzj7goVK3RvXaCngLGEs61f+KpPcxdOoFjet2LikITANOBf4IvEkb103SCsB/A0dFxIJmq3YzL5rMH3S9qFvDJLqZ1xZ1a6TKZ9FUJiIeInXHIGkDYK+8aA7wu4h4Li/7Fam/9GLSoxI6te1jE5rUrdMkFrfeIdW57evWpF4HAtdHxBvAPEl/ACYCv2cI1Asa1y0i3gSO7lxP0h+BPwMv0oZ1k7QMKQBOjYgr8+xnJa0REXNzF8W8PL/Ro0ja8v+xl3VrpC3r1syQbMFLWi3/XQo4HvhxXnQDsKmkkblPd0fgwXz6tVDSNvmq9yHALwah6D1qUrfOefuTHr0MvHNq2fZ1a1KvvwC7KFke2AZ4aKjUCxrXLf8fLp/HPwK8GRFt+f+Yy/FTYFZEnFJYdA1waB4/lMXlvAaYJGl47n5aH7irJnXrVjvWrUeDfZW3p4HUWp0LvEE6gn4WOJJ0JfwR4HvkX+Tm9Q8CHiD1i/6gMH9invcYcHpxmyFUt52AO7pJp63q1pt6ASsAV+TP7EHgmHatVx/qNp70+OtZwK9Jj3Vty7qRujSDdBfazDzsSboT7WbSmcfNwMqFbf5PLv/DFO4mqUndZpMupi/Kn/NG7Vi3ngY/qsDMrKaGZBeNmZn1zAHezKymHODNzGrKAd7MrKYc4M3MasoB3oYMSW8pPUnzfqWnNq7Yw/onSPrqABWvM89LJH2xML21pHvz7zLMBpQDvA0lr0bEhIjYmHSP8hGDXaBuHA0cI6kj//DpdOB/RfpVa6/lH4D5e2p94n8cG6puJz/oSdJ6kq6XNF3S7yV9oOvKjdaRtLekOyXNkPRrSavn+Ttq8bP3Z0galecfI+lPuVX+ra75RMSzwEmkR9EeTvpxze2SfljY7gs5rRUk3ZwfjHefpH3z/PFKzy4/E7ib7h84Z9azwf6llQcPZQdgUf47jPTr193z9M3A+nl8a+A3efwE4Ks9rLMSi395+jng5Dz+S2C7PL4C6blNHyW9kFmkxtG1wA7dlHMp0tMKnyD9WnIycHxeNpz08LF1c5qj8/xVSY/cFekXsG8D2wz2PvcwtAf3C9pQspykmaQAOB24KT8h8B+BK7T45TrDixv1sM5awOX5YVPLkoIywB+AUyRNBa6MiDmSPkoK8jPyOiuQnsHS+Sx4ACLibUlnAxMj4vm83aaSPpVXGZO3mwN8V9IOpIC+JrB6XufJiLijl/vHbAkO8DaUvBoREySNIbWejwDOB16KiAlNtluqyTr/BZwSEdcovVLvBICI+J6k/yE9s+QOSbuRWtcnRsTZJcr6dh7I2/1bRNxQXEHSp4EOYMuIeEPSbGBEXvxKiTzMmnIfvA05EfEy8GXgq8CrwBOS9od3Lkpu1mX9BU3WGQM8ncc7nyyIpPUi4r6I+D6pS+UDpKeVHpbPCJC0ZueTJHtwA/BFpUfWImmD/JTJMcC8HNx3Btbp9c4wa8IB3oakiJhBemPSJNILXj4r6R7SUyn37WaTRuucQOq6+T3wXGH9o/LtmPeQDiLXRcSNwCWki6b3kd5GNapEcc8hPSnzbqWXdZ9NOnueSnqF37RcvofK1t+sDD9N0sysptyCNzOrKQd4M7OacoA3M6spB3gzs5pygDczqykHeDOzmnKANzOrqf8PHbagYnrvJ7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grouping new data frame into a new variable release year\n",
    "\n",
    "every_year_df = df.groupby('release_year').mean()\n",
    "plt.bar(every_year_df.index,every_year_df['vote_average'], color = 'black', alpha=0.5)\n",
    "plt.title('Vote Average by Release Year')\n",
    "plt.xlabel('Release Year')\n",
    "plt.ylabel('Vote Average')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I made a new dataframe that grouped the movies by release year. Then I plotted the vote average by release year on a bar chart.\n",
    "\n",
    "\n",
    "In this bar chart, there seems to be a slight downward slope in vote average over time. Though there isn't necessarily a clear trend, it is safe to say that the most highly voted movie were released between 1960 to around 1980 and the popularity between 0 and 5 have the progressing mid-high vote.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 3: Checking the percentage distribution of the genre."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next i want to split the genres column above into different rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Action|Adventure|Science Fiction|Thriller\n",
       "1    Action|Adventure|Science Fiction|Thriller\n",
       "2           Adventure|Science Fiction|Thriller\n",
       "3     Action|Adventure|Science Fiction|Fantasy\n",
       "4                        Action|Crime|Thriller\n",
       "Name: genres, dtype: object"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calling out the column  'genre' \n",
    "\n",
    "df_genres = df['genres']\n",
    "df_genres.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next i want to split the genres column above into different rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Splitting the row with more than one genre into different rows\n",
    "\n",
    "from itertools import chain\n",
    "\n",
    "# Return list from series of '|'-separated strings\n",
    "\n",
    "def my_function(s):\n",
    "    return list(chain.from_iterable(s.str.split('|')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating lengths of splits\n",
    "\n",
    "lens = df['genres'].str.split('|').map(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating new dataframe, repeating or chaining as appropriate\n",
    "\n",
    "df_genres = pd.DataFrame({'genres': my_function(df['genres'])})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Science Fiction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Science Fiction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Science Fiction</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            genres\n",
       "0           Action\n",
       "1        Adventure\n",
       "2  Science Fiction\n",
       "3         Thriller\n",
       "4           Action\n",
       "5        Adventure\n",
       "6  Science Fiction\n",
       "7         Thriller\n",
       "8        Adventure\n",
       "9  Science Fiction"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking the header\n",
    "\n",
    "df_genres.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Drawing the pie chart of genres\n",
    "\n",
    "df_genres['genres'].value_counts().plot(kind='pie', figsize=(6,6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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   "source": [
    "From the pie chart, the 'Animation','Fantasy', and 'Adventure' respectively accounts for a majority of percentage over the year, while other genres like 'Thriller' and 'History' are less frequent to become the most popular genre."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "## CONCLUSIONS\n",
    "\n",
    "In this project, I was able to analyze these qualities and identify which properties are associated with movie popularity.\n",
    "\n",
    "After cleaning the dataset by removing unnecessary, null, and duplicated values, i checked what the relationship between runtime and vote average was.\n",
    "\n",
    "I continued from there to check some correlation between vote average, popularity and release year. Because only vote average was more evenly distributed, I plotted a few charts and the most highly voted movies were released between 1960 and 1980 and popularity between 0 and 5 have the progressing mid-high vote. \n",
    " \n",
    "Next, I plotted various other variables against vote average and found that movies with higher vote averages tend to have higher budgets and higher revenue. \n",
    "\n",
    "And lastly, i Checked the percantage distribution of the genre to decipher what genre have the highest %, and From the pie chart, the 'Animation','Fantasy', and 'Adventure' respectively accounts for a majority of percentage over the year, while other genres like 'Thriller' and 'History' are less frequent to become the most popular genre."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## REFERENCES\n",
    "\n",
    "\n",
    " https://stackoverflow.com/questions/50731229/split-cell-into-multiple-rows-in-pandas-dataframe.\n",
    " https://matplotlib.org/gallery/pie_and_polar_charts/pie_features.html#sphx-glr-gallery-pie-and-polar-charts-pie-features-py."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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