ETL_clean_wiki_movies.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import re\n",
    "\n",
    "from sqlalchemy import create_engine\n",
    "import psycopg2\n",
    "\n",
    "from config import db_password\n",
    "\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 1. Add the clean movie function that takes in the argument, \"movie\".\n",
    "def clean_movie(movie):\n",
    "    movie = dict(movie) #create a non-destructive copy\n",
    "    alt_titles = {}\n",
    "    for key in ['Also known as','Arabic','Cantonese','Chinese','French',\n",
    "                'Hangul','Hebrew','Hepburn','Japanese','Literally',\n",
    "                'Mandarin','McCune–Reischauer','Original title','Polish',\n",
    "                'Revised Romanization','Romanized','Russian',\n",
    "                'Simplified','Traditional','Yiddish']:\n",
    "        if key in movie:\n",
    "            alt_titles[key] = movie[key]\n",
    "            movie.pop(key)\n",
    "    if len(alt_titles) > 0:\n",
    "        movie['alt_titles'] = alt_titles\n",
    "\n",
    "    return movie\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "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>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1425941529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1425942435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>858</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1221</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1246</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26024284</th>\n",
       "      <td>270896</td>\n",
       "      <td>58559</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1257031564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26024285</th>\n",
       "      <td>270896</td>\n",
       "      <td>60069</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1257032032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26024286</th>\n",
       "      <td>270896</td>\n",
       "      <td>63082</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1257031764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26024287</th>\n",
       "      <td>270896</td>\n",
       "      <td>64957</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1257033990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26024288</th>\n",
       "      <td>270896</td>\n",
       "      <td>71878</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1257031858</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26024289 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          userId  movieId  rating   timestamp\n",
       "0              1      110     1.0  1425941529\n",
       "1              1      147     4.5  1425942435\n",
       "2              1      858     5.0  1425941523\n",
       "3              1     1221     5.0  1425941546\n",
       "4              1     1246     5.0  1425941556\n",
       "...          ...      ...     ...         ...\n",
       "26024284  270896    58559     5.0  1257031564\n",
       "26024285  270896    60069     5.0  1257032032\n",
       "26024286  270896    63082     4.5  1257031764\n",
       "26024287  270896    64957     4.5  1257033990\n",
       "26024288  270896    71878     2.0  1257031858\n",
       "\n",
       "[26024289 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kaggle_metadata = pd.read_csv('movies_metadata.csv', low_memory=False)\n",
    "ratings = pd.read_csv('ratings.csv') \n",
    "ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    " with open('wikipedia-movies.json', mode='r') as file:\n",
    "        wiki_movies_raw = json.load(file)\n",
    "    # 3. Write a list comprehension to filter out TV shows.\n",
    "        wiki_movies = [movie for movie in wiki_movies_raw\n",
    "        if ('Director' in movie or 'Directed by' in movie)\n",
    "        and 'imdb_link' in movie\n",
    "        and 'No. of episodes' not in movie] \n",
    "        wiki_movies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2 Add the function that takes in three arguments;\n",
    "# Wikipedia data, Kaggle metadata, and MovieLens rating data (from Kaggle)\n",
    "\n",
    "def extract_transform_load():\n",
    "    # Read in the kaggle metadata and MovieLens ratings CSV files as Pandas DataFrames.\n",
    "    kaggle_metadata = pd.read_csv('movies_metadata.csv', low_memory=False)\n",
    "    ratings = pd.read_csv('ratings.csv') \n",
    "        # Open and read the Wikipedia data JSON file.\n",
    "    \n",
    "    with open('wikipedia-movies.json', mode='r') as file:\n",
    "        wiki_movies_raw = json.load(file)\n",
    "    # 3. Write a list comprehension to filter out TV shows.\n",
    "    wiki_movies = [movie for movie in wiki_movies_raw\n",
    "               if ('Director' in movie or 'Directed by' in movie)\n",
    "                   and 'imdb_link' in movie\n",
    "                   and 'No. of episodes' not in movie]\n",
    "        \n",
    "     # 4. Write a list comprehension to iterate through the cleaned wiki movies list\n",
    "    # and call the clean_movie function on each movie.\n",
    "    clean_movies = [clean_movie(movie) for movie in wiki_movies]\n",
    "    # 5. Read in the cleaned movies list from Step 4 as a DataFrame.\n",
    "    wiki_movies_df = pd.DataFrame(clean_movies)\n",
    "       # 6. Write a try-except block to catch errors while extracting the IMDb ID using a regular expression string and\n",
    "    #  dropping any imdb_id duplicates. If there is an error, capture and print the exception.\n",
    "    try:\n",
    "        wiki_movies_df.drop_duplicates(subset='imdb_id', inplace=True)\n",
    "        \n",
    "    except:\n",
    "        #  7. Write a list comprehension to keep the columns that don't have null values from the wiki_movies_df DataFrame.\n",
    "        wiki_columns_to_keep = [column for column in wiki_movies_df.columns if wiki_movies_df[column].isnull().sum() < len(wiki_movies_df) * 0.9]\n",
    "        wiki_movies_df = wiki_movies_df[wiki_columns_to_keep]\n",
    "        # 8. Create a variable that will hold the non-null values from the “Box office” column.\n",
    "    \n",
    "        box_office = wiki_movies_df['Box office'].dropna()\n",
    "        # 9. Convert the box office data created in Step 8 to string values using the lambda and join functions.\n",
    "        box_office = box_office.apply(lambda x: ' '.join(x) if type(x) == list else x)\n",
    "           # 10. Write a regular expression to match the six elements of \"form_one\" of the box office data.\n",
    "        form_one = r'\\$\\d+\\.?\\d*\\s*[mb]illion'\n",
    "         # 11. Write a regular expression to match the three elements of \"form_two\" of the box office data.\n",
    "    \n",
    "        form_two = r'\\$\\d{1,3}(?:,\\d{3})+'\n",
    "\n",
    "        \n",
    "        # 12. Add the parse_dollars function.# if s is not a string, return NaN\n",
    "        def parse_dollars(s):\n",
    "            if type(s) != str:\n",
    "                return np.nan\n",
    "\n",
    "            # if input is of the form $###.# million # remove dollar sign and \" million\"\n",
    "            if re.match(r'\\$\\s*\\d+\\.?\\d*\\s*milli?on', s, flags=re.IGNORECASE):\n",
    "                s = re.sub('\\$|\\s|[a-zA-Z]','', s)\n",
    "\n",
    "                # convert to float and multiply by a million  # return value\n",
    "                value = float(s) * 10**6\n",
    "                return value\n",
    "\n",
    "            # if input is of the form $###.# billion # remove dollar sign and \" billion\"\n",
    "            elif re.match(r'\\$\\s*\\d+\\.?\\d*\\s*billi?on', s, flags=re.IGNORECASE):\n",
    "                s = re.sub('\\$|\\s|[a-zA-Z]','', s)\n",
    "\n",
    "                # convert to float and multiply by a billion\n",
    "                value = float(s) * 10**9\n",
    "\n",
    "                # return value\n",
    "                return value\n",
    "\n",
    "            # if input is of the form $###,###,### # remove dollar sign and commas\n",
    "            elif re.match(r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)', s, flags=re.IGNORECASE):\n",
    "                s = re.sub('\\$|,','', s)\n",
    "\n",
    "                # convert to float\n",
    "                value = float(s)\n",
    "\n",
    "                # return value\n",
    "                return value\n",
    "\n",
    "            # otherwise, return NaN\n",
    "            else:\n",
    "                return np.nan\n",
    "      # 13. Clean the box office column in the wiki_movies_df DataFrame.\n",
    "    wiki_movies_df['box_office'] = box_office.str.extract(f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)\n",
    "    # 14. Clean the budget column in the wiki_movies_df DataFrame.\n",
    "    budget = wiki_movies_df['Budget'].dropna()\n",
    "      # 15. Clean the release date column in the wiki_movies_df DataFrame.\n",
    "    release_date = wiki_movies_df['Release date'].dropna().apply(lambda x: ' '.join(x) if type(x) == list else x)  \n",
    "    # 16. Clean the running time column in the wiki_movies_df DataFrame.\n",
    "    running_time = wiki_movies_df['Running time'].dropna().apply(lambda x: ' '.join(x) if type(x) == list else x)\n",
    "    # Return three variables. The first is the wiki_movies_df DataFrame\n",
    "    \n",
    "    return wiki_movies_df, kaggle_metadata, ratings \n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 17. Create the path to your file directory and variables for the three files.\n",
    "file_dir = 'C://Users/elizavetalyadova/Desktop/Movies-ETL'\n",
    "# The Wikipedia data\n",
    "wiki_file = f'{file_dir}/wikipedia.movies.json'\n",
    "# The Kaggle metadata\n",
    "kaggle_file = f'{file_dir}/movies_metadata.csv'\n",
    "# The MovieLens rating data.\n",
    "ratings_file = f'{file_dir}/ratings.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 18. Set the three variables equal to the function created in D1.\n",
    "wiki_file, kaggle_file, ratings_file = extract_transform_load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 19. Set the wiki_movies_df equal to the wiki_file variable. \n",
    "wiki_movies_df = wiki_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>year</th>\n",
       "      <th>imdb_link</th>\n",
       "      <th>title</th>\n",
       "      <th>Directed by</th>\n",
       "      <th>Produced by</th>\n",
       "      <th>Screenplay by</th>\n",
       "      <th>Story by</th>\n",
       "      <th>Based on</th>\n",
       "      <th>Starring</th>\n",
       "      <th>...</th>\n",
       "      <th>Distributed by</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Running time</th>\n",
       "      <th>Country</th>\n",
       "      <th>Language</th>\n",
       "      <th>Budget</th>\n",
       "      <th>Box office</th>\n",
       "      <th>Written by</th>\n",
       "      <th>Productioncompanies</th>\n",
       "      <th>box_office</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Adventures_o...</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0098987/</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>Renny Harlin</td>\n",
       "      <td>[Steve Perry, Joel Silver]</td>\n",
       "      <td>[David Arnott, James Cappe, Daniel Waters]</td>\n",
       "      <td>[David Arnott, James Cappe]</td>\n",
       "      <td>[Characters, by Rex Weiner]</td>\n",
       "      <td>[Andrew Dice Clay, Wayne Newton, Priscilla Pre...</td>\n",
       "      <td>...</td>\n",
       "      <td>20th Century Fox</td>\n",
       "      <td>[July 11, 1990, (, 1990-07-11, )]</td>\n",
       "      <td>102 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>$20 million</td>\n",
       "      <td>$21.4 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21400000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://en.wikipedia.org/wiki/After_Dark,_My_S...</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0098994/</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>James Foley</td>\n",
       "      <td>[Ric Kidney, Robert Redlin]</td>\n",
       "      <td>[James Foley, Robert Redlin]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[the novel, After Dark, My Sweet, by, Jim Thom...</td>\n",
       "      <td>[Jason Patric, Rachel Ward, Bruce Dern, George...</td>\n",
       "      <td>...</td>\n",
       "      <td>Avenue Pictures</td>\n",
       "      <td>[May 17, 1990, (, 1990-05-17, ), (Cannes Film ...</td>\n",
       "      <td>114 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>$6 million</td>\n",
       "      <td>$2.7 million</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2700000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Air_America_(film)</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099005/</td>\n",
       "      <td>Air America</td>\n",
       "      <td>Roger Spottiswoode</td>\n",
       "      <td>Daniel Melnick</td>\n",
       "      <td>[John Eskow, Richard Rush]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Air America, by, Christopher Robbins]</td>\n",
       "      <td>[Mel Gibson, Robert Downey Jr., Nancy Travis, ...</td>\n",
       "      <td>...</td>\n",
       "      <td>TriStar Pictures</td>\n",
       "      <td>[August 10, 1990, (, 1990-08-10, )]</td>\n",
       "      <td>113 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>[English, Lao]</td>\n",
       "      <td>$35 million</td>\n",
       "      <td>$57,718,089</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57718089.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Alice_(1990_film)</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099012/</td>\n",
       "      <td>Alice</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>Robert Greenhut</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Alec Baldwin, Blythe Danner, Judy Davis, Mia ...</td>\n",
       "      <td>...</td>\n",
       "      <td>Orion Pictures</td>\n",
       "      <td>[December 25, 1990, (, 1990-12-25, )]</td>\n",
       "      <td>106 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>$12 million</td>\n",
       "      <td>$7,331,647</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7331647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Almost_an_Angel</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099018/</td>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Paul Hogan, Elias Koteas, Linda Kozlowski]</td>\n",
       "      <td>...</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>December 19, 1990</td>\n",
       "      <td>95 minutes</td>\n",
       "      <td>US</td>\n",
       "      <td>English</td>\n",
       "      <td>$25 million</td>\n",
       "      <td>$6,939,946 (USA)</td>\n",
       "      <td>Paul Hogan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6939946.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 url  year  \\\n",
       "0  https://en.wikipedia.org/wiki/The_Adventures_o...  1990   \n",
       "1  https://en.wikipedia.org/wiki/After_Dark,_My_S...  1990   \n",
       "2   https://en.wikipedia.org/wiki/Air_America_(film)  1990   \n",
       "3    https://en.wikipedia.org/wiki/Alice_(1990_film)  1990   \n",
       "4      https://en.wikipedia.org/wiki/Almost_an_Angel  1990   \n",
       "\n",
       "                               imdb_link                            title  \\\n",
       "0  https://www.imdb.com/title/tt0098987/  The Adventures of Ford Fairlane   \n",
       "1  https://www.imdb.com/title/tt0098994/             After Dark, My Sweet   \n",
       "2  https://www.imdb.com/title/tt0099005/                      Air America   \n",
       "3  https://www.imdb.com/title/tt0099012/                            Alice   \n",
       "4  https://www.imdb.com/title/tt0099018/                  Almost an Angel   \n",
       "\n",
       "          Directed by                  Produced by  \\\n",
       "0        Renny Harlin   [Steve Perry, Joel Silver]   \n",
       "1         James Foley  [Ric Kidney, Robert Redlin]   \n",
       "2  Roger Spottiswoode               Daniel Melnick   \n",
       "3         Woody Allen              Robert Greenhut   \n",
       "4        John Cornell                 John Cornell   \n",
       "\n",
       "                                Screenplay by                     Story by  \\\n",
       "0  [David Arnott, James Cappe, Daniel Waters]  [David Arnott, James Cappe]   \n",
       "1                [James Foley, Robert Redlin]                          NaN   \n",
       "2                  [John Eskow, Richard Rush]                          NaN   \n",
       "3                                         NaN                          NaN   \n",
       "4                                         NaN                          NaN   \n",
       "\n",
       "                                            Based on  \\\n",
       "0                        [Characters, by Rex Weiner]   \n",
       "1  [the novel, After Dark, My Sweet, by, Jim Thom...   \n",
       "2             [Air America, by, Christopher Robbins]   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "\n",
       "                                            Starring  ...      Distributed by  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...  ...    20th Century Fox   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...  ...     Avenue Pictures   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...  ...    TriStar Pictures   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...  ...      Orion Pictures   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]  ...  Paramount Pictures   \n",
       "\n",
       "                                        Release date Running time  \\\n",
       "0                  [July 11, 1990, (, 1990-07-11, )]  102 minutes   \n",
       "1  [May 17, 1990, (, 1990-05-17, ), (Cannes Film ...  114 minutes   \n",
       "2                [August 10, 1990, (, 1990-08-10, )]  113 minutes   \n",
       "3              [December 25, 1990, (, 1990-12-25, )]  106 minutes   \n",
       "4                                  December 19, 1990   95 minutes   \n",
       "\n",
       "         Country        Language       Budget        Box office   Written by  \\\n",
       "0  United States         English  $20 million     $21.4 million          NaN   \n",
       "1  United States         English   $6 million      $2.7 million          NaN   \n",
       "2  United States  [English, Lao]  $35 million       $57,718,089          NaN   \n",
       "3  United States         English  $12 million        $7,331,647  Woody Allen   \n",
       "4             US         English  $25 million  $6,939,946 (USA)   Paul Hogan   \n",
       "\n",
       "  Productioncompanies   box_office  \n",
       "0                  NaN  21400000.0  \n",
       "1                  NaN   2700000.0  \n",
       "2                  NaN  57718089.0  \n",
       "3                  NaN   7331647.0  \n",
       "4                  NaN   6939946.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 20. Check that the wiki_movies_df DataFrame looks like this. \n",
    "wiki_movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['url',\n",
       " 'year',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'Directed by',\n",
       " 'Produced by',\n",
       " 'Screenplay by',\n",
       " 'Story by',\n",
       " 'Based on',\n",
       " 'Starring',\n",
       " 'Music by',\n",
       " 'Cinematography',\n",
       " 'Edited by',\n",
       " 'Productioncompany ',\n",
       " 'Distributed by',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Country',\n",
       " 'Language',\n",
       " 'Budget',\n",
       " 'Box office',\n",
       " 'Written by',\n",
       " 'Productioncompanies ',\n",
       " 'box_office']"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 21. Check that wiki_movies_df DataFrame columns are correct. \n",
    "wiki_movies_df.columns.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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