ETL_clean_wiki_movies.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "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": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. Add the clean movie function that takes in the argument, \"movie\".\n",
    "def clean_movie(movie):\n",
    "    movie = dict(movie)  # Creates a non-destructive copy locally\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",
    "\n",
    "    if len(alt_titles) > 0:\n",
    "        movie['alt_titles'] = alt_titles\n",
    "\n",
    "    def change_column_name(old_name, new_name):\n",
    "        if old_name in movie:\n",
    "            movie[new_name] = movie.pop(old_name)\n",
    "    \n",
    "    change_column_name('Adaptation by', 'Writer(s)')\n",
    "    change_column_name('Country of origin', 'Country')\n",
    "    change_column_name('Directed by', 'Director')\n",
    "    change_column_name('Distributed by', 'Distributor')\n",
    "    change_column_name('Edited by', 'Editor(s)')\n",
    "    change_column_name('Length', 'Running time')\n",
    "    change_column_name('Original release', 'Release date')\n",
    "    change_column_name('Music by', 'Composer(s)')\n",
    "    change_column_name('Produced by', 'Producer(s)')\n",
    "    change_column_name('Producer', 'Producer(s)')\n",
    "    change_column_name('Productioncompanies ', 'Production company(s)')\n",
    "    change_column_name('Productioncompany ', 'Production company(s)')\n",
    "    change_column_name('Released', 'Release Date')\n",
    "    change_column_name('Release Date', 'Release date')\n",
    "    change_column_name('Screen story by', 'Writer(s)')\n",
    "    change_column_name('Screenplay by', 'Writer(s)')\n",
    "    change_column_name('Story by', 'Writer(s)')\n",
    "    change_column_name('Theme music composer', 'Composer(s)')\n",
    "    change_column_name('Written by', 'Writer(s)')\n",
    "\n",
    "    return movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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(kaggle_file, low_memory=False)\n",
    "\n",
    "    ratings = pd.read_csv(ratings_file, low_memory=False)  \n",
    "\n",
    "    # Open and read the Wikipedia data JSON file.\n",
    "    with open(wiki_file, mode='r') as file:\n",
    "        wiki_movies_raw = json.load(file)\n",
    "    \n",
    "    # 3. Write a list comprehension to filter out TV shows.\n",
    "    wiki_movies = [movie for movie in wiki_movies_raw if \\\n",
    "        ('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",
    "\n",
    "    # 5. Read in the cleaned movies list from Step 4 as a DataFrame.\n",
    "    wiki_movies_df = pd.DataFrame(clean_movies)\n",
    "\n",
    "\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['imdb_id'] = wiki_movies_df['imdb_link'].str.extract(r'(tt\\d{7})')\n",
    "        wiki_movies_df.drop_duplicates(subset='imdb_id', inplace=True)\n",
    "    except Exception as e:\n",
    "        print(f'A \"{e}\" error occurred in the extraction of imdb id numbers') \n",
    "\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] \\\n",
    "        .isnull().sum() < len(wiki_movies_df) * 0.9]\n",
    "\n",
    "    wiki_movies_df = wiki_movies_df[wiki_columns_to_keep]\n",
    "\n",
    "    # 8. Create a variable that will hold the non-null values from the “Box office” column.\n",
    "    box_office = wiki_movies_df['Box office'].dropna()\n",
    "\n",
    "    \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",
    "\n",
    "    # 10. Write a regular expression to match the six elements of \"form_one\" of the box office data.\n",
    "    # Form one is like $4 billion\n",
    "    form_one = r'\\$\\s*\\d+\\.?\\d*\\s*[mb]illi?on'\n",
    "\n",
    "    # 11. Write a regular expression to match the three elements of \"form_two\" of the box office data.\n",
    "    # Form two looks like $400,000,000.00\n",
    "    form_two = r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)'\n",
    "\n",
    "    # 12. Add the parse_dollars function.\n",
    "    def parse_dollars(s):\n",
    "        form_one_m = r'\\$\\s*\\d+\\.?\\d*\\s*milli?on'\n",
    "        form_one_b = r'\\$\\s*\\d+\\.?\\d*\\s*billi?on'\n",
    "        form_two = r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)'\n",
    "        \n",
    "        if type(s) !=str:\n",
    "            return np.nan\n",
    "        \n",
    "        elif re.match(form_one_m, s, flags=re.IGNORECASE):\n",
    "            s = re.sub('\\$|\\s|[a-zA-Z]', '', s)\n",
    "            value = float(s) * 10**6 \n",
    "            return value\n",
    "        \n",
    "        elif re.match(form_one_b, s, flags=re.IGNORECASE):\n",
    "            s = re.sub('\\$|\\s|[a-zA-Z]', '', s)\n",
    "            value = float(s) * 10**9 \n",
    "            return value\n",
    "\n",
    "        elif re.match(form_two, s, flags=re.IGNORECASE):\n",
    "            s = re.sub('\\$|,', '', s)\n",
    "            value = float(s)\n",
    "            return value\n",
    "\n",
    "        else:\n",
    "            return np.nan\n",
    "    \n",
    "        \n",
    "    # 13. Clean the box office column in the wiki_movies_df DataFrame.\n",
    "    wiki_movies_df['box_office'] = box_office.str.extract(\n",
    "        f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)\n",
    "\n",
    "    wiki_movies_df.drop('Box office', axis=1, inplace=True)\n",
    "    \n",
    "    # 14. Clean the budget column in the wiki_movies_df DataFrame.\n",
    "    budget = wiki_movies_df['Budget'].dropna()\n",
    "    budget = budget.map(lambda x: ' '.join(x) if type == list else x)\n",
    "    budget = budget.str.replace(r'\\$.*[-—–](?![a-zA-Z])', '$', regex=True)\n",
    "    budget = budget.str.replace(r'\\[\\d+\\]\\s*', '', regex=True)\n",
    "\n",
    "    wiki_movies_df['budget'] = budget.str.extract(\n",
    "        f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)\n",
    "\n",
    "    wiki_movies_df.drop('Budget', axis=1, inplace=True)\n",
    "\n",
    "  \n",
    "\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 == list else x)\n",
    "    date_form_one = r'(?:January|February|March|April|May|June|July|August|September|October|November|December)\\s[123]?\\d,\\s\\d{4}'\n",
    "    date_form_two = r'\\d{4}.[01]\\d.[0123]\\d'\n",
    "    date_form_three = r'(?:January|February|March|April|May|June|July|August|September|October|November|December)\\s\\d{4}'\n",
    "    date_form_four = r'\\d{4}'\n",
    "\n",
    "    \n",
    "\n",
    "    wiki_movies_df['release_date'] = pd.to_datetime(release_date.str.extract(\n",
    "        f'({date_form_one}|{date_form_two}|{date_form_three}|{date_form_four})')[0], infer_datetime_format=True)\n",
    "\n",
    "    #wiki_movies_df.drop('Release date', axis=1, inplace=True)\n",
    "\n",
    "\n",
    "    # 16. Clean the running time column in the wiki_movies_df DataFrame.\n",
    "    running_time = wiki_movies_df['Running time'].dropna().apply(\n",
    "        lambda x: ' '.join(x) if type(x) == list else x)\n",
    "\n",
    "    running_time_extract = running_time.str.extract(\n",
    "        r'(\\d+)\\s*ho?u?r?s?\\s*(\\d*)|(\\d+)\\s*m')\n",
    "\n",
    "    running_time_extract = running_time_extract.apply(\n",
    "        lambda c: pd.to_numeric(c, errors='coerce')).fillna(0)\n",
    "\n",
    "    wiki_movies_df['running_time'] = running_time_extract.apply(\n",
    "        lambda r: r[0]*60 + r[1] if r[2]==0 else r[2], axis=1)\n",
    "\n",
    "    wiki_movies_df.drop('Running time', axis=1, inplace=True)\n",
    "\n",
    "    # Return three variables. The first is the wiki_movies_df DataFrame\n",
    "    \n",
    "    return wiki_movies_df, kaggle_metadata, ratings "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 17. Create the path to your file directory and variables for the three files.\n",
    "file_dir = 'C:/Users/justi/Onedrive/Desktop/Analytics'\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": 80,
   "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": 81,
   "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": 82,
   "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>Based on</th>\n",
       "      <th>Starring</th>\n",
       "      <th>Cinematography</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Country</th>\n",
       "      <th>Language</th>\n",
       "      <th>...</th>\n",
       "      <th>Editor(s)</th>\n",
       "      <th>Composer(s)</th>\n",
       "      <th>Producer(s)</th>\n",
       "      <th>Production company(s)</th>\n",
       "      <th>Writer(s)</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>box_office</th>\n",
       "      <th>budget</th>\n",
       "      <th>release_date</th>\n",
       "      <th>running_time</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>[Characters, by Rex Weiner]</td>\n",
       "      <td>[Andrew Dice Clay, Wayne Newton, Priscilla Pre...</td>\n",
       "      <td>Oliver Wood</td>\n",
       "      <td>[July 11, 1990, (, 1990-07-11, )]</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>Michael Tronick</td>\n",
       "      <td>[Cliff Eidelman, Yello]</td>\n",
       "      <td>[Steve Perry, Joel Silver]</td>\n",
       "      <td>Silver Pictures</td>\n",
       "      <td>[David Arnott, James Cappe]</td>\n",
       "      <td>tt0098987</td>\n",
       "      <td>21400000.0</td>\n",
       "      <td>20000000.0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>102.0</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>[the novel, After Dark, My Sweet, by, Jim Thom...</td>\n",
       "      <td>[Jason Patric, Rachel Ward, Bruce Dern, George...</td>\n",
       "      <td>Mark Plummer</td>\n",
       "      <td>[May 17, 1990, (, 1990-05-17, ), (Cannes Film ...</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>Howard E. Smith</td>\n",
       "      <td>Maurice Jarre</td>\n",
       "      <td>[Ric Kidney, Robert Redlin]</td>\n",
       "      <td>Avenue Pictures</td>\n",
       "      <td>[James Foley, Robert Redlin]</td>\n",
       "      <td>tt0098994</td>\n",
       "      <td>2700000.0</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>114.0</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>[Air America, by, Christopher Robbins]</td>\n",
       "      <td>[Mel Gibson, Robert Downey Jr., Nancy Travis, ...</td>\n",
       "      <td>Roger Deakins</td>\n",
       "      <td>[August 10, 1990, (, 1990-08-10, )]</td>\n",
       "      <td>United States</td>\n",
       "      <td>[English, Lao]</td>\n",
       "      <td>...</td>\n",
       "      <td>[John Bloom, Lois Freeman-Fox]</td>\n",
       "      <td>Charles Gross</td>\n",
       "      <td>Daniel Melnick</td>\n",
       "      <td>[Carolco Pictures, IndieProd Company]</td>\n",
       "      <td>[John Eskow, Richard Rush]</td>\n",
       "      <td>tt0099005</td>\n",
       "      <td>57718089.0</td>\n",
       "      <td>35000000.0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>113.0</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>NaN</td>\n",
       "      <td>[Alec Baldwin, Blythe Danner, Judy Davis, Mia ...</td>\n",
       "      <td>Carlo Di Palma</td>\n",
       "      <td>[December 25, 1990, (, 1990-12-25, )]</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>Susan E. Morse</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Robert Greenhut</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>tt0099012</td>\n",
       "      <td>7331647.0</td>\n",
       "      <td>12000000.0</td>\n",
       "      <td>NaT</td>\n",
       "      <td>106.0</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>NaN</td>\n",
       "      <td>[Paul Hogan, Elias Koteas, Linda Kozlowski]</td>\n",
       "      <td>Russell Boyd</td>\n",
       "      <td>December 19, 1990</td>\n",
       "      <td>US</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>David Stiven</td>\n",
       "      <td>Maurice Jarre</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Paul Hogan</td>\n",
       "      <td>tt0099018</td>\n",
       "      <td>6939946.0</td>\n",
       "      <td>25000000.0</td>\n",
       "      <td>1990-12-19</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 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",
       "                                            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  Cinematography  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...     Oliver Wood   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...    Mark Plummer   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...   Roger Deakins   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...  Carlo Di Palma   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]    Russell Boyd   \n",
       "\n",
       "                                        Release date        Country  \\\n",
       "0                  [July 11, 1990, (, 1990-07-11, )]  United States   \n",
       "1  [May 17, 1990, (, 1990-05-17, ), (Cannes Film ...  United States   \n",
       "2                [August 10, 1990, (, 1990-08-10, )]  United States   \n",
       "3              [December 25, 1990, (, 1990-12-25, )]  United States   \n",
       "4                                  December 19, 1990             US   \n",
       "\n",
       "         Language  ...                       Editor(s)  \\\n",
       "0         English  ...                 Michael Tronick   \n",
       "1         English  ...                 Howard E. Smith   \n",
       "2  [English, Lao]  ...  [John Bloom, Lois Freeman-Fox]   \n",
       "3         English  ...                  Susan E. Morse   \n",
       "4         English  ...                    David Stiven   \n",
       "\n",
       "               Composer(s)                  Producer(s)  \\\n",
       "0  [Cliff Eidelman, Yello]   [Steve Perry, Joel Silver]   \n",
       "1            Maurice Jarre  [Ric Kidney, Robert Redlin]   \n",
       "2            Charles Gross               Daniel Melnick   \n",
       "3                      NaN              Robert Greenhut   \n",
       "4            Maurice Jarre                 John Cornell   \n",
       "\n",
       "                   Production company(s)                     Writer(s)  \\\n",
       "0                        Silver Pictures   [David Arnott, James Cappe]   \n",
       "1                        Avenue Pictures  [James Foley, Robert Redlin]   \n",
       "2  [Carolco Pictures, IndieProd Company]    [John Eskow, Richard Rush]   \n",
       "3                                    NaN                   Woody Allen   \n",
       "4                                    NaN                    Paul Hogan   \n",
       "\n",
       "     imdb_id  box_office      budget  release_date  running_time  \n",
       "0  tt0098987  21400000.0  20000000.0           NaT         102.0  \n",
       "1  tt0098994   2700000.0   6000000.0           NaT         114.0  \n",
       "2  tt0099005  57718089.0  35000000.0           NaT         113.0  \n",
       "3  tt0099012   7331647.0  12000000.0           NaT         106.0  \n",
       "4  tt0099018   6939946.0  25000000.0    1990-12-19          95.0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 82,
     "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": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['url',\n",
       " 'year',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'Based on',\n",
       " 'Starring',\n",
       " 'Cinematography',\n",
       " 'Release date',\n",
       " 'Country',\n",
       " 'Language',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Composer(s)',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Writer(s)',\n",
       " 'imdb_id',\n",
       " 'box_office',\n",
       " 'budget',\n",
       " 'release_date',\n",
       " 'running_time']"
      ]
     },
     "execution_count": 83,
     "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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