010_EDA_Budget_vs_Revenue.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis: ROI for Budget"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While we've seen that movie revenue has been increasing over time, movies are also more expensive to make now than they used to be. With the advent of CGI and greenscreen technology, blockbuster budgets have also increased exponentially. Let's see how that affects a movie's earning potential."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Libraries to import:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set_palette(\"muted\")\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Concatenate Scraped Movie Data by Decade:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start by creating a dataframe consisting of webscraped data from IMDB for the top 300 movies from each year going back to 1960. We will concatenate each decade's csv file into one. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sixties = pd.read_csv('../zippedData/1960_1970.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "seventies = pd.read_csv('../zippedData/1971_1980.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "eighties = pd.read_csv('../zippedData/1981_1990.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "nineties = pd.read_csv('../zippedData/1991_2000.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "aughts = pd.read_csv('../zippedData/2001_2010.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "teens = pd.read_csv('../zippedData/2011_2020.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>url</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>genre</th>\n",
       "      <th>gross_usa</th>\n",
       "      <th>budget</th>\n",
       "      <th>worldwide_gross</th>\n",
       "      <th>pg_rated</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.imdb.com/title/tt0054215/</td>\n",
       "      <td>Psycho</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Horror', 'Mystery', 'Thriller']</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>$806,947</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.5</td>\n",
       "      <td>580,863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.imdb.com/title/tt0054047/</td>\n",
       "      <td>The Magnificent Seven</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Action', 'Adventure', 'Western']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$2,000,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.7</td>\n",
       "      <td>85,315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.imdb.com/title/tt0054331/</td>\n",
       "      <td>Spartacus</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Adventure', 'Biography', 'Drama', 'History',...</td>\n",
       "      <td>$1,830,650</td>\n",
       "      <td>$12,000,000</td>\n",
       "      <td>$1,836,351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9</td>\n",
       "      <td>120,895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.imdb.com/title/tt0053604/</td>\n",
       "      <td>The Apartment</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Comedy', 'Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$3,000,000</td>\n",
       "      <td>$177,066</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3</td>\n",
       "      <td>157,134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.imdb.com/title/tt0053917/</td>\n",
       "      <td>Home from the Hill</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$1,818,688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2,864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2995</th>\n",
       "      <td>https://www.imdb.com/title/tt7541720/</td>\n",
       "      <td>Music</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2996</th>\n",
       "      <td>https://www.imdb.com/title/tt5867314/</td>\n",
       "      <td>The Empty Man</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2997</th>\n",
       "      <td>https://www.imdb.com/title/tt5714470/</td>\n",
       "      <td>Come Away</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Adventure', 'Drama', 'Fantasy']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.6</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2998</th>\n",
       "      <td>https://www.imdb.com/title/tt6559576/</td>\n",
       "      <td>Selfie Dad</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Comedy', 'Family']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG</td>\n",
       "      <td>3.7</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2999</th>\n",
       "      <td>https://www.imdb.com/title/tt9614452/</td>\n",
       "      <td>The Big Bull</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18300 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        url                  title  year  \\\n",
       "0     https://www.imdb.com/title/tt0054215/                 Psycho  1960   \n",
       "1     https://www.imdb.com/title/tt0054047/  The Magnificent Seven  1960   \n",
       "2     https://www.imdb.com/title/tt0054331/              Spartacus  1960   \n",
       "3     https://www.imdb.com/title/tt0053604/          The Apartment  1960   \n",
       "4     https://www.imdb.com/title/tt0053917/     Home from the Hill  1960   \n",
       "...                                     ...                    ...   ...   \n",
       "2995  https://www.imdb.com/title/tt7541720/                  Music  2020   \n",
       "2996  https://www.imdb.com/title/tt5867314/          The Empty Man  2020   \n",
       "2997  https://www.imdb.com/title/tt5714470/              Come Away  2020   \n",
       "2998  https://www.imdb.com/title/tt6559576/             Selfie Dad  2020   \n",
       "2999  https://www.imdb.com/title/tt9614452/           The Big Bull  2020   \n",
       "\n",
       "                                                  genre    gross_usa  \\\n",
       "0                     ['Horror', 'Mystery', 'Thriller']  $32,000,000   \n",
       "1                    ['Action', 'Adventure', 'Western']          NaN   \n",
       "2     ['Adventure', 'Biography', 'Drama', 'History',...   $1,830,650   \n",
       "3                        ['Comedy', 'Drama', 'Romance']          NaN   \n",
       "4                                  ['Drama', 'Romance']          NaN   \n",
       "...                                                 ...          ...   \n",
       "2995                                          ['Drama']          NaN   \n",
       "2996  ['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...          NaN   \n",
       "2997                  ['Adventure', 'Drama', 'Fantasy']          NaN   \n",
       "2998                               ['Comedy', 'Family']          NaN   \n",
       "2999                                 ['Crime', 'Drama']          NaN   \n",
       "\n",
       "           budget worldwide_gross pg_rated  rating rating_pop  \n",
       "0        $806,947     $32,000,000      NaN     8.5    580,863  \n",
       "1      $2,000,000             NaN      NaN     7.7     85,315  \n",
       "2     $12,000,000      $1,836,351      NaN     7.9    120,895  \n",
       "3      $3,000,000        $177,066      NaN     8.3    157,134  \n",
       "4      $1,818,688             NaN      NaN     7.4      2,864  \n",
       "...           ...             ...      ...     ...        ...  \n",
       "2995          NaN             NaN    PG-13     NaN        NaN  \n",
       "2996          NaN             NaN        R     NaN        NaN  \n",
       "2997          NaN             NaN      NaN     6.6         27  \n",
       "2998          NaN             NaN       PG     3.7         83  \n",
       "2999          NaN             NaN      NaN     NaN        NaN  \n",
       "\n",
       "[18300 rows x 10 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined = sixties.append([seventies, eighties, nineties, aughts, teens])\n",
    "combined"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine DataFrame and Preliminary Cleaning:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "18,000 entries, not bad."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18300, 10)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['url', 'title', 'year', 'genre', 'gross_usa', 'budget',\n",
       "       'worldwide_gross', 'pg_rated', 'rating', 'rating_pop'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we are combining multiple dataframes they will have shared indexes. So let's reset the index and remove the old column this will create."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined = combined.drop('index', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>url</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>genre</th>\n",
       "      <th>gross_usa</th>\n",
       "      <th>budget</th>\n",
       "      <th>worldwide_gross</th>\n",
       "      <th>pg_rated</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.imdb.com/title/tt0054215/</td>\n",
       "      <td>Psycho</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Horror', 'Mystery', 'Thriller']</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>$806,947</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.5</td>\n",
       "      <td>580,863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.imdb.com/title/tt0054047/</td>\n",
       "      <td>The Magnificent Seven</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Action', 'Adventure', 'Western']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$2,000,000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.7</td>\n",
       "      <td>85,315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.imdb.com/title/tt0054331/</td>\n",
       "      <td>Spartacus</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Adventure', 'Biography', 'Drama', 'History',...</td>\n",
       "      <td>$1,830,650</td>\n",
       "      <td>$12,000,000</td>\n",
       "      <td>$1,836,351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9</td>\n",
       "      <td>120,895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.imdb.com/title/tt0053604/</td>\n",
       "      <td>The Apartment</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Comedy', 'Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$3,000,000</td>\n",
       "      <td>$177,066</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3</td>\n",
       "      <td>157,134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.imdb.com/title/tt0053917/</td>\n",
       "      <td>Home from the Hill</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>$1,818,688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2,864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18295</th>\n",
       "      <td>https://www.imdb.com/title/tt7541720/</td>\n",
       "      <td>Music</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18296</th>\n",
       "      <td>https://www.imdb.com/title/tt5867314/</td>\n",
       "      <td>The Empty Man</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18297</th>\n",
       "      <td>https://www.imdb.com/title/tt5714470/</td>\n",
       "      <td>Come Away</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Adventure', 'Drama', 'Fantasy']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.6</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18298</th>\n",
       "      <td>https://www.imdb.com/title/tt6559576/</td>\n",
       "      <td>Selfie Dad</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Comedy', 'Family']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG</td>\n",
       "      <td>3.7</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18299</th>\n",
       "      <td>https://www.imdb.com/title/tt9614452/</td>\n",
       "      <td>The Big Bull</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18300 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         url                  title  year  \\\n",
       "0      https://www.imdb.com/title/tt0054215/                 Psycho  1960   \n",
       "1      https://www.imdb.com/title/tt0054047/  The Magnificent Seven  1960   \n",
       "2      https://www.imdb.com/title/tt0054331/              Spartacus  1960   \n",
       "3      https://www.imdb.com/title/tt0053604/          The Apartment  1960   \n",
       "4      https://www.imdb.com/title/tt0053917/     Home from the Hill  1960   \n",
       "...                                      ...                    ...   ...   \n",
       "18295  https://www.imdb.com/title/tt7541720/                  Music  2020   \n",
       "18296  https://www.imdb.com/title/tt5867314/          The Empty Man  2020   \n",
       "18297  https://www.imdb.com/title/tt5714470/              Come Away  2020   \n",
       "18298  https://www.imdb.com/title/tt6559576/             Selfie Dad  2020   \n",
       "18299  https://www.imdb.com/title/tt9614452/           The Big Bull  2020   \n",
       "\n",
       "                                                   genre    gross_usa  \\\n",
       "0                      ['Horror', 'Mystery', 'Thriller']  $32,000,000   \n",
       "1                     ['Action', 'Adventure', 'Western']          NaN   \n",
       "2      ['Adventure', 'Biography', 'Drama', 'History',...   $1,830,650   \n",
       "3                         ['Comedy', 'Drama', 'Romance']          NaN   \n",
       "4                                   ['Drama', 'Romance']          NaN   \n",
       "...                                                  ...          ...   \n",
       "18295                                          ['Drama']          NaN   \n",
       "18296  ['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...          NaN   \n",
       "18297                  ['Adventure', 'Drama', 'Fantasy']          NaN   \n",
       "18298                               ['Comedy', 'Family']          NaN   \n",
       "18299                                 ['Crime', 'Drama']          NaN   \n",
       "\n",
       "            budget worldwide_gross pg_rated  rating rating_pop  \n",
       "0         $806,947     $32,000,000      NaN     8.5    580,863  \n",
       "1       $2,000,000             NaN      NaN     7.7     85,315  \n",
       "2      $12,000,000      $1,836,351      NaN     7.9    120,895  \n",
       "3       $3,000,000        $177,066      NaN     8.3    157,134  \n",
       "4       $1,818,688             NaN      NaN     7.4      2,864  \n",
       "...            ...             ...      ...     ...        ...  \n",
       "18295          NaN             NaN    PG-13     NaN        NaN  \n",
       "18296          NaN             NaN        R     NaN        NaN  \n",
       "18297          NaN             NaN      NaN     6.6         27  \n",
       "18298          NaN             NaN       PG     3.7         83  \n",
       "18299          NaN             NaN      NaN     NaN        NaN  \n",
       "\n",
       "[18300 rows x 10 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Check for Missing Values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "url                    0\n",
       "title                  0\n",
       "year                   0\n",
       "genre                  5\n",
       "gross_usa           8893\n",
       "budget              9547\n",
       "worldwide_gross     8212\n",
       "pg_rated           11061\n",
       "rating               117\n",
       "rating_pop           117\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove Dollar Signs and Commas from Currency Columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined['worldwide_gross'] = combined['worldwide_gross'].str.strip('$')\n",
    "combined['worldwide_gross'] = combined['worldwide_gross'].str.replace(',', '')\n",
    "\n",
    "combined['budget'] = combined['budget'].str.strip('$')\n",
    "combined['budget'] = combined['budget'].str.replace(',', '')\n",
    "\n",
    "combined['gross_usa'] = combined['gross_usa'].str.strip('$')\n",
    "combined['gross_usa'] = combined['gross_usa'].str.replace(',', '')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove Non-USD Reported Earnings:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We removed entries with non-USD reported budgets. This removed about 600 entries of the 18,000. Note that this does not remove all foreign films, just films produced by companies who did not report their budget in USD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined = combined[~combined['budget'].astype(str).str.startswith('SEK')] # Format is redefine the column with all\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('NOK')] # entries EXCEPT where the entry starts\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('KRW')] # with the specified currency string.\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('SGD')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('THB')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('JPY')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('HUF')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('INR')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('GBP')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('HKD')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('FRF')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('EUR')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('FIM')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('DEM')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('DKK')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('CAD')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('ESP')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('AUD')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('BEF')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('CNY')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('ATS')]\n",
    "combined = combined[~combined['budget'].astype(str).str.startswith('BRL')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>url</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>genre</th>\n",
       "      <th>gross_usa</th>\n",
       "      <th>budget</th>\n",
       "      <th>worldwide_gross</th>\n",
       "      <th>pg_rated</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.imdb.com/title/tt0054215/</td>\n",
       "      <td>Psycho</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Horror', 'Mystery', 'Thriller']</td>\n",
       "      <td>32000000</td>\n",
       "      <td>806947</td>\n",
       "      <td>32000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.5</td>\n",
       "      <td>580,863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.imdb.com/title/tt0054047/</td>\n",
       "      <td>The Magnificent Seven</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Action', 'Adventure', 'Western']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.7</td>\n",
       "      <td>85,315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.imdb.com/title/tt0054331/</td>\n",
       "      <td>Spartacus</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Adventure', 'Biography', 'Drama', 'History',...</td>\n",
       "      <td>1830650</td>\n",
       "      <td>12000000</td>\n",
       "      <td>1836351</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9</td>\n",
       "      <td>120,895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.imdb.com/title/tt0053604/</td>\n",
       "      <td>The Apartment</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Comedy', 'Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3000000</td>\n",
       "      <td>177066</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3</td>\n",
       "      <td>157,134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.imdb.com/title/tt0053917/</td>\n",
       "      <td>Home from the Hill</td>\n",
       "      <td>1960</td>\n",
       "      <td>['Drama', 'Romance']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1818688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2,864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18295</th>\n",
       "      <td>https://www.imdb.com/title/tt7541720/</td>\n",
       "      <td>Music</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18296</th>\n",
       "      <td>https://www.imdb.com/title/tt5867314/</td>\n",
       "      <td>The Empty Man</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18297</th>\n",
       "      <td>https://www.imdb.com/title/tt5714470/</td>\n",
       "      <td>Come Away</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Adventure', 'Drama', 'Fantasy']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.6</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18298</th>\n",
       "      <td>https://www.imdb.com/title/tt6559576/</td>\n",
       "      <td>Selfie Dad</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Comedy', 'Family']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PG</td>\n",
       "      <td>3.7</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18299</th>\n",
       "      <td>https://www.imdb.com/title/tt9614452/</td>\n",
       "      <td>The Big Bull</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Crime', 'Drama']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17445 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         url                  title  year  \\\n",
       "0      https://www.imdb.com/title/tt0054215/                 Psycho  1960   \n",
       "1      https://www.imdb.com/title/tt0054047/  The Magnificent Seven  1960   \n",
       "2      https://www.imdb.com/title/tt0054331/              Spartacus  1960   \n",
       "3      https://www.imdb.com/title/tt0053604/          The Apartment  1960   \n",
       "4      https://www.imdb.com/title/tt0053917/     Home from the Hill  1960   \n",
       "...                                      ...                    ...   ...   \n",
       "18295  https://www.imdb.com/title/tt7541720/                  Music  2020   \n",
       "18296  https://www.imdb.com/title/tt5867314/          The Empty Man  2020   \n",
       "18297  https://www.imdb.com/title/tt5714470/              Come Away  2020   \n",
       "18298  https://www.imdb.com/title/tt6559576/             Selfie Dad  2020   \n",
       "18299  https://www.imdb.com/title/tt9614452/           The Big Bull  2020   \n",
       "\n",
       "                                                   genre gross_usa    budget  \\\n",
       "0                      ['Horror', 'Mystery', 'Thriller']  32000000    806947   \n",
       "1                     ['Action', 'Adventure', 'Western']       NaN   2000000   \n",
       "2      ['Adventure', 'Biography', 'Drama', 'History',...   1830650  12000000   \n",
       "3                         ['Comedy', 'Drama', 'Romance']       NaN   3000000   \n",
       "4                                   ['Drama', 'Romance']       NaN   1818688   \n",
       "...                                                  ...       ...       ...   \n",
       "18295                                          ['Drama']       NaN       NaN   \n",
       "18296  ['Crime', 'Drama', 'Horror', 'Mystery', 'Thril...       NaN       NaN   \n",
       "18297                  ['Adventure', 'Drama', 'Fantasy']       NaN       NaN   \n",
       "18298                               ['Comedy', 'Family']       NaN       NaN   \n",
       "18299                                 ['Crime', 'Drama']       NaN       NaN   \n",
       "\n",
       "      worldwide_gross pg_rated  rating rating_pop  \n",
       "0            32000000      NaN     8.5    580,863  \n",
       "1                 NaN      NaN     7.7     85,315  \n",
       "2             1836351      NaN     7.9    120,895  \n",
       "3              177066      NaN     8.3    157,134  \n",
       "4                 NaN      NaN     7.4      2,864  \n",
       "...               ...      ...     ...        ...  \n",
       "18295             NaN    PG-13     NaN        NaN  \n",
       "18296             NaN        R     NaN        NaN  \n",
       "18297             NaN      NaN     6.6         27  \n",
       "18298             NaN       PG     3.7         83  \n",
       "18299             NaN      NaN     NaN        NaN  \n",
       "\n",
       "[17445 rows x 10 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remove Rows with Missing Data: \n",
    "\n",
    "We need intact budget and worldwide gross earnings for each movie so we need to remove rows with missing values in these columns. This will decrease the size of the dataframe, but, in this case, it is necessary. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>url</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>genre</th>\n",
       "      <th>gross_usa</th>\n",
       "      <th>budget</th>\n",
       "      <th>worldwide_gross</th>\n",
       "      <th>pg_rated</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1202</th>\n",
       "      <td>https://www.imdb.com/title/tt0057012/</td>\n",
       "      <td>Dr. Strangelove or: How I Learned to Stop Worr...</td>\n",
       "      <td>1964</td>\n",
       "      <td>['Comedy']</td>\n",
       "      <td>9440272</td>\n",
       "      <td>1800000</td>\n",
       "      <td>9443876</td>\n",
       "      <td>PG</td>\n",
       "      <td>8.4</td>\n",
       "      <td>437,986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1205</th>\n",
       "      <td>https://www.imdb.com/title/tt0058461/</td>\n",
       "      <td>A Fistful of Dollars</td>\n",
       "      <td>1964</td>\n",
       "      <td>['Action', 'Drama', 'Western']</td>\n",
       "      <td>14500000</td>\n",
       "      <td>200000</td>\n",
       "      <td>14516248</td>\n",
       "      <td>R</td>\n",
       "      <td>8.0</td>\n",
       "      <td>190,339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1238</th>\n",
       "      <td>https://www.imdb.com/title/tt0057877/</td>\n",
       "      <td>Becket</td>\n",
       "      <td>1964</td>\n",
       "      <td>['Biography', 'Drama', 'History']</td>\n",
       "      <td>149327</td>\n",
       "      <td>3000000</td>\n",
       "      <td>149327</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>7.8</td>\n",
       "      <td>13,272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1502</th>\n",
       "      <td>https://www.imdb.com/title/tt0059113/</td>\n",
       "      <td>Doctor Zhivago</td>\n",
       "      <td>1965</td>\n",
       "      <td>['Drama', 'Romance', 'War']</td>\n",
       "      <td>111721910</td>\n",
       "      <td>11000000</td>\n",
       "      <td>111918564</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>8.0</td>\n",
       "      <td>67,790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1558</th>\n",
       "      <td>https://www.imdb.com/title/tt0059418/</td>\n",
       "      <td>Major Dundee</td>\n",
       "      <td>1965</td>\n",
       "      <td>['Adventure', 'War', 'Western']</td>\n",
       "      <td>20807</td>\n",
       "      <td>3800000</td>\n",
       "      <td>20807</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>6.7</td>\n",
       "      <td>6,864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18099</th>\n",
       "      <td>https://www.imdb.com/title/tt9173418/</td>\n",
       "      <td>Brahms: The Boy II</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama', 'Horror', 'Mystery', 'Thriller']</td>\n",
       "      <td>12611536</td>\n",
       "      <td>10000000</td>\n",
       "      <td>20311536</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>4.6</td>\n",
       "      <td>7,432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18127</th>\n",
       "      <td>https://www.imdb.com/title/tt7545266/</td>\n",
       "      <td>Like a Boss</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Comedy']</td>\n",
       "      <td>22169514</td>\n",
       "      <td>29000000</td>\n",
       "      <td>29753143</td>\n",
       "      <td>R</td>\n",
       "      <td>4.4</td>\n",
       "      <td>6,756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18130</th>\n",
       "      <td>https://www.imdb.com/title/tt7510346/</td>\n",
       "      <td>The Turning</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama', 'Horror', 'Mystery']</td>\n",
       "      <td>15472775</td>\n",
       "      <td>14000000</td>\n",
       "      <td>18592707</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>3.8</td>\n",
       "      <td>6,813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18136</th>\n",
       "      <td>https://www.imdb.com/title/tt9208444/</td>\n",
       "      <td>Impractical Jokers: The Movie</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Comedy']</td>\n",
       "      <td>10691091</td>\n",
       "      <td>3000000</td>\n",
       "      <td>10691091</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3,694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18217</th>\n",
       "      <td>https://www.imdb.com/title/tt7798646/</td>\n",
       "      <td>The Photograph</td>\n",
       "      <td>2020</td>\n",
       "      <td>['Drama', 'Romance']</td>\n",
       "      <td>20578185</td>\n",
       "      <td>16000000</td>\n",
       "      <td>20653204</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2,353</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4616 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         url  \\\n",
       "1202   https://www.imdb.com/title/tt0057012/   \n",
       "1205   https://www.imdb.com/title/tt0058461/   \n",
       "1238   https://www.imdb.com/title/tt0057877/   \n",
       "1502   https://www.imdb.com/title/tt0059113/   \n",
       "1558   https://www.imdb.com/title/tt0059418/   \n",
       "...                                      ...   \n",
       "18099  https://www.imdb.com/title/tt9173418/   \n",
       "18127  https://www.imdb.com/title/tt7545266/   \n",
       "18130  https://www.imdb.com/title/tt7510346/   \n",
       "18136  https://www.imdb.com/title/tt9208444/   \n",
       "18217  https://www.imdb.com/title/tt7798646/   \n",
       "\n",
       "                                                   title  year  \\\n",
       "1202   Dr. Strangelove or: How I Learned to Stop Worr...  1964   \n",
       "1205                                A Fistful of Dollars  1964   \n",
       "1238                                              Becket  1964   \n",
       "1502                                      Doctor Zhivago  1965   \n",
       "1558                                        Major Dundee  1965   \n",
       "...                                                  ...   ...   \n",
       "18099                                 Brahms: The Boy II  2020   \n",
       "18127                                        Like a Boss  2020   \n",
       "18130                                        The Turning  2020   \n",
       "18136                      Impractical Jokers: The Movie  2020   \n",
       "18217                                     The Photograph  2020   \n",
       "\n",
       "                                            genre  gross_usa    budget  \\\n",
       "1202                                   ['Comedy']    9440272   1800000   \n",
       "1205               ['Action', 'Drama', 'Western']   14500000    200000   \n",
       "1238            ['Biography', 'Drama', 'History']     149327   3000000   \n",
       "1502                  ['Drama', 'Romance', 'War']  111721910  11000000   \n",
       "1558              ['Adventure', 'War', 'Western']      20807   3800000   \n",
       "...                                           ...        ...       ...   \n",
       "18099  ['Drama', 'Horror', 'Mystery', 'Thriller']   12611536  10000000   \n",
       "18127                                  ['Comedy']   22169514  29000000   \n",
       "18130              ['Drama', 'Horror', 'Mystery']   15472775  14000000   \n",
       "18136                                  ['Comedy']   10691091   3000000   \n",
       "18217                        ['Drama', 'Romance']   20578185  16000000   \n",
       "\n",
       "      worldwide_gross pg_rated  rating rating_pop  \n",
       "1202          9443876       PG     8.4    437,986  \n",
       "1205         14516248        R     8.0    190,339  \n",
       "1238           149327    PG-13     7.8     13,272  \n",
       "1502        111918564    PG-13     8.0     67,790  \n",
       "1558            20807    PG-13     6.7      6,864  \n",
       "...               ...      ...     ...        ...  \n",
       "18099        20311536    PG-13     4.6      7,432  \n",
       "18127        29753143        R     4.4      6,756  \n",
       "18130        18592707    PG-13     3.8      6,813  \n",
       "18136        10691091    PG-13     6.0      3,694  \n",
       "18217        20653204    PG-13     5.9      2,353  \n",
       "\n",
       "[4616 rows x 10 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pared_down = combined.dropna() #Now we can drop missing values.\n",
    "pared_down"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Recast Budget and Worldwide Gross as Int64: \n",
    "\n",
    "This throws a warning because we are altering a copy of a dataframe. In this case, it is what we want so don't mind the warning, the change will go through."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/arencarpenter/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "pared_down['budget'] = pared_down.budget.astype('int64') # Recast as numerical data type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/arencarpenter/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "pared_down['worldwide_gross'] = pared_down.worldwide_gross.astype('int64')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confirm that the data type of both columns is now int64."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pared_down.budget.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pared_down.worldwide_gross.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's sort the values to get a sense of our range of budgets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11436         6000\n",
       "9672          7000\n",
       "13262         7000\n",
       "10425        15000\n",
       "14150        15000\n",
       "           ...    \n",
       "17111    300000000\n",
       "14113    300000000\n",
       "17122    317000000\n",
       "17401    321000000\n",
       "17706    356000000\n",
       "Name: budget, Length: 4616, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pared_down.budget.sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Visualization:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can start to visualize. Let's plot each movie's budget and worldwide revenue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 10))\n",
    "sns.regplot(x = 'budget', y = 'worldwide_gross', data = pared_down, scatter_kws={'alpha':0.5})\n",
    "plt.title('Budget vs Worldwide Revenue')          # Set title.\n",
    "plt.xlabel(\"Budget \\n in hundred millions\")       # Set x-axis label.\n",
    "plt.ylabel('Worldwide Revenue \\n in billions')    # Set y-axis label.\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, there is a positive relationship between budget and revenue. Using our regression line, we would expect a film with budget of 150,000,000 -- or 150 million -- to return 500,000,000 -- or 0.5 billion -- in revenue. Thus a profit of 350,000,000. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the same scatter plot as a regplot for the distribution of each variable. As we can see, most movies have a budget of less than 50,000,000 and earn less than 100,000,000. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7fb00f54add0>"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x = 'budget', y = 'worldwide_gross', data = pared_down, alpha = 0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Insights:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The average movie has a positive return on investment for its budget. Devoid of other factors, producers should put in as much money as they can to ensure the biggest payoff. However, this does not account for other important factors, such as release time, user and critic ratings, and competition from other films."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
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