Movies_ETL.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "from sqlalchemy import create_engine\n",
    "from config import db_password\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Resources\\\\\\\\wikipedia.movies.json'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_dir = r\"Resources\\\\\"\n",
    "f'{file_dir}wikipedia.movies.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(f'{file_dir}wikipedia.movies.json', mode='r') as file:\n",
    "    wiki_movies_raw = json.load(file)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7311"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(wiki_movies_raw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'url': 'https://en.wikipedia.org/wiki/The_Adventures_of_Ford_Fairlane',\n",
       "  'year': 1990,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0098987/',\n",
       "  'title': 'The Adventures of Ford Fairlane',\n",
       "  'Directed by': 'Renny Harlin',\n",
       "  'Produced by': ['Steve Perry', 'Joel Silver'],\n",
       "  'Screenplay by': ['David Arnott', 'James Cappe', 'Daniel Waters'],\n",
       "  'Story by': ['David Arnott', 'James Cappe'],\n",
       "  'Based on': ['Characters', 'by Rex Weiner'],\n",
       "  'Starring': ['Andrew Dice Clay',\n",
       "   'Wayne Newton',\n",
       "   'Priscilla Presley',\n",
       "   'Lauren Holly',\n",
       "   'Morris Day',\n",
       "   'Robert Englund',\n",
       "   \"Ed O'Neill\"],\n",
       "  'Narrated by': 'Andrew \"Dice\" Clay',\n",
       "  'Music by': ['Cliff Eidelman', 'Yello'],\n",
       "  'Cinematography': 'Oliver Wood',\n",
       "  'Edited by': 'Michael Tronick',\n",
       "  'Productioncompany ': 'Silver Pictures',\n",
       "  'Distributed by': '20th Century Fox',\n",
       "  'Release date': ['July 11, 1990', '(', '1990-07-11', ')'],\n",
       "  'Running time': '102 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$20 million',\n",
       "  'Box office': '$21.4 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/After_Dark,_My_Sweet',\n",
       "  'year': 1990,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0098994/',\n",
       "  'title': 'After Dark, My Sweet',\n",
       "  'Directed by': 'James Foley',\n",
       "  'Produced by': ['Ric Kidney', 'Robert Redlin'],\n",
       "  'Screenplay by': ['James Foley', 'Robert Redlin'],\n",
       "  'Based on': ['the novel', 'After Dark, My Sweet', 'by', 'Jim Thompson'],\n",
       "  'Starring': ['Jason Patric',\n",
       "   'Rachel Ward',\n",
       "   'Bruce Dern',\n",
       "   'George Dickerson'],\n",
       "  'Music by': 'Maurice Jarre',\n",
       "  'Cinematography': 'Mark Plummer',\n",
       "  'Edited by': 'Howard E. Smith',\n",
       "  'Productioncompany ': 'Avenue Pictures',\n",
       "  'Distributed by': 'Avenue Pictures',\n",
       "  'Release date': ['May 17, 1990',\n",
       "   '(',\n",
       "   '1990-05-17',\n",
       "   ')',\n",
       "   '(Cannes Film Market)',\n",
       "   'August 24, 1990',\n",
       "   '(',\n",
       "   '1990-08-24',\n",
       "   ')',\n",
       "   '(United States)'],\n",
       "  'Running time': '114 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$6 million',\n",
       "  'Box office': '$2.7 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Air_America_(film)',\n",
       "  'year': 1990,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0099005/',\n",
       "  'title': 'Air America',\n",
       "  'Directed by': 'Roger Spottiswoode',\n",
       "  'Produced by': 'Daniel Melnick',\n",
       "  'Screenplay by': ['John Eskow', 'Richard Rush'],\n",
       "  'Based on': ['Air America', 'by', 'Christopher Robbins'],\n",
       "  'Starring': ['Mel Gibson',\n",
       "   'Robert Downey Jr.',\n",
       "   'Nancy Travis',\n",
       "   'David Marshall Grant',\n",
       "   'Lane Smith'],\n",
       "  'Music by': 'Charles Gross',\n",
       "  'Cinematography': 'Roger Deakins',\n",
       "  'Edited by': ['John Bloom', 'Lois Freeman-Fox'],\n",
       "  'Productioncompany ': ['Carolco Pictures', 'IndieProd Company'],\n",
       "  'Distributed by': 'TriStar Pictures',\n",
       "  'Release date': ['August 10, 1990', '(', '1990-08-10', ')'],\n",
       "  'Running time': '113 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': ['English', 'Lao'],\n",
       "  'Budget': '$35 million',\n",
       "  'Box office': '$57,718,089'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Alice_(1990_film)',\n",
       "  'year': 1990,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0099012/',\n",
       "  'title': 'Alice',\n",
       "  'Directed by': 'Woody Allen',\n",
       "  'Produced by': 'Robert Greenhut',\n",
       "  'Written by': 'Woody Allen',\n",
       "  'Starring': ['Alec Baldwin',\n",
       "   'Blythe Danner',\n",
       "   'Judy Davis',\n",
       "   'Mia Farrow',\n",
       "   'William Hurt',\n",
       "   'Keye Luke',\n",
       "   'Joe Mantegna',\n",
       "   'Bernadette Peters'],\n",
       "  'Cinematography': 'Carlo Di Palma',\n",
       "  'Edited by': 'Susan E. Morse',\n",
       "  'Distributed by': 'Orion Pictures',\n",
       "  'Release date': ['December 25, 1990', '(', '1990-12-25', ')'],\n",
       "  'Running time': '106 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$12 million',\n",
       "  'Box office': '$7,331,647'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Almost_an_Angel',\n",
       "  'year': 1990,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0099018/',\n",
       "  'title': 'Almost an Angel',\n",
       "  'Directed by': 'John Cornell',\n",
       "  'Produced by': 'John Cornell',\n",
       "  'Written by': 'Paul Hogan',\n",
       "  'Starring': ['Paul Hogan', 'Elias Koteas', 'Linda Kozlowski'],\n",
       "  'Music by': 'Maurice Jarre',\n",
       "  'Cinematography': 'Russell Boyd',\n",
       "  'Edited by': 'David Stiven',\n",
       "  'Distributed by': 'Paramount Pictures',\n",
       "  'Release date': 'December 19, 1990',\n",
       "  'Running time': '95 minutes',\n",
       "  'Country': 'US',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$25 million',\n",
       "  'Box office': '$6,939,946 (USA)'}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First 5 records\n",
    "wiki_movies_raw[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'url': 'https://en.wikipedia.org/wiki/Holmes_%26_Watson',\n",
       "  'year': 2018,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt1255919/',\n",
       "  'title': 'Holmes & Watson',\n",
       "  'Directed by': 'Etan Cohen',\n",
       "  'Produced by': ['Will Ferrell',\n",
       "   'Adam McKay',\n",
       "   'Jimmy Miller',\n",
       "   'Clayton Townsend'],\n",
       "  'Screenplay by': 'Etan Cohen',\n",
       "  'Based on': ['Sherlock Holmes',\n",
       "   'and',\n",
       "   'Dr. Watson',\n",
       "   'by',\n",
       "   'Sir Arthur Conan Doyle'],\n",
       "  'Starring': ['Will Ferrell',\n",
       "   'John C. Reilly',\n",
       "   'Rebecca Hall',\n",
       "   'Rob Brydon',\n",
       "   'Steve Coogan',\n",
       "   'Ralph Fiennes'],\n",
       "  'Music by': 'Mark Mothersbaugh',\n",
       "  'Cinematography': 'Oliver Wood',\n",
       "  'Edited by': 'Dean Zimmerman',\n",
       "  'Productioncompanies ': ['Columbia Pictures',\n",
       "   'Gary Sanchez Productions',\n",
       "   'Mosaic Media Group',\n",
       "   'Mimran Schur Pictures'],\n",
       "  'Distributed by': 'Sony Pictures Releasing',\n",
       "  'Release date': ['December 25, 2018',\n",
       "   '(',\n",
       "   '2018-12-25',\n",
       "   ')',\n",
       "   '(United States)'],\n",
       "  'Running time': '90 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$42 million',\n",
       "  'Box office': '$41.9 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Vice_(2018_film)',\n",
       "  'year': 2018,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt6266538/',\n",
       "  'title': 'Vice',\n",
       "  'Directed by': 'Adam McKay',\n",
       "  'Produced by': ['Brad Pitt',\n",
       "   'Dede Gardner',\n",
       "   'Jeremy Kleiner',\n",
       "   'Kevin J. Messick',\n",
       "   'Will Ferrell',\n",
       "   'Adam McKay'],\n",
       "  'Written by': 'Adam McKay',\n",
       "  'Starring': ['Christian Bale',\n",
       "   'Amy Adams',\n",
       "   'Steve Carell',\n",
       "   'Sam Rockwell',\n",
       "   'Tyler Perry',\n",
       "   'Alison Pill',\n",
       "   'Lily Rabe',\n",
       "   'Jesse Plemons'],\n",
       "  'Music by': 'Nicholas Britell',\n",
       "  'Cinematography': 'Greig Fraser',\n",
       "  'Edited by': 'Hank Corwin',\n",
       "  'Productioncompany ': ['Plan B Entertainment',\n",
       "   'Gary Sanchez Productions',\n",
       "   'Annapurna Pictures'],\n",
       "  'Distributed by': 'Mirror Releasing',\n",
       "  'Release date': ['December 11, 2018',\n",
       "   '(',\n",
       "   '2018-12-11',\n",
       "   ')',\n",
       "   '(',\n",
       "   'Samuel Goldwyn Theater',\n",
       "   ')',\n",
       "   'December 25, 2018',\n",
       "   '(',\n",
       "   '2018-12-25',\n",
       "   ')',\n",
       "   '(United States)'],\n",
       "  'Running time': '132 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$60 million',\n",
       "  'Box office': '$76.1 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/On_the_Basis_of_Sex',\n",
       "  'year': 2018,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt4669788/',\n",
       "  'title': 'On the Basis of Sex',\n",
       "  'Directed by': 'Mimi Leder',\n",
       "  'Produced by': 'Robert W. Cort',\n",
       "  'Written by': 'Daniel Stiepleman',\n",
       "  'Starring': ['Felicity Jones',\n",
       "   'Armie Hammer',\n",
       "   'Justin Theroux',\n",
       "   'Sam Waterston',\n",
       "   'Kathy Bates'],\n",
       "  'Music by': 'Mychael Danna',\n",
       "  'Cinematography': 'Michael Grady',\n",
       "  'Edited by': 'Michelle Tesoro',\n",
       "  'Productioncompanies ': ['Focus Features',\n",
       "   '[1]',\n",
       "   'Participant Media',\n",
       "   '[1]',\n",
       "   'Robert Cort Productions',\n",
       "   '[1]',\n",
       "   'Alibaba Pictures',\n",
       "   '[2]'],\n",
       "  'Distributed by': 'Focus Features',\n",
       "  'Release date': ['November 8, 2018',\n",
       "   '(',\n",
       "   '2018-11-08',\n",
       "   ')',\n",
       "   '(',\n",
       "   'AFI Fest',\n",
       "   ')',\n",
       "   'December 25, 2018',\n",
       "   '(',\n",
       "   '2018-12-25',\n",
       "   ')',\n",
       "   '(United States)'],\n",
       "  'Running time': '120 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$20 million',\n",
       "  'Box office': '$38.4 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Destroyer_(2018_film)',\n",
       "  'year': 2018,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt7137380/',\n",
       "  'title': 'Destroyer',\n",
       "  'Directed by': 'Karyn Kusama',\n",
       "  'Produced by': ['Fred Berger', 'Phil Hay', 'Matt Manfredi'],\n",
       "  'Written by': ['Phil Hay', 'Matt Manfredi'],\n",
       "  'Starring': ['Nicole Kidman',\n",
       "   'Sebastian Stan',\n",
       "   'Toby Kebbell',\n",
       "   'Tatiana Maslany',\n",
       "   'Bradley Whitford',\n",
       "   'Jade Pettyjohn',\n",
       "   'Scoot McNairy'],\n",
       "  'Music by': 'Theodore Shapiro',\n",
       "  'Cinematography': 'Julie Kirkwood',\n",
       "  'Edited by': 'Plummy Tucker',\n",
       "  'Productioncompany ': ['30West',\n",
       "   'Automatik Entertainment',\n",
       "   'Annapurna Pictures'],\n",
       "  'Distributed by': 'Mirror Releasing',\n",
       "  'Release date': ['August 31, 2018',\n",
       "   '(',\n",
       "   '2018-08-31',\n",
       "   ')',\n",
       "   '(',\n",
       "   'Telluride',\n",
       "   ')',\n",
       "   'December 25, 2018',\n",
       "   '(',\n",
       "   '2018-12-25',\n",
       "   ')',\n",
       "   '(United States)'],\n",
       "  'Running time': '123 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$9 million',\n",
       "  'Box office': '$5.5 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Black_Mirror:_Bandersnatch',\n",
       "  'year': 2018,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt9495224/',\n",
       "  'title': 'Bandersnatch',\n",
       "  'Directed by': 'David Slade',\n",
       "  'Produced by': 'Russell McLean',\n",
       "  'Written by': 'Charlie Brooker',\n",
       "  'Starring': ['Fionn Whitehead',\n",
       "   'Will Poulter',\n",
       "   'Craig Parkinson',\n",
       "   'Alice Lowe',\n",
       "   'Asim Chaudhry'],\n",
       "  'Music by': 'Brian Reitzell',\n",
       "  'Cinematography': ['Aaron Morton', 'Jake Polonsky'],\n",
       "  'Edited by': 'Tony Kearns',\n",
       "  'Productioncompany ': ['House of Tomorrow', 'Netflix'],\n",
       "  'Distributed by': 'Netflix',\n",
       "  'Release date': ['28 December 2018', '(', '2018-12-28', ')'],\n",
       "  'Running time': 'Variable; 90 minutes for default path',\n",
       "  'Country': 'United Kingdom',\n",
       "  'Language': 'English'}]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Last 5 records\n",
    "wiki_movies_raw[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'url': 'https://en.wikipedia.org/wiki/Benji:_Off_the_Leash!',\n",
       "  'year': 2004,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0315273/',\n",
       "  'title': 'Benji: Off the Leash!',\n",
       "  'Directed by': 'Joe Camp',\n",
       "  'Written by': 'Joe Camp',\n",
       "  'Starring': ['Benji', 'Nick Whitaker', 'Shaggy', 'Gypsy the Cockatoo'],\n",
       "  'Music by': 'Antonio di Lorenzo',\n",
       "  'Productioncompany ': 'Mulberry Square Productions',\n",
       "  'Distributed by': 'Mulberry Square Productions',\n",
       "  'Release date': ['March 26, 2004', '(', '2004-03-26', ')'],\n",
       "  'Running time': '97 min',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Box office': '$3,817,362'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/The_Best_Thief_in_the_World',\n",
       "  'year': 2004,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0389796/',\n",
       "  'title': 'The Best Thief in the World',\n",
       "  'Directed by': 'Jacob Kornbluth',\n",
       "  'Produced by': ['Tim Perrell', 'Nicola Usborne'],\n",
       "  'Written by': 'Jacob Kornbluth',\n",
       "  'Starring': ['Marc Rozendaal',\n",
       "   'Michael Silverman',\n",
       "   'David Warshofsky',\n",
       "   'Audra McDonald',\n",
       "   'Lois Smith'],\n",
       "  'Music by': ['Prince Paul', 'and', 'Don Newkirk'],\n",
       "  'Cinematography': 'Ben Kutchins',\n",
       "  'Edited by': 'Stephanie Sterner',\n",
       "  'Distributed by': 'Showtime Networks',\n",
       "  'Release date': ['January 16, 2004', '(', '2004-01-16', ')'],\n",
       "  'Running time': '93 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Beyond_the_Sea_(2004_film)',\n",
       "  'year': 2004,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0363473/',\n",
       "  'title': 'Beyond the Sea',\n",
       "  'Directed by': 'Kevin Spacey',\n",
       "  'Produced by': ['Kevin Spacey',\n",
       "   'Phillip Barry',\n",
       "   'Dana Brunetti',\n",
       "   'Arthur Friedman',\n",
       "   'Jan Fantl',\n",
       "   'Andy Paterson'],\n",
       "  'Written by': ['Lewis Colick', 'Kevin Spacey'],\n",
       "  'Starring': ['Kevin Spacey', 'Kate Bosworth', 'Bob Hoskins', 'John Goodman'],\n",
       "  'Music by': 'Bobby Darin',\n",
       "  'Cinematography': 'Eduardo Serra',\n",
       "  'Edited by': 'Trevor Waite',\n",
       "  'Productioncompany ': 'Trigger Street Productions',\n",
       "  'Distributed by': ['Lionsgate Films',\n",
       "   '(USA)',\n",
       "   'Entertainment Film Distributors',\n",
       "   '(UK)',\n",
       "   'GAGA',\n",
       "   '(Japan)',\n",
       "   'Maple Pictures',\n",
       "   '(Canada)'],\n",
       "  'Release date': ['December 17, 2004', '(', '2004-12-17', ')'],\n",
       "  'Running time': '118 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$25 million',\n",
       "  'Box office': '$8.4 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/The_Big_Bounce_(2004_film)',\n",
       "  'year': 2004,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0315824/',\n",
       "  'title': 'The Big Bounce',\n",
       "  'Directed by': 'George Armitage',\n",
       "  'Produced by': ['George Armitage', 'Steve Bing'],\n",
       "  'Screenplay by': 'Sebastian Gutierrez',\n",
       "  'Based on': ['The Big Bounce', 'by', 'Elmore Leonard'],\n",
       "  'Starring': ['Owen Wilson',\n",
       "   'Charlie Sheen',\n",
       "   'Morgan Freeman',\n",
       "   'Sara Foster',\n",
       "   'Gary Sinise'],\n",
       "  'Music by': 'George S. Clinton',\n",
       "  'Cinematography': 'Jeffrey L. Kimball',\n",
       "  'Edited by': 'Barry Malkin',\n",
       "  'Productioncompany ': 'Shangri-La Entertainment',\n",
       "  'Distributed by': 'Warner Bros. Pictures',\n",
       "  'Release date': ['January 30, 2004', '(', '2004-01-30', ')'],\n",
       "  'Running time': '88 minutes',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$50 million',\n",
       "  'Box office': '$6.8 million'},\n",
       " {'url': 'https://en.wikipedia.org/wiki/Birth_(film)',\n",
       "  'year': 2004,\n",
       "  'imdb_link': 'https://www.imdb.com/title/tt0337876/',\n",
       "  'title': 'Birth',\n",
       "  'Directed by': 'Jonathan Glazer',\n",
       "  'Produced by': ['Lizie Gower', 'Nick Morris', 'Jean-Louis Piel'],\n",
       "  'Written by': ['Jean-Claude Carrière', 'Milo Addica', 'Jonathan Glazer'],\n",
       "  'Starring': ['Nicole Kidman',\n",
       "   'Cameron Bright',\n",
       "   'Danny Huston',\n",
       "   'Lauren Bacall'],\n",
       "  'Music by': 'Alexandre Desplat',\n",
       "  'Cinematography': 'Harris Savides',\n",
       "  'Edited by': ['Sam Sneade', 'Claus Wehlisch'],\n",
       "  'Distributed by': 'New Line Cinema',\n",
       "  'Release date': ['November 8, 2004', '(', '2004-11-08', ')'],\n",
       "  'Running time': '96 minutes',\n",
       "  'Country': 'United States',\n",
       "  'Language': 'English',\n",
       "  'Budget': '$20 million',\n",
       "  'Box office': '$23.9 million'}]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Some records in the middle\n",
    "wiki_movies_raw[3600:3605]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "kaggle_metadata = pd.read_csv(f'{file_dir}movies_metadata.csv', low_memory=False)\n",
    "ratings = pd.read_csv(f'{file_dir}ratings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
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       "   adult                              belongs_to_collection    budget  \\\n",
       "0  False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
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       "2  False  {'id': 119050, 'name': 'Grumpy Old Men Collect...         0   \n",
       "3  False                                                NaN  16000000   \n",
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       "\n",
       "                                              genres  \\\n",
       "0  [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
       "1  [{'id': 12, 'name': 'Adventure'}, {'id': 14, '...   \n",
       "2  [{'id': 10749, 'name': 'Romance'}, {'id': 35, ...   \n",
       "3  [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...   \n",
       "4                     [{'id': 35, 'name': 'Comedy'}]   \n",
       "\n",
       "                               homepage     id    imdb_id original_language  \\\n",
       "0  http://toystory.disney.com/toy-story    862  tt0114709                en   \n",
       "1                                   NaN   8844  tt0113497                en   \n",
       "2                                   NaN  15602  tt0113228                en   \n",
       "3                                   NaN  31357  tt0114885                en   \n",
       "4                                   NaN  11862  tt0113041                en   \n",
       "\n",
       "                original_title  \\\n",
       "0                    Toy Story   \n",
       "1                      Jumanji   \n",
       "2             Grumpier Old Men   \n",
       "3            Waiting to Exhale   \n",
       "4  Father of the Bride Part II   \n",
       "\n",
       "                                            overview  ... release_date  \\\n",
       "0  Led by Woody, Andy's toys live happily in his ...  ...   1995-10-30   \n",
       "1  When siblings Judy and Peter discover an encha...  ...   1995-12-15   \n",
       "2  A family wedding reignites the ancient feud be...  ...   1995-12-22   \n",
       "3  Cheated on, mistreated and stepped on, the wom...  ...   1995-12-22   \n",
       "4  Just when George Banks has recovered from his ...  ...   1995-02-10   \n",
       "\n",
       "       revenue runtime                                   spoken_languages  \\\n",
       "0  373554033.0    81.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "1  262797249.0   104.0  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...   \n",
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       "3   81452156.0   127.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "4   76578911.0   106.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "\n",
       "     status                                            tagline  \\\n",
       "0  Released                                                NaN   \n",
       "1  Released          Roll the dice and unleash the excitement!   \n",
       "2  Released  Still Yelling. Still Fighting. Still Ready for...   \n",
       "3  Released  Friends are the people who let you be yourself...   \n",
       "4  Released  Just When His World Is Back To Normal... He's ...   \n",
       "\n",
       "                         title  video vote_average vote_count  \n",
       "0                    Toy Story  False          7.7     5415.0  \n",
       "1                      Jumanji  False          6.9     2413.0  \n",
       "2             Grumpier Old Men  False          6.5       92.0  \n",
       "3            Waiting to Exhale  False          6.1       34.0  \n",
       "4  Father of the Bride Part II  False          5.7      173.0  \n",
       "\n",
       "[5 rows x 24 columns]"
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     },
     "execution_count": 10,
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       "      <td>[Air America, by, Christopher Robbins]</td>\n",
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       "                                                 url    year  \\\n",
       "0  https://en.wikipedia.org/wiki/The_Adventures_o...  1990.0   \n",
       "1  https://en.wikipedia.org/wiki/After_Dark,_My_S...  1990.0   \n",
       "2   https://en.wikipedia.org/wiki/Air_America_(film)  1990.0   \n",
       "3    https://en.wikipedia.org/wiki/Alice_(1990_film)  1990.0   \n",
       "4      https://en.wikipedia.org/wiki/Almost_an_Angel  1990.0   \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  ... Predecessor  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...  ...         NaN   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...  ...         NaN   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...  ...         NaN   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...  ...         NaN   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]  ...         NaN   \n",
       "\n",
       "  Founders Area served Products Services Russian Hebrew Revenue  \\\n",
       "0      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "1      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "2      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "3      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "4      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "\n",
       "  Operating income Polish  \n",
       "0              NaN    NaN  \n",
       "1              NaN    NaN  \n",
       "2              NaN    NaN  \n",
       "3              NaN    NaN  \n",
       "4              NaN    NaN  \n",
       "\n",
       "[5 rows x 193 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df = pd.DataFrame(wiki_movies_raw)\n",
    "wiki_movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "193"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7080"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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",
    "len(wiki_movies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>url</th>\n",
       "      <th>year</th>\n",
       "      <th>imdb_link</th>\n",
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       "      <th>Starring</th>\n",
       "      <th>...</th>\n",
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       "      <th>Cantonese</th>\n",
       "      <th>Chinese</th>\n",
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       "      <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",
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       "      <td>NaN</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",
       "      <td>NaN</td>\n",
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       "      <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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>5 rows × 78 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  ... Hepburn Literally  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...  ...     NaN       NaN   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...  ...     NaN       NaN   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...  ...     NaN       NaN   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...  ...     NaN       NaN   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]  ...     NaN       NaN   \n",
       "\n",
       "  Cantonese Chinese Yiddish Arabic Romanized Russian Hebrew Polish  \n",
       "0       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "1       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "2       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "3       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "4       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "\n",
       "[5 rows x 78 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df1 = pd.DataFrame(wiki_movies)\n",
    "wiki_movies_df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>NaN</td>\n",
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       "      <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",
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       "      <td>[James Foley, Robert Redlin]</td>\n",
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       "      <td>[the novel, After Dark, My Sweet, by, Jim Thom...</td>\n",
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       "      <td>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <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>NaN</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      ],
      "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  ... Hepburn Literally  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...  ...     NaN       NaN   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...  ...     NaN       NaN   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...  ...     NaN       NaN   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...  ...     NaN       NaN   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]  ...     NaN       NaN   \n",
       "\n",
       "  Cantonese Chinese Yiddish Arabic Romanized Russian Hebrew Polish  \n",
       "0       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "1       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "2       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "3       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "4       NaN     NaN     NaN    NaN       NaN     NaN    NaN    NaN  \n",
       "\n",
       "[5 rows x 75 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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",
    "wiki_movies_df2 = pd.DataFrame(wiki_movies)\n",
    "wiki_movies_df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_movie(movie):\n",
    "    movie = dict(movie) \n",
    "    #create a non-destructive copy\n",
    "    return movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Predecessor</th>\n",
       "      <th>Founders</th>\n",
       "      <th>Area served</th>\n",
       "      <th>Products</th>\n",
       "      <th>Services</th>\n",
       "      <th>Russian</th>\n",
       "      <th>Hebrew</th>\n",
       "      <th>Revenue</th>\n",
       "      <th>Operating income</th>\n",
       "      <th>Polish</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7060</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Insult_(film)</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>https://www.imdb.com/title/tt7048622/</td>\n",
       "      <td>The Insult</td>\n",
       "      <td>Ziad Doueiri</td>\n",
       "      <td>[Rachid Bouchareb, Jean Bréhat, Julie Gayet, A...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Adel Karam, Kamel El Basha]</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7293</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Capernaum_(film)</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>https://www.imdb.com/title/tt8267604/</td>\n",
       "      <td>Capernaum</td>\n",
       "      <td>Nadine Labaki</td>\n",
       "      <td>[Michel Merkt, Khaled Mouzanar]</td>\n",
       "      <td>[Nadine Labaki, Jihad Hojaily, Michelle Keserw...</td>\n",
       "      <td>[Georges Khabbaz, Nadine Labaki, Michelle Kese...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Zain Al Rafeea, Yordanos Shiferaw, Boluwatife...</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 193 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  url    year  \\\n",
       "7060  https://en.wikipedia.org/wiki/The_Insult_(film)  2018.0   \n",
       "7293   https://en.wikipedia.org/wiki/Capernaum_(film)  2018.0   \n",
       "\n",
       "                                  imdb_link       title    Directed by  \\\n",
       "7060  https://www.imdb.com/title/tt7048622/  The Insult   Ziad Doueiri   \n",
       "7293  https://www.imdb.com/title/tt8267604/   Capernaum  Nadine Labaki   \n",
       "\n",
       "                                            Produced by  \\\n",
       "7060  [Rachid Bouchareb, Jean Bréhat, Julie Gayet, A...   \n",
       "7293                    [Michel Merkt, Khaled Mouzanar]   \n",
       "\n",
       "                                          Screenplay by  \\\n",
       "7060                                                NaN   \n",
       "7293  [Nadine Labaki, Jihad Hojaily, Michelle Keserw...   \n",
       "\n",
       "                                               Story by Based on  \\\n",
       "7060                                                NaN      NaN   \n",
       "7293  [Georges Khabbaz, Nadine Labaki, Michelle Kese...      NaN   \n",
       "\n",
       "                                               Starring  ... Predecessor  \\\n",
       "7060                       [Adel Karam, Kamel El Basha]  ...         NaN   \n",
       "7293  [Zain Al Rafeea, Yordanos Shiferaw, Boluwatife...  ...         NaN   \n",
       "\n",
       "     Founders Area served Products Services Russian Hebrew Revenue  \\\n",
       "7060      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "7293      NaN         NaN      NaN      NaN     NaN    NaN     NaN   \n",
       "\n",
       "     Operating income Polish  \n",
       "7060              NaN    NaN  \n",
       "7293              NaN    NaN  \n",
       "\n",
       "[2 rows x 193 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df[wiki_movies_df['Arabic'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7060    https://en.wikipedia.org/wiki/The_Insult_(film)\n",
       "7293     https://en.wikipedia.org/wiki/Capernaum_(film)\n",
       "Name: url, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df[wiki_movies_df['Arabic'].notnull()]['url']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Actor control',\n",
       " 'Adaptation by',\n",
       " 'Alias',\n",
       " 'Alma mater',\n",
       " 'Also known as',\n",
       " 'Animation by',\n",
       " 'Arabic',\n",
       " 'Area',\n",
       " 'Area served',\n",
       " 'Artist(s)',\n",
       " 'Attraction type',\n",
       " 'Audio format',\n",
       " 'Author',\n",
       " 'Based on',\n",
       " 'Biographical data',\n",
       " 'Bopomofo',\n",
       " 'Born',\n",
       " 'Box office',\n",
       " 'Budget',\n",
       " 'Camera setup',\n",
       " 'Cantonese',\n",
       " 'Characters',\n",
       " 'Children',\n",
       " 'Chinese',\n",
       " 'Cinematography',\n",
       " 'Closing date',\n",
       " 'Color process',\n",
       " 'Comics',\n",
       " 'Composer(s)',\n",
       " 'Coordinates',\n",
       " 'Country',\n",
       " 'Country of origin',\n",
       " 'Cover artist',\n",
       " 'Created by',\n",
       " 'Date premiered',\n",
       " 'Designer(s)',\n",
       " 'Developed by',\n",
       " 'Developer(s)',\n",
       " 'Dewey Decimal',\n",
       " 'Died',\n",
       " 'Directed by',\n",
       " 'Director',\n",
       " 'Distributed by',\n",
       " 'Distributor',\n",
       " 'Divisions',\n",
       " 'Duration',\n",
       " 'Edited by',\n",
       " 'Editor(s)',\n",
       " 'Ending theme',\n",
       " 'Engine',\n",
       " 'Engine(s)',\n",
       " 'Executive producer(s)',\n",
       " 'Family',\n",
       " 'Fate',\n",
       " 'Film(s)',\n",
       " 'Followed by',\n",
       " 'Format(s)',\n",
       " 'Formerly',\n",
       " 'Founded',\n",
       " 'Founder',\n",
       " 'Founders',\n",
       " 'French',\n",
       " 'Full name',\n",
       " 'Gender',\n",
       " 'Genre',\n",
       " 'Genre(s)',\n",
       " 'Genres',\n",
       " 'Gwoyeu Romatzyh',\n",
       " 'Hangul',\n",
       " 'Hanyu Pinyin',\n",
       " 'Headquarters',\n",
       " 'Hebrew',\n",
       " 'Height',\n",
       " 'Hepburn',\n",
       " 'Hokkien POJ',\n",
       " 'IPA',\n",
       " 'ISBN',\n",
       " 'Illustrator',\n",
       " 'Industry',\n",
       " 'Instruments',\n",
       " 'Japanese',\n",
       " 'Jyutping',\n",
       " 'Key people',\n",
       " 'LC Class',\n",
       " 'Label',\n",
       " 'Labels',\n",
       " 'Language',\n",
       " 'Length',\n",
       " 'Literal meaning',\n",
       " 'Literally',\n",
       " 'Mandarin',\n",
       " 'McCune–Reischauer',\n",
       " 'Media type',\n",
       " 'Mode(s)',\n",
       " 'Music',\n",
       " 'Music by',\n",
       " 'Name',\n",
       " 'Narrated by',\n",
       " 'Nationality',\n",
       " 'No. of episodes',\n",
       " 'No. of seasons',\n",
       " 'Novel(s)',\n",
       " 'Number of employees',\n",
       " 'OCLC',\n",
       " 'Occupation',\n",
       " 'Opening date',\n",
       " 'Opening theme',\n",
       " 'Operating income',\n",
       " 'Original language',\n",
       " 'Original language(s)',\n",
       " 'Original network',\n",
       " 'Original release',\n",
       " 'Original title',\n",
       " 'Original work',\n",
       " 'Other names',\n",
       " 'Owner',\n",
       " 'Pages',\n",
       " 'Parent',\n",
       " 'Parent(s)',\n",
       " 'Picture format',\n",
       " 'Place premiered',\n",
       " 'Platform(s)',\n",
       " 'Polish',\n",
       " 'Portrayed by',\n",
       " 'Preceded by',\n",
       " 'Predecessor',\n",
       " 'Produced by',\n",
       " 'Producer',\n",
       " 'Producer(s)',\n",
       " 'Production company',\n",
       " 'Production company(s)',\n",
       " 'Production location(s)',\n",
       " 'Productioncompanies ',\n",
       " 'Productioncompany ',\n",
       " 'Products',\n",
       " 'Programmer(s)',\n",
       " 'Publication date',\n",
       " 'Published',\n",
       " 'Published in English',\n",
       " 'Publisher',\n",
       " 'Publisher(s)',\n",
       " 'Recorded',\n",
       " 'Relatives',\n",
       " 'Release',\n",
       " 'Release date',\n",
       " 'Release(s)',\n",
       " 'Released',\n",
       " 'Replaced',\n",
       " 'Replaced by',\n",
       " 'Resting place',\n",
       " 'Revenue',\n",
       " 'Revised Romanization',\n",
       " 'Romanized',\n",
       " 'Running time',\n",
       " 'Russian',\n",
       " 'Screen story by',\n",
       " 'Screenplay by',\n",
       " 'Seasons',\n",
       " 'Series',\n",
       " 'Services',\n",
       " 'Set in',\n",
       " 'Setting',\n",
       " 'Simplified',\n",
       " 'Simplified Chinese',\n",
       " 'Species',\n",
       " 'Spouse(s)',\n",
       " 'Starring',\n",
       " 'Status',\n",
       " 'Story by',\n",
       " 'Subject',\n",
       " 'Subsidiaries',\n",
       " 'Suggested by',\n",
       " 'Television series',\n",
       " 'Text',\n",
       " 'Theme music composer',\n",
       " 'Total assets',\n",
       " 'Traditional',\n",
       " 'Traditional Chinese',\n",
       " 'Transcriptions',\n",
       " 'Type',\n",
       " 'Venue',\n",
       " 'Voices of',\n",
       " 'Wade–Giles',\n",
       " 'Website',\n",
       " 'Writer(s)',\n",
       " 'Written by',\n",
       " 'Yale Romanization',\n",
       " 'Years active',\n",
       " 'Yiddish',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Make an empty dict to hold all of the alternative titles.\n",
    "def clean_movie(movie):\n",
    "    movie = dict(movie) \n",
    "    \n",
    "    #create a non-destructive copy\n",
    "    alt_titles = {}\n",
    "    \n",
    "    # Loop through a list of all alternative title keys\n",
    "    # combine alternate titles into one list\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",
    "        \n",
    "        # Check if the current key exists in the movie object.\n",
    "        if key in movie:\n",
    "            \n",
    "            # If so, remove the key-value pair and add to the alternative titles dictionary.\n",
    "            alt_titles[key] = movie[key]\n",
    "            movie.pop(key)\n",
    "            \n",
    "    # After looping through every key, add the alternative titles dict to the movie object.\n",
    "    if len(alt_titles) > 0:\n",
    "        movie['alt_titles'] = alt_titles\n",
    "      \n",
    "    # merge column names\n",
    "    def change_column_name(old_name, new_name):\n",
    "        if old_name in movie:\n",
    "            movie[new_name] = movie.pop(old_name)\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": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Animation by',\n",
       " 'Audio format',\n",
       " 'Based on',\n",
       " 'Box office',\n",
       " 'Budget',\n",
       " 'Cinematography',\n",
       " 'Color process',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Created by',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Executive producer(s)',\n",
       " 'Followed by',\n",
       " 'Genre',\n",
       " 'Label',\n",
       " 'Language',\n",
       " 'Narrated by',\n",
       " 'Original language(s)',\n",
       " 'Original network',\n",
       " 'Picture format',\n",
       " 'Preceded by',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Production location(s)',\n",
       " 'Recorded',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Starring',\n",
       " 'Suggested by',\n",
       " 'Venue',\n",
       " 'Voices of',\n",
       " 'Writer(s)',\n",
       " 'alt_titles',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a list of cleaned movies with a list comprehension\n",
    "clean_movies = [clean_movie(movie) for movie in wiki_movies]\n",
    "\n",
    "# Create a DataFrame from clean_movies and print the columns as a list\n",
    "wiki_movies_df = pd.DataFrame(clean_movies)\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7076\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "# Extract movie IDs and add them to a new column in the DataFrame\n",
    "wiki_movies_df['imdb_id'] = wiki_movies_df['imdb_link'].str.extract(r'(tt\\d{7})')\n",
    "print(len(wiki_movies_df))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7033\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Narrated by</th>\n",
       "      <th>Cinematography</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Running time</th>\n",
       "      <th>...</th>\n",
       "      <th>Created by</th>\n",
       "      <th>Preceded by</th>\n",
       "      <th>Suggested by</th>\n",
       "      <th>alt_titles</th>\n",
       "      <th>Recorded</th>\n",
       "      <th>Venue</th>\n",
       "      <th>Label</th>\n",
       "      <th>Animation by</th>\n",
       "      <th>Color process</th>\n",
       "      <th>imdb_id</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>Andrew \"Dice\" Clay</td>\n",
       "      <td>Oliver Wood</td>\n",
       "      <td>[July 11, 1990, (, 1990-07-11, )]</td>\n",
       "      <td>102 minutes</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tt0098987</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>NaN</td>\n",
       "      <td>Mark Plummer</td>\n",
       "      <td>[May 17, 1990, (, 1990-05-17, ), (Cannes Film ...</td>\n",
       "      <td>114 minutes</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tt0098994</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>NaN</td>\n",
       "      <td>Roger Deakins</td>\n",
       "      <td>[August 10, 1990, (, 1990-08-10, )]</td>\n",
       "      <td>113 minutes</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tt0099005</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>NaN</td>\n",
       "      <td>Carlo Di Palma</td>\n",
       "      <td>[December 25, 1990, (, 1990-12-25, )]</td>\n",
       "      <td>106 minutes</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tt0099012</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>NaN</td>\n",
       "      <td>Russell Boyd</td>\n",
       "      <td>December 19, 1990</td>\n",
       "      <td>95 minutes</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tt0099018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 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         Narrated by  \\\n",
       "0  [Andrew Dice Clay, Wayne Newton, Priscilla Pre...  Andrew \"Dice\" Clay   \n",
       "1  [Jason Patric, Rachel Ward, Bruce Dern, George...                 NaN   \n",
       "2  [Mel Gibson, Robert Downey Jr., Nancy Travis, ...                 NaN   \n",
       "3  [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...                 NaN   \n",
       "4        [Paul Hogan, Elias Koteas, Linda Kozlowski]                 NaN   \n",
       "\n",
       "   Cinematography                                       Release date  \\\n",
       "0     Oliver Wood                  [July 11, 1990, (, 1990-07-11, )]   \n",
       "1    Mark Plummer  [May 17, 1990, (, 1990-05-17, ), (Cannes Film ...   \n",
       "2   Roger Deakins                [August 10, 1990, (, 1990-08-10, )]   \n",
       "3  Carlo Di Palma              [December 25, 1990, (, 1990-12-25, )]   \n",
       "4    Russell Boyd                                  December 19, 1990   \n",
       "\n",
       "  Running time  ... Created by Preceded by Suggested by alt_titles Recorded  \\\n",
       "0  102 minutes  ...        NaN         NaN          NaN        NaN      NaN   \n",
       "1  114 minutes  ...        NaN         NaN          NaN        NaN      NaN   \n",
       "2  113 minutes  ...        NaN         NaN          NaN        NaN      NaN   \n",
       "3  106 minutes  ...        NaN         NaN          NaN        NaN      NaN   \n",
       "4   95 minutes  ...        NaN         NaN          NaN        NaN      NaN   \n",
       "\n",
       "  Venue Label Animation by Color process    imdb_id  \n",
       "0   NaN   NaN          NaN           NaN  tt0098987  \n",
       "1   NaN   NaN          NaN           NaN  tt0098994  \n",
       "2   NaN   NaN          NaN           NaN  tt0099005  \n",
       "3   NaN   NaN          NaN           NaN  tt0099012  \n",
       "4   NaN   NaN          NaN           NaN  tt0099018  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop any duplicates of movie IDs\n",
    "wiki_movies_df.drop_duplicates(subset='imdb_id', inplace=True)\n",
    "print(len(wiki_movies_df))\n",
    "wiki_movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['url', 0],\n",
       " ['year', 0],\n",
       " ['imdb_link', 0],\n",
       " ['title', 1],\n",
       " ['Based on', 4852],\n",
       " ['Starring', 184],\n",
       " ['Narrated by', 6752],\n",
       " ['Cinematography', 691],\n",
       " ['Release date', 32],\n",
       " ['Running time', 139],\n",
       " ['Country', 236],\n",
       " ['Language', 244],\n",
       " ['Budget', 2295],\n",
       " ['Box office', 1548],\n",
       " ['Director', 0],\n",
       " ['Distributor', 357],\n",
       " ['Editor(s)', 548],\n",
       " ['Composer(s)', 518],\n",
       " ['Producer(s)', 202],\n",
       " ['Production company(s)', 1678],\n",
       " ['Writer(s)', 199],\n",
       " ['Genre', 6923],\n",
       " ['Original language(s)', 6875],\n",
       " ['Original network', 6908],\n",
       " ['Executive producer(s)', 6936],\n",
       " ['Production location(s)', 6986],\n",
       " ['Picture format', 6969],\n",
       " ['Audio format', 6972],\n",
       " ['Voices of', 7031],\n",
       " ['Followed by', 7024],\n",
       " ['Created by', 7023],\n",
       " ['Preceded by', 7023],\n",
       " ['Suggested by', 7032],\n",
       " ['alt_titles', 7012],\n",
       " ['Recorded', 7031],\n",
       " ['Venue', 7032],\n",
       " ['Label', 7031],\n",
       " ['Animation by', 7031],\n",
       " ['Color process', 7032],\n",
       " ['imdb_id', 0]]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the count of null values for each column\n",
    "[[column,wiki_movies_df[column].isnull().sum()] for column in wiki_movies_df.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>Running time</th>\n",
       "      <th>Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Budget</th>\n",
       "      <th>Box office</th>\n",
       "      <th>Director</th>\n",
       "      <th>Distributor</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",
       "    </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>102 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$20 million</td>\n",
       "      <td>$21.4 million</td>\n",
       "      <td>Renny Harlin</td>\n",
       "      <td>20th Century Fox</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",
       "    </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>114 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$6 million</td>\n",
       "      <td>$2.7 million</td>\n",
       "      <td>James Foley</td>\n",
       "      <td>Avenue Pictures</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",
       "    </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>113 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$35 million</td>\n",
       "      <td>$57,718,089</td>\n",
       "      <td>Roger Spottiswoode</td>\n",
       "      <td>TriStar Pictures</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",
       "    </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>106 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$12 million</td>\n",
       "      <td>$7,331,647</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>Orion Pictures</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 21 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",
       "\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",
       "\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",
       "\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",
       "\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",
       "\n",
       "         Country  ...       Budget     Box office            Director  \\\n",
       "0  United States  ...  $20 million  $21.4 million        Renny Harlin   \n",
       "1  United States  ...   $6 million   $2.7 million         James Foley   \n",
       "2  United States  ...  $35 million    $57,718,089  Roger Spottiswoode   \n",
       "3  United States  ...  $12 million     $7,331,647         Woody Allen   \n",
       "\n",
       "        Distributor                       Editor(s)              Composer(s)  \\\n",
       "0  20th Century Fox                 Michael Tronick  [Cliff Eidelman, Yello]   \n",
       "1   Avenue Pictures                 Howard E. Smith            Maurice Jarre   \n",
       "2  TriStar Pictures  [John Bloom, Lois Freeman-Fox]            Charles Gross   \n",
       "3    Orion Pictures                  Susan E. Morse                      NaN   \n",
       "\n",
       "                   Producer(s)                  Production company(s)  \\\n",
       "0   [Steve Perry, Joel Silver]                        Silver Pictures   \n",
       "1  [Ric Kidney, Robert Redlin]                        Avenue Pictures   \n",
       "2               Daniel Melnick  [Carolco Pictures, IndieProd Company]   \n",
       "3              Robert Greenhut                                    NaN   \n",
       "\n",
       "                      Writer(s)    imdb_id  \n",
       "0   [David Arnott, James Cappe]  tt0098987  \n",
       "1  [James Foley, Robert Redlin]  tt0098994  \n",
       "2    [John Eskow, Richard Rush]  tt0099005  \n",
       "3                   Woody Allen  tt0099012  \n",
       "\n",
       "[4 rows x 21 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a list of columns that have less than 90% null values\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",
    "\n",
    "# select the columns from the wiki movies DataFrame\n",
    "wiki_movies_df = wiki_movies_df[wiki_columns_to_keep]\n",
    "\n",
    "len(wiki_movies_df)\n",
    "wiki_movies_df.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5485"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a data series that drops missing values \n",
    "box_office = wiki_movies_df['Box office'].dropna()\n",
    "len(box_office)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34                           [US$, 4,212,828]\n",
       "54      [$6,698,361 (, United States, ), [2]]\n",
       "74                    [$6,488,144, (US), [1]]\n",
       "126                [US$1,531,489, (domestic)]\n",
       "130                          [US$, 4,803,039]\n",
       "                        ...                  \n",
       "6980               [$99.6, million, [4], [5]]\n",
       "6994                   [$365.6, million, [1]]\n",
       "6995                         [$53.8, million]\n",
       "7015                     [$435, million, [7]]\n",
       "7048                   [$529.3, million, [4]]\n",
       "Name: Box office, Length: 135, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a is_not_a_string function\n",
    "def is_not_a_string(x):\n",
    "    return type(x) != str\n",
    "box_office[box_office.map(is_not_a_string)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34                           [US$, 4,212,828]\n",
       "54      [$6,698,361 (, United States, ), [2]]\n",
       "74                    [$6,488,144, (US), [1]]\n",
       "126                [US$1,531,489, (domestic)]\n",
       "130                          [US$, 4,803,039]\n",
       "                        ...                  \n",
       "6980               [$99.6, million, [4], [5]]\n",
       "6994                   [$365.6, million, [1]]\n",
       "6995                         [$53.8, million]\n",
       "7015                     [$435, million, [7]]\n",
       "7048                   [$529.3, million, [4]]\n",
       "Name: Box office, Length: 135, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create lambda function to identify values that are not a string\n",
    "box_office[box_office.map(lambda x: type(x) != str)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          $21.4 million\n",
       "1           $2.7 million\n",
       "2            $57,718,089\n",
       "3             $7,331,647\n",
       "4       $6,939,946 (USA)\n",
       "              ...       \n",
       "7070       $19.4 million\n",
       "7071       $41.9 million\n",
       "7072       $76.1 million\n",
       "7073       $38.4 million\n",
       "7074        $5.5 million\n",
       "Name: Box office, Length: 5485, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "box_office = box_office.apply(lambda x: ' '.join(x) if type(x) == list else x)\n",
    "box_office"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a variable (form_one) that contains the form $123.4 million/billion\n",
    "form_one = r'\\$\\d+\\.?\\d*\\s*[mb]illion'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3896"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count how many box office values match form_one\n",
    "box_office.str.contains(form_one, flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1544"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a variable (form_two) that contains the form $123,456,789\n",
    "form_two = r'\\$\\d{1,3}(?:,\\d{3})+'\n",
    "\n",
    "# count how many box office values match form_two\n",
    "box_office.str.contains(form_two, flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34                         US$ 4,212,828\n",
       "79                              $335.000\n",
       "110                   $4.35-4.37 million\n",
       "130                        US$ 4,803,039\n",
       "600                           $5000 (US)\n",
       "731                         $ 11,146,270\n",
       "957                             $ 50,004\n",
       "1070                          35,254,617\n",
       "1147    $ 407,618 (U.S.) (sub-total) [1]\n",
       "1446                        $ 11,829,959\n",
       "1480                          £3 million\n",
       "1611                            $520.000\n",
       "1865                        ¥1.1 billion\n",
       "2032                                 N/A\n",
       "2091                                $309\n",
       "2130               US$ 171.8 million [9]\n",
       "2257                   US$ 3,395,581 [1]\n",
       "2263            $ 1,223,034 ( domestic )\n",
       "2347                            $282.175\n",
       "2638            $ 104,883 (US sub-total)\n",
       "2665         926,423 admissions (France)\n",
       "2697      $ 1.7 million (US) (sub-total)\n",
       "2823                            $414.000\n",
       "2924                            $621.000\n",
       "3088           $32 [2] –33.1 million [1]\n",
       "3631                                 TBA\n",
       "3859                  $38.9–40.3 million\n",
       "3879            CN¥3.650 million (China)\n",
       "4116                          £7,385,434\n",
       "4123                            $161.000\n",
       "4261                  $20.7–23.9 million\n",
       "4306                              $20-30\n",
       "4492                        $47.7 millon\n",
       "4561             $45.2k (only in Turkey)\n",
       "4662                USD$ 8.2 million [2]\n",
       "5362                   $ 142 million [3]\n",
       "5447                               £2.56\n",
       "5784                            413 733$\n",
       "6013                             Unknown\n",
       "6145                  $17.5–18.4 million\n",
       "6234                  $41.8–41.9 million\n",
       "6369                               $111k\n",
       "6370                                $588\n",
       "6593                      less than $372\n",
       "6829                    $ 41 million [3]\n",
       "6843                             8 crore\n",
       "6904                         $6.9 millon\n",
       "Name: Box office, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a list of values that match the variables\n",
    "matches_form_one = box_office.str.contains(form_one, flags=re.IGNORECASE)\n",
    "matches_form_two = box_office.str.contains(form_two, flags=re.IGNORECASE)\n",
    "\n",
    "#return box office values that aren't described by either form_one or form_two\n",
    "box_office[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parse_dollars(s):\n",
    "    # if s is not a string, return NaN\n",
    "    if type(s) != str:\n",
    "        return np.nan\n",
    "    \n",
    "    # if input is of the form $###.# million\n",
    "    if re.match(r'\\$\\s*\\d+\\.?\\d*\\s*milli?on', s, flags=re.IGNORECASE):\n",
    "        \n",
    "        # remove dollar sign and \" million\"\n",
    "        s = re.sub('\\$|\\s|[a-zA-Z]','', s)\n",
    "        \n",
    "        # convert to float and multiply by a million\n",
    "        value = float(s) * 10**6\n",
    "        \n",
    "        # return value\n",
    "        return value\n",
    "    \n",
    "    # if input is of the form $###.# billion\n",
    "    elif re.match(r'\\$\\s*\\d+\\.?\\d*\\s*billi?on', s, flags=re.IGNORECASE):\n",
    "        \n",
    "        # remove dollar sign and \" billion\"\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 $###,###,###\n",
    "    elif re.match(r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)', s, flags=re.IGNORECASE):\n",
    "        \n",
    "        # remove dollar sign and commas\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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Based on',\n",
       " 'Box office',\n",
       " 'Budget',\n",
       " 'Cinematography',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Language',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Starring',\n",
       " 'Writer(s)',\n",
       " 'box_office',\n",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# From the wiki movies df, extract the form_one and form_two matches from the box_office column and parse the values into numeric values\n",
    "wiki_movies_df['box_office'] = box_office.str.extract(f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)\n",
    "\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       21400000.0\n",
       "1        2700000.0\n",
       "2       57718089.0\n",
       "3        7331647.0\n",
       "4        6939946.0\n",
       "           ...    \n",
       "7071    41900000.0\n",
       "7072    76100000.0\n",
       "7073    38400000.0\n",
       "7074     5500000.0\n",
       "7075           NaN\n",
       "Name: box_office, Length: 7033, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df['box_office']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the orgininal Box office column\n",
    "wiki_movies_df.drop('Box office', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a budget variable\n",
    "budget = wiki_movies_df['Budget'].dropna()\n",
    "\n",
    "# Convert any lists to strings:\n",
    "budget = budget.map(lambda x: ' '.join(x) if type(x) == list else x)\n",
    "\n",
    "# remove any values between a dollar sign and a hyphen (for budgets given in ranges):\n",
    "budget = budget.str.replace(r'\\$.*[-—–](?![a-z])', '$', regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "135                  USD$ 9 million\n",
       "136                         Unknown\n",
       "204     60 million Norwegian Kroner\n",
       "255                        $ 80,000\n",
       "351              US$ 65 million [1]\n",
       "                   ...             \n",
       "6821                  £12.9 million\n",
       "6843                      3.5 crore\n",
       "6895                        919,000\n",
       "6904                    $8.6 millon\n",
       "7070                   €4.3 million\n",
       "Name: Budget, Length: 76, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a list of values that match the variables for budget\n",
    "matches_form_one = budget.str.contains(form_one, flags=re.IGNORECASE)\n",
    "matches_form_two = budget.str.contains(form_two, flags=re.IGNORECASE)\n",
    "\n",
    "# return budget values that aren't described by either form_one or form_two\n",
    "budget[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "135                  USD$ 9 million\n",
       "136                         Unknown\n",
       "204     60 million Norwegian Kroner\n",
       "255                        $ 80,000\n",
       "351                 US$ 65 million \n",
       "                   ...             \n",
       "6821                  £12.9 million\n",
       "6843                      3.5 crore\n",
       "6895                        919,000\n",
       "6904                    $8.6 millon\n",
       "7070                   €4.3 million\n",
       "Name: Budget, Length: 76, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove the citation references\n",
    "\n",
    "budget = budget.str.replace(r'\\[\\d+\\]\\s*', '')\n",
    "budget[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Based on',\n",
       " 'Budget',\n",
       " 'Cinematography',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Language',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Starring',\n",
       " 'Writer(s)',\n",
       " 'box_office',\n",
       " 'budget',\n",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# From the wiki movies df, extract the form_one and form_two matches from the budget column and parse the values into numeric values\n",
    "wiki_movies_df['budget'] = budget.str.extract(f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)\n",
    "\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the orgininal budget column\n",
    "wiki_movies_df.drop('Budget', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Based on',\n",
       " 'Cinematography',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Language',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Starring',\n",
       " 'Writer(s)',\n",
       " 'box_office',\n",
       " 'budget',\n",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make a variable that holds the non-null values of Release date in the DataFrame, converting lists to strings:\n",
    "\n",
    "release_date = wiki_movies_df['Release date'].dropna().apply(lambda x: ' '.join(x) if type(x) == list else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list of formats that match the variables for release date\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.[123]\\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}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>July 11, 1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>May 17, 1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>August 10, 1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>December 25, 1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>December 19, 1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7071</th>\n",
       "      <td>December 25, 2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7072</th>\n",
       "      <td>December 11, 2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7073</th>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7074</th>\n",
       "      <td>August 31, 2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7075</th>\n",
       "      <td>December 2018</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7001 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      0\n",
       "0         July 11, 1990\n",
       "1          May 17, 1990\n",
       "2       August 10, 1990\n",
       "3     December 25, 1990\n",
       "4     December 19, 1990\n",
       "...                 ...\n",
       "7071  December 25, 2018\n",
       "7072  December 11, 2018\n",
       "7073               2018\n",
       "7074    August 31, 2018\n",
       "7075      December 2018\n",
       "\n",
       "[7001 rows x 1 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the dates\n",
    "release_date.str.extract(f'({date_form_one}|{date_form_two}|{date_form_three}|{date_form_four})', flags=re.IGNORECASE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the release date\n",
    "wiki_movies_df['release_date'] = pd.to_datetime(release_date.str.extract(f'({date_form_one}|{date_form_two}|{date_form_three}|{date_form_four})')[0], infer_datetime_format=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                 102 minutes\n",
       "1                                 114 minutes\n",
       "2                                 113 minutes\n",
       "3                                 106 minutes\n",
       "4                                  95 minutes\n",
       "                        ...                  \n",
       "7071                               90 minutes\n",
       "7072                              132 minutes\n",
       "7073                              120 minutes\n",
       "7074                              123 minutes\n",
       "7075    Variable; 90 minutes for default path\n",
       "Name: Running time, Length: 6894, dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a variable that holds the non-null values of running time in the DataFrame, converting lists to strings:\n",
    "\n",
    "running_time = wiki_movies_df['Running time'].dropna().apply(lambda x: ' '.join(x) if type(x) == list else x)\n",
    "running_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6528"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how many running times match the running_time format, i.e. 100 minutes.\n",
    "\n",
    "running_time.str.contains(r'^\\d*\\s*minutes$', flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9                                                 102 min\n",
       "26                                                 93 min\n",
       "28                                                32 min.\n",
       "34                                                101 min\n",
       "35                                                 97 min\n",
       "                              ...                        \n",
       "6500       114 minutes [1] 120 minutes (extended edition)\n",
       "6643                                             104 mins\n",
       "6709    90 minutes (theatrical) [1] 91 minutes (unrate...\n",
       "7057    108 minutes (Original cut) 98 minutes (UK cut)...\n",
       "7075                Variable; 90 minutes for default path\n",
       "Name: Running time, Length: 366, dtype: object"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the other entires that do not match the running_time format.\n",
    "running_time[running_time.str.contains(r'^\\d*\\s*minutes$', flags=re.IGNORECASE) != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6877"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count the number of other entires that do not match the running_time format.\n",
    "running_time.str.contains(r'^\\d*\\s*m', flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "668                     UK:84 min (DVD version) US:86 min\n",
       "727                         78-102 min (depending on cut)\n",
       "840                       Varies (79 [3] –84 [1] minutes)\n",
       "1347                                              25 : 03\n",
       "1443    United States: 77 minutes Argentina: 94 minute...\n",
       "1499                                            1hr 35min\n",
       "1551                                               varies\n",
       "1774                    Netherlands:96 min, Canada:95 min\n",
       "1777                                       approx. 14 min\n",
       "2273                                           1 h 43 min\n",
       "2993                                               1h 48m\n",
       "3925                                              4 hours\n",
       "4425    US domestic version: 86 minutes Original versi...\n",
       "4967    Theatrical cut: 97 minutes Unrated cut: 107 mi...\n",
       "5424                    115 [1] /123 [2] /128 [3] minutes\n",
       "5447                                    1 hour 32 minutes\n",
       "7075                Variable; 90 minutes for default path\n",
       "Name: Running time, dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the remaining entries\n",
    "running_time[running_time.str.contains(r'^\\d*\\s*m', flags=re.IGNORECASE) != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1347    25 : 03\n",
       "1551     varies\n",
       "3925    4 hours\n",
       "Name: Running time, dtype: object"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# capture some of the remaining entries by relaxing the condition\n",
    "# that the pattern must start at the beginning of the string.\n",
    "running_time[running_time.str.contains(r'\\d*\\s*m', flags=re.IGNORECASE) != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract the digits for running time\n",
    "running_time_extract = running_time.str.extract(r'(\\d+)\\s*ho?u?r?s?\\s*(\\d*)|(\\d+)\\s*m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert the running time data to numeric values\n",
    "running_time_extract = running_time_extract.apply(lambda col: pd.to_numeric(col, errors='coerce')).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the running time data to the dataframe\n",
    "wiki_movies_df['running_time'] = running_time_extract.apply(lambda row: row[0]*60 + row[1] if row[2] == 0 else row[2], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop Running time from the dataset with the following code:\n",
    "\n",
    "wiki_movies_df.drop('Running time', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Based on',\n",
       " 'Cinematography',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Language',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Release date',\n",
       " 'Starring',\n",
       " 'Writer(s)',\n",
       " 'box_office',\n",
       " 'budget',\n",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'release_date',\n",
       " 'running_time',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "adult                     object\n",
       "belongs_to_collection     object\n",
       "budget                    object\n",
       "genres                    object\n",
       "homepage                  object\n",
       "id                        object\n",
       "imdb_id                   object\n",
       "original_language         object\n",
       "original_title            object\n",
       "overview                  object\n",
       "popularity                object\n",
       "poster_path               object\n",
       "production_companies      object\n",
       "production_countries      object\n",
       "release_date              object\n",
       "revenue                  float64\n",
       "runtime                  float64\n",
       "spoken_languages          object\n",
       "status                    object\n",
       "tagline                   object\n",
       "title                     object\n",
       "video                     object\n",
       "vote_average             float64\n",
       "vote_count               float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check that all of the columns came in as the correct data types.\n",
    "\n",
    "kaggle_metadata.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False                                                                                                                             45454\n",
       "True                                                                                                                                  9\n",
       " Rune Balot goes to a casino connected to the October corporation to try to wrap up her case once and for all.                        1\n",
       " - Written by Ørnås                                                                                                                   1\n",
       " Avalanche Sharks tells the story of a bikini contest that turns into a horrifying affair when it is hit by a shark avalanche.        1\n",
       "Name: adult, dtype: int64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check that all the values are either True or False for the \"adult\" and \"video\" columns.\n",
    "\n",
    "kaggle_metadata['adult'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>adult</th>\n",
       "      <th>belongs_to_collection</th>\n",
       "      <th>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>...</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19730</th>\n",
       "      <td>- Written by Ørnås</td>\n",
       "      <td>0.065736</td>\n",
       "      <td>/ff9qCepilowshEtG2GYWwzt2bs4.jpg</td>\n",
       "      <td>[{'name': 'Carousel Productions', 'id': 11176}...</td>\n",
       "      <td>[{'iso_3166_1': 'CA', 'name': 'Canada'}, {'iso...</td>\n",
       "      <td>1997-08-20</td>\n",
       "      <td>0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>...</td>\n",
       "      <td>1</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29503</th>\n",
       "      <td>Rune Balot goes to a casino connected to the ...</td>\n",
       "      <td>1.931659</td>\n",
       "      <td>/zV8bHuSL6WXoD6FWogP9j4x80bL.jpg</td>\n",
       "      <td>[{'name': 'Aniplex', 'id': 2883}, {'name': 'Go...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>2012-09-29</td>\n",
       "      <td>0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>[{'iso_639_1': 'ja', 'name': '日本語'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>...</td>\n",
       "      <td>12</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35587</th>\n",
       "      <td>Avalanche Sharks tells the story of a bikini ...</td>\n",
       "      <td>2.185485</td>\n",
       "      <td>/zaSf5OG7V8X8gqFvly88zDdRm46.jpg</td>\n",
       "      <td>[{'name': 'Odyssey Media', 'id': 17161}, {'nam...</td>\n",
       "      <td>[{'iso_3166_1': 'CA', 'name': 'Canada'}]</td>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>...</td>\n",
       "      <td>22</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   adult  \\\n",
       "19730                                 - Written by Ørnås   \n",
       "29503   Rune Balot goes to a casino connected to the ...   \n",
       "35587   Avalanche Sharks tells the story of a bikini ...   \n",
       "\n",
       "      belongs_to_collection                            budget  \\\n",
       "19730              0.065736  /ff9qCepilowshEtG2GYWwzt2bs4.jpg   \n",
       "29503              1.931659  /zV8bHuSL6WXoD6FWogP9j4x80bL.jpg   \n",
       "35587              2.185485  /zaSf5OG7V8X8gqFvly88zDdRm46.jpg   \n",
       "\n",
       "                                                  genres  \\\n",
       "19730  [{'name': 'Carousel Productions', 'id': 11176}...   \n",
       "29503  [{'name': 'Aniplex', 'id': 2883}, {'name': 'Go...   \n",
       "35587  [{'name': 'Odyssey Media', 'id': 17161}, {'nam...   \n",
       "\n",
       "                                                homepage          id imdb_id  \\\n",
       "19730  [{'iso_3166_1': 'CA', 'name': 'Canada'}, {'iso...  1997-08-20       0   \n",
       "29503  [{'iso_3166_1': 'US', 'name': 'United States o...  2012-09-29       0   \n",
       "35587           [{'iso_3166_1': 'CA', 'name': 'Canada'}]  2014-01-01       0   \n",
       "\n",
       "      original_language                            original_title  overview  \\\n",
       "19730             104.0  [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "29503              68.0      [{'iso_639_1': 'ja', 'name': '日本語'}]  Released   \n",
       "35587              82.0  [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "\n",
       "       ... release_date revenue runtime spoken_languages status  tagline  \\\n",
       "19730  ...            1     NaN     NaN              NaN    NaN      NaN   \n",
       "29503  ...           12     NaN     NaN              NaN    NaN      NaN   \n",
       "35587  ...           22     NaN     NaN              NaN    NaN      NaN   \n",
       "\n",
       "       title video vote_average vote_count  \n",
       "19730    NaN   NaN          NaN        NaN  \n",
       "29503    NaN   NaN          NaN        NaN  \n",
       "35587    NaN   NaN          NaN        NaN  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove bad data\n",
    "kaggle_metadata[~kaggle_metadata['adult'].isin(['True','False'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Keep rows where adult is 'False' and drop the adult column.\n",
    "kaggle_metadata = kaggle_metadata[kaggle_metadata['adult'] == 'False'].drop('adult',axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    45358\n",
       "True        93\n",
       "Name: video, dtype: int64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at the values of the video column:\n",
    "kaggle_metadata['video'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert the data tpe for the video column\n",
    "kaggle_metadata['video'] = kaggle_metadata['video'] == 'True'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert numeric columns to the proper datatype\n",
    "kaggle_metadata['budget'] = kaggle_metadata['budget'].astype(int)\n",
    "kaggle_metadata['id'] = pd.to_numeric(kaggle_metadata['id'], errors='raise')\n",
    "kaggle_metadata['popularity'] = pd.to_numeric(kaggle_metadata['popularity'], errors='raise')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert release date to datetime\n",
    "kaggle_metadata['release_date'] = pd.to_datetime(kaggle_metadata['release_date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 26024289 entries, 0 to 26024288\n",
      "Data columns (total 4 columns):\n",
      " #   Column     Non-Null Count     Dtype  \n",
      "---  ------     --------------     -----  \n",
      " 0   userId     26024289 non-null  int64  \n",
      " 1   movieId    26024289 non-null  int64  \n",
      " 2   rating     26024289 non-null  float64\n",
      " 3   timestamp  26024289 non-null  int64  \n",
      "dtypes: float64(1), int64(3)\n",
      "memory usage: 794.2 MB\n"
     ]
    }
   ],
   "source": [
    "# set the null_counts option to True\n",
    "ratings.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          2015-03-09 22:52:09\n",
       "1          2015-03-09 23:07:15\n",
       "2          2015-03-09 22:52:03\n",
       "3          2015-03-09 22:52:26\n",
       "4          2015-03-09 22:52:36\n",
       "                   ...        \n",
       "26024284   2009-10-31 23:26:04\n",
       "26024285   2009-10-31 23:33:52\n",
       "26024286   2009-10-31 23:29:24\n",
       "26024287   2009-11-01 00:06:30\n",
       "26024288   2009-10-31 23:30:58\n",
       "Name: timestamp, Length: 26024289, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the rating data to a datetime datatype\n",
    "pd.to_datetime(ratings['timestamp'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count          26,024,289.00\n",
       "mean                    3.53\n",
       "std                     1.07\n",
       "min                     0.50\n",
       "25%                     3.00\n",
       "50%                     3.50\n",
       "75%                     4.00\n",
       "max                     5.00\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ratings histogram\n",
    "pd.options.display.float_format = '{:20,.2f}'.format\n",
    "ratings['rating'].plot(kind='hist')\n",
    "\n",
    "# ratings stats\n",
    "ratings['rating'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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_wiki</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>release_date_kaggle</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title_kaggle</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</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>1990-07-11</td>\n",
       "      <td>20,423,389.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Kojak. Columbo. Dirty Harry. Wimps.</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>False</td>\n",
       "      <td>6.20</td>\n",
       "      <td>72.00</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>1990-08-24</td>\n",
       "      <td>0.00</td>\n",
       "      <td>114.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>All they risked was everything.</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>False</td>\n",
       "      <td>6.50</td>\n",
       "      <td>17.00</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>1990-08-10</td>\n",
       "      <td>33,461,269.00</td>\n",
       "      <td>112.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>The few. The proud. The totally insane.</td>\n",
       "      <td>Air America</td>\n",
       "      <td>False</td>\n",
       "      <td>5.30</td>\n",
       "      <td>146.00</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>1990-12-25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>102.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alice</td>\n",
       "      <td>False</td>\n",
       "      <td>6.30</td>\n",
       "      <td>57.00</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>1990-12-21</td>\n",
       "      <td>0.00</td>\n",
       "      <td>95.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Who does he think he is?</td>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>False</td>\n",
       "      <td>5.60</td>\n",
       "      <td>23.00</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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>https://en.wikipedia.org/wiki/A_Fantastic_Woman</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5639354/</td>\n",
       "      <td>A Fantastic Woman</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Daniela Vega, Francisco Reyes]</td>\n",
       "      <td>Benjamín Echazarreta</td>\n",
       "      <td>[12 February 2017, (, 2017-02-12, ), (, Berlin...</td>\n",
       "      <td>[Chile, Germany, Spain, United States, [2]]</td>\n",
       "      <td>Spanish</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>[{'iso_639_1': 'es', 'name': 'Español'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Fantastic Woman</td>\n",
       "      <td>False</td>\n",
       "      <td>7.20</td>\n",
       "      <td>13.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Permission_(film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5390066/</td>\n",
       "      <td>Permission</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Rebecca Hall, Dan Stevens, Morgan Spector, Fr...</td>\n",
       "      <td>Adam Bricker</td>\n",
       "      <td>[April 22, 2017, (, 2017-04-22, ), (, Tribeca ...</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-04-22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>96.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Permission</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Loveless_(film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt6304162/</td>\n",
       "      <td>Loveless</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Maryana Spivak, Aleksey Rozin, Matvey Novikov...</td>\n",
       "      <td>Mikhail Krichman</td>\n",
       "      <td>[18 May 2017, (, 2017-05-18, ), (, Cannes, ), ...</td>\n",
       "      <td>[Russia, France, Belgium, Germany, [3]]</td>\n",
       "      <td>Russian</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>128.00</td>\n",
       "      <td>[{'iso_639_1': 'ru', 'name': 'Pусский'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Loveless</td>\n",
       "      <td>False</td>\n",
       "      <td>7.80</td>\n",
       "      <td>26.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Gemini_(2017_film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5795086/</td>\n",
       "      <td>Gemini</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...</td>\n",
       "      <td>Andrew Reed</td>\n",
       "      <td>[March 12, 2017, (, 2017-03-12, ), (, SXSW, ),...</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-03-12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>92.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Post Production</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gemini</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6051</th>\n",
       "      <td>https://en.wikipedia.org/wiki/How_to_Talk_to_G...</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt3859310/</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>[\", How to Talk to Girls at Parties, \", by, Ne...</td>\n",
       "      <td>[Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...</td>\n",
       "      <td>Frank G. DeMarco</td>\n",
       "      <td>[May 21, 2017, (, 2017-05-21, ), (, Cannes, ),...</td>\n",
       "      <td>[United Kingdom, United States]</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-12-27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>102.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Some girls are out of this world.</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6052 rows × 44 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",
       "6047    https://en.wikipedia.org/wiki/A_Fantastic_Woman  2018   \n",
       "6048    https://en.wikipedia.org/wiki/Permission_(film)  2018   \n",
       "6049      https://en.wikipedia.org/wiki/Loveless_(film)  2018   \n",
       "6050   https://en.wikipedia.org/wiki/Gemini_(2017_film)  2018   \n",
       "6051  https://en.wikipedia.org/wiki/How_to_Talk_to_G...  2018   \n",
       "\n",
       "                                  imdb_link                       title_wiki  \\\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",
       "6047  https://www.imdb.com/title/tt5639354/                A Fantastic Woman   \n",
       "6048  https://www.imdb.com/title/tt5390066/                       Permission   \n",
       "6049  https://www.imdb.com/title/tt6304162/                         Loveless   \n",
       "6050  https://www.imdb.com/title/tt5795086/                           Gemini   \n",
       "6051  https://www.imdb.com/title/tt3859310/  How to Talk to Girls at Parties   \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",
       "6047                                                NaN   \n",
       "6048                                                NaN   \n",
       "6049                                                NaN   \n",
       "6050                                                NaN   \n",
       "6051  [\", How to Talk to Girls at Parties, \", by, Ne...   \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",
       "6047                    [Daniela Vega, Francisco Reyes]  Benjamín Echazarreta   \n",
       "6048  [Rebecca Hall, Dan Stevens, Morgan Spector, Fr...          Adam Bricker   \n",
       "6049  [Maryana Spivak, Aleksey Rozin, Matvey Novikov...      Mikhail Krichman   \n",
       "6050  [Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...           Andrew Reed   \n",
       "6051  [Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...      Frank G. DeMarco   \n",
       "\n",
       "                                           Release date  \\\n",
       "0                     [July 11, 1990, (, 1990-07-11, )]   \n",
       "1     [May 17, 1990, (, 1990-05-17, ), (Cannes Film ...   \n",
       "2                   [August 10, 1990, (, 1990-08-10, )]   \n",
       "3                 [December 25, 1990, (, 1990-12-25, )]   \n",
       "4                                     December 19, 1990   \n",
       "...                                                 ...   \n",
       "6047  [12 February 2017, (, 2017-02-12, ), (, Berlin...   \n",
       "6048  [April 22, 2017, (, 2017-04-22, ), (, Tribeca ...   \n",
       "6049  [18 May 2017, (, 2017-05-18, ), (, Cannes, ), ...   \n",
       "6050  [March 12, 2017, (, 2017-03-12, ), (, SXSW, ),...   \n",
       "6051  [May 21, 2017, (, 2017-05-21, ), (, Cannes, ),...   \n",
       "\n",
       "                                          Country        Language  ...  \\\n",
       "0                                   United States         English  ...   \n",
       "1                                   United States         English  ...   \n",
       "2                                   United States  [English, Lao]  ...   \n",
       "3                                   United States         English  ...   \n",
       "4                                              US         English  ...   \n",
       "...                                           ...             ...  ...   \n",
       "6047  [Chile, Germany, Spain, United States, [2]]         Spanish  ...   \n",
       "6048                                United States         English  ...   \n",
       "6049      [Russia, France, Belgium, Germany, [3]]         Russian  ...   \n",
       "6050                                United States         English  ...   \n",
       "6051              [United Kingdom, United States]         English  ...   \n",
       "\n",
       "     release_date_kaggle              revenue              runtime  \\\n",
       "0             1990-07-11        20,423,389.00               104.00   \n",
       "1             1990-08-24                 0.00               114.00   \n",
       "2             1990-08-10        33,461,269.00               112.00   \n",
       "3             1990-12-25                 0.00               102.00   \n",
       "4             1990-12-21                 0.00                95.00   \n",
       "...                  ...                  ...                  ...   \n",
       "6047          2017-04-06                 0.00               104.00   \n",
       "6048          2017-04-22                 0.00                96.00   \n",
       "6049          2017-06-01                 0.00               128.00   \n",
       "6050          2017-03-12                 0.00                92.00   \n",
       "6051          2017-12-27                 0.00               102.00   \n",
       "\n",
       "                                       spoken_languages           status  \\\n",
       "0              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "1              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "2     [{'iso_639_1': 'en', 'name': 'English'}, {'iso...         Released   \n",
       "3              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "4              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "...                                                 ...              ...   \n",
       "6047           [{'iso_639_1': 'es', 'name': 'Español'}]         Released   \n",
       "6048           [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "6049           [{'iso_639_1': 'ru', 'name': 'Pусский'}]         Released   \n",
       "6050           [{'iso_639_1': 'en', 'name': 'English'}]  Post Production   \n",
       "6051           [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "\n",
       "                                      tagline  \\\n",
       "0         Kojak. Columbo. Dirty Harry. Wimps.   \n",
       "1             All they risked was everything.   \n",
       "2     The few. The proud. The totally insane.   \n",
       "3                                         NaN   \n",
       "4                    Who does he think he is?   \n",
       "...                                       ...   \n",
       "6047                                      NaN   \n",
       "6048                                      NaN   \n",
       "6049                                      NaN   \n",
       "6050                                      NaN   \n",
       "6051        Some girls are out of this world.   \n",
       "\n",
       "                         title_kaggle  video         vote_average  \\\n",
       "0     The Adventures of Ford Fairlane  False                 6.20   \n",
       "1                After Dark, My Sweet  False                 6.50   \n",
       "2                         Air America  False                 5.30   \n",
       "3                               Alice  False                 6.30   \n",
       "4                     Almost an Angel  False                 5.60   \n",
       "...                               ...    ...                  ...   \n",
       "6047                A Fantastic Woman  False                 7.20   \n",
       "6048                       Permission  False                 0.00   \n",
       "6049                         Loveless  False                 7.80   \n",
       "6050                           Gemini  False                 0.00   \n",
       "6051  How to Talk to Girls at Parties  False                 0.00   \n",
       "\n",
       "               vote_count  \n",
       "0                   72.00  \n",
       "1                   17.00  \n",
       "2                  146.00  \n",
       "3                   57.00  \n",
       "4                   23.00  \n",
       "...                   ...  \n",
       "6047                13.00  \n",
       "6048                 1.00  \n",
       "6049                26.00  \n",
       "6050                 0.00  \n",
       "6051                10.00  \n",
       "\n",
       "[6052 rows x 44 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# identify redundant columns\n",
    "movies_df = pd.merge(wiki_movies_df, kaggle_metadata, on='imdb_id', suffixes=['_wiki','_kaggle'])\n",
    "movies_df"
   ]
  },
  {
   "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",
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       "    }\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>title_wiki</th>\n",
       "      <th>title_kaggle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Air America</td>\n",
       "      <td>Air America</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alice</td>\n",
       "      <td>Alice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>Almost an Angel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>A Fantastic Woman</td>\n",
       "      <td>A Fantastic Woman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>Permission</td>\n",
       "      <td>Permission</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>Loveless</td>\n",
       "      <td>Loveless</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>Gemini</td>\n",
       "      <td>Gemini</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6051</th>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6052 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           title_wiki                     title_kaggle\n",
       "0     The Adventures of Ford Fairlane  The Adventures of Ford Fairlane\n",
       "1                After Dark, My Sweet             After Dark, My Sweet\n",
       "2                         Air America                      Air America\n",
       "3                               Alice                            Alice\n",
       "4                     Almost an Angel                  Almost an Angel\n",
       "...                               ...                              ...\n",
       "6047                A Fantastic Woman                A Fantastic Woman\n",
       "6048                       Permission                       Permission\n",
       "6049                         Loveless                         Loveless\n",
       "6050                           Gemini                           Gemini\n",
       "6051  How to Talk to Girls at Parties  How to Talk to Girls at Parties\n",
       "\n",
       "[6052 rows x 2 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect the titles from the wiki and kaggle data\n",
    "movies_df[['title_wiki','title_kaggle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title_wiki</th>\n",
       "      <th>title_kaggle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>China Cry</td>\n",
       "      <td>China Cry: A True Story</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Daddy's Dyin' ...Who's Got the Will?</td>\n",
       "      <td>Daddy's Dyin'... Who's Got the Will?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>The Dark Side of the Moon</td>\n",
       "      <td>The Dark Side of The Moon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Delta Force 2</td>\n",
       "      <td>Delta Force 2: The Colombian Connection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>DuckTales the Movie:Treasure of the Lost Lamp</td>\n",
       "      <td>DuckTales: The Movie - Treasure of the Lost Lamp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5956</th>\n",
       "      <td>Chips</td>\n",
       "      <td>CHiPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5971</th>\n",
       "      <td>Spark</td>\n",
       "      <td>Spark: A Space Tail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5994</th>\n",
       "      <td>Pirates of the Caribbean:Dead Men Tell No Tales</td>\n",
       "      <td>Pirates of the Caribbean: Dead Men Tell No Tales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6023</th>\n",
       "      <td>Valerian and the Cityof a Thousand Planets</td>\n",
       "      <td>Valerian and the City of a Thousand Planets</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6028</th>\n",
       "      <td>An Inconvenient Sequel:Truth to Power</td>\n",
       "      <td>An Inconvenient Sequel: Truth to Power</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>438 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           title_wiki  \\\n",
       "27                                          China Cry   \n",
       "36               Daddy's Dyin' ...Who's Got the Will?   \n",
       "38                          The Dark Side of the Moon   \n",
       "42                                      Delta Force 2   \n",
       "48      DuckTales the Movie:Treasure of the Lost Lamp   \n",
       "...                                               ...   \n",
       "5956                                            Chips   \n",
       "5971                                            Spark   \n",
       "5994  Pirates of the Caribbean:Dead Men Tell No Tales   \n",
       "6023       Valerian and the Cityof a Thousand Planets   \n",
       "6028            An Inconvenient Sequel:Truth to Power   \n",
       "\n",
       "                                          title_kaggle  \n",
       "27                             China Cry: A True Story  \n",
       "36                Daddy's Dyin'... Who's Got the Will?  \n",
       "38                           The Dark Side of The Moon  \n",
       "42             Delta Force 2: The Colombian Connection  \n",
       "48    DuckTales: The Movie - Treasure of the Lost Lamp  \n",
       "...                                                ...  \n",
       "5956                                             CHiPS  \n",
       "5971                               Spark: A Space Tail  \n",
       "5994  Pirates of the Caribbean: Dead Men Tell No Tales  \n",
       "6023       Valerian and the City of a Thousand Planets  \n",
       "6028            An Inconvenient Sequel: Truth to Power  \n",
       "\n",
       "[438 rows x 2 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect the titles from the wiki and kaggle data that don't match\n",
    "movies_df[movies_df['title_wiki'] != movies_df['title_kaggle']][['title_wiki','title_kaggle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>url</th>\n",
       "      <th>year</th>\n",
       "      <th>imdb_link</th>\n",
       "      <th>title_wiki</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>release_date_kaggle</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title_kaggle</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [url, year, imdb_link, title_wiki, Based on, Starring, Cinematography, Release date, Country, Language, Director, Distributor, Editor(s), Composer(s), Producer(s), Production company(s), Writer(s), imdb_id, box_office, budget_wiki, release_date_wiki, running_time, belongs_to_collection, budget_kaggle, genres, homepage, id, original_language, original_title, overview, popularity, poster_path, production_companies, production_countries, release_date_kaggle, revenue, runtime, spoken_languages, status, tagline, title_kaggle, video, vote_average, vote_count]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 44 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show any rows where title_kaggle is empty\n",
    "movies_df[(movies_df['title_kaggle'] == '') | (movies_df['title_kaggle'].isnull())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='running_time', ylabel='runtime'>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fill in missing runtime values with zero and make the scatter plot:\n",
    "\n",
    "movies_df.fillna(0).plot(x='running_time', y='runtime', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='budget_wiki', ylabel='budget_kaggle'>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fill in missing budget values with zero and make a scatter plot:\n",
    "movies_df.fillna(0).plot(x='budget_wiki',y='budget_kaggle', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='box_office', ylabel='revenue'>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fill in missing box office values with zero and make a scatter plot:\n",
    "movies_df.fillna(0).plot(x='box_office', y='revenue', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='box_office', ylabel='revenue'>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# filter the scatter plot for everything less than $1 billion in box_office.\n",
    "movies_df.fillna(0)[movies_df['box_office'] < 10**9].plot(x='box_office', y='revenue', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='release_date_wiki'>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zXimv/8DdmFTSN0nRtX6e9J1zaWXRqo18XlGFATt3GbNffK/R5xDRxF7tc7I4+8jCVrG4SUvxpO+cSxtlazax5P1P4s/E2EAS3HfeURl5kbYhPOk759JCdVlnR0Vicx6LaNrjP7fyWTCbmyd951zKDb/ySdZv3ZnQsXt3yqX056OSHFHb5UnfuQxWe5RMKh77LwtWJrxUIcB/jRqQxKjaPk/6zmWo2FEyudlZzP5uSYsl/qbOcz9w3zxys7M4fXjrWp82HXjSdy5Dxc41X1FZxaJVG1ss6TdlzP15x/b30ThN4BOuOZehSvoXkJudRTtBTnYWJf0LWuRxC6c9kvCxAvL2zEleMBnIe/rOZaiivvnM/m5Js9f0R139DO+s30bXjjn8ZPTBjT7+zBF9uH9xORWVVS365tRWyWz3BTVJvYFZwL5AFTDDzK6T1BX4G1AIrAZOM7NN4ZhLgHOBXcCPzOzx0F7EFytnPQpcaPUEUFxcbKWlpQn+ec65VBp19TOsWL8t4eNzs7OY870SgJRdcG6tJJWZWXHt9ob09CuBn5jZYkl5QJmkJ4GzgafMbLqkacA04GJJhwATgEOB/YD5kg4ys13ATcAUYBFR0h+DL5noXKvSmBE/iST8vPbZDNw3jwP3yfvStMee7JOjIcslrgXWhttbJC0DegKnACPDbncAzwAXh/a7zexz4F1J7wBHVK+ba2YLASTNAsbiSd+5VqMhI36aUrMHOPmw/fhNG1yQPF006kKupEJgGPAisE94Q6h+Y+gedusJvB9zWHlo6xlu1253zrUS8Ub8xGpqws/NzuLbbXRB8nTR4Au5kjoBc4Efm9mnUl1rpcddRN120x7vsaYQlYHo08fH4DqXLqpH/MReVJ1064u8tPpjDt4nr9Hna5cFE4b34dD9urBp+06v2beABvX0JeUQJfzZZnZ/aP5IUo+wvQewLrSXA71jDu8FfBjae8Vp/wozm2FmxWZW3K1bt4b+Lc65ZlbUN58jCruSk53FEYVduW7+2yxYsYEdFVUsKd/c4PN02qMdRxTm0y4rizkvvcevH37DE34LqTfpK+rS3wosM7NrYjb9HZgcbk8GHoxpnyBpD0n9gAOBl0IJaIukknDOSTHHOOdagR/f/UpNkl+wYgMLVmxo1PHtssRvTx3M0l+N4bgB3ancVXepyDWPhpR3jgbOAl6XtCS0XQpMB+6RdC7wHjAewMzekHQP8CbRyJ8LwsgdgKl8MWTzMfwirnOtyuNvfNSk4684ZVDNtAnxSkWu+dU7Tj/VfJy+c+kh0SULjyjM5/PKqrjz5KRywre2rinj9J1zGaJ2Eh775+d4rXwz7XOy2C+/Q6PP99tTB+92QrSivvme7FuYJ33nHBAl/DP+Eo3Bb5clenTeg/JPdgCwvaKKd9ZtbdT5Rh2yj8+AmYZ8wjXnHAD3Ly5nZ2W0atWuKqtJ+Ilon5PFecftn6zQXBJ50nfOAbDioy1JOU+7LPHf/3Zo3LJN2ZpN3PD0O5St2ZSUx3KN5+Ud5xwAL61OPBHnZImK6tVQzNi0/atLH6Zy0Rb3BU/6zmWwsX9+jtc/2MxeCc5RP7wwn3vPO6omoe9u+GUqF21xX/Ck71wGiR2dc8VDb9R8i3bj9opGnytLMO2b0QpWDZmb38flpwcfp+9chogtr2QJwjXbRuuZvycjD+r2pWmPGxODj8tvGT5O37kMF/vFqkQWI4doVM71E4YlnLB9XH7qedJ3LgM0Zcrjrh1zOfbAvTlwnzzvobcBnvSda6OmP7qMf7zxL8Ycum/C5zhzRB9+6wuatCme9J1rg6Y/uoybF6wCqPndGAL2yMlinC9o0uZ40neuDUok0VcbXpjPyAHdvZTTRnnSd64NSHQGzFjVvftp3xzoyb4N86TvXCuXaMLP26Md23buwgzatROnF/dOaBima1086TvXSo26+hlWbtjGnjntGn2sgPNGHkBJ/wIfN59hGrJc4m2S1klaGtN2mKSFkl6X9JCkzqE9V9LM0P6qpJExxxSF9nckXa/drKzunNu9UVc/w4r126gy2LZzV/0H1FL9jdiivvlccPwBnvAzSENm2bwdGFOr7RZgmpkNBuYBF4X27wGE9lHA1ZKqH+MmYArRmrkHxjmnc66BVqzf1qj9zzu2P4f16sIRhflMHNGHOd/zyc4yVb3lHTNbIKmwVvMAYEG4/STwOHA5cAjwVDhunaRPgGJJ7wOdzWwhgKRZwFh8jVzn4krmdAVzpx7lCd7VSLSmvxQ4GXiQaEH03qH9VeAUSXeHtqLwuwoojzm+HOiZ4GM716bFm4IYqHkTeOtfDZv3PjtL/PqUQZ7w3ZckmvTPAa6X9N/A34HqybNvAwYCpcAa4AWgkui6UW11zv4haQpRKYg+fXy5NZdZak9BPHdxOfeVvk/FLiOnnehT0LHec0wc0cdH4ri4Ekr6ZrYcGA0g6SDgpNBeCfxn9X6SXgBWAJuA2K/29QI+3M35ZwAzIJplM5EYnWutSvoXkJ0lKnYZ7bLEhi2fs3NX9N9g5y7jkzgLlMQ6sFtHfuNTJ7g6JLRcoqTu4XcW8HPg5nC/g6SO4fYooNLM3jSztcAWSSVh1M4kotKQcy6e6sFtcQa5xVvwpGuHHNoJhvbqwpM/GdnMwbnWrN6evqQ5wEhgb0nlwC+ATpIuCLvcD8wMt7sDj0uqAj4Azoo51VSikUB7El3A9Yu4zsWxaNVGKndVYcCuXVXsnbfHlxYfOeeY/vzy70tryj1zphzpZRzXYA0ZvXNGHZuui7PvaqKRPfHOUwoMakxwzmWi2itMjTu8F+MO7/Wl0TwD9s3zL1W5hPjKWc6lIV9hyjWVr5zlXJqKl+B9hSnXXDzpO5dC8cbke7J3zSmh0TvOueSoPSZ/0aqNqQ7JtXGe9J1LoeqLtu30xSRozjUnL+84l0JFffOZ/d0Sv2jrWownfedSzC/aupbk5R3nnMsgnvSdcy6DeNJ3zrkM4knfOecyiCd955zLIJ70nXMug3jSd865DOJJ3znnMognfeecyyD1Jn1Jt0laJ2lpTNthkhZKel3SQ5I6h/YcSXeE9mWSLok5pii0vyPp+rBsonPOuRbUkJ7+7cCYWm23ANPMbDAwD7gotI8H9gjtRcD3JRWGbTcBU4ADw0/tczrnnGtm9SZ9M1sAfFyreQCwINx+EhhXvTvQUVI20Vq4O4FPJfUAOpvZQouW6poFjG16+M455xoj0Zr+UuDkcHs80Dvcvg/YBqwF3gP+YGYfAz2B8pjjy0Obc865FpRo0j8HuEBSGZBH1KMHOALYBewH9AN+Iqk/EK9+X+fivJKmSCqVVLp+/foEQ3TOOVdbQknfzJab2WgzKwLmACvDpjOBf5hZhZmtA54Hiol69r1iTtEL+HA3559hZsVmVtytW7dEQnTOORdHQklfUvfwOwv4OXBz2PQecIIiHYESYLmZrQW2SCoJo3YmAQ82OXrnnHON0pAhm3OAhcAASeWSzgXOkPQ2sJyoxz4z7H4D0Imo5v8yMNPMXgvbphKN+nmH6JPBY8n8Q5xzztWv3pWzzOyMOjZdF2ffrUQXduOdpxQY1KjonHPOJZV/I9c55zKIJ33nnMsgnvSdcy6DeNJ3zrkM4knfOecyiCd955zLIJ70nXMug3jSd865DOJJ3znnMognfeecyyCe9J1zLoN40nfOuQziSd855zKIJ33nnMsgnvSdcy6DeNJ3zrkM4knfOecySEOWS7xN0jpJS2PaDpO0UNLrkh6S1Dm0T5S0JOanStLQsK0o7P+OpOvDWrnOOedaUEN6+rcDY2q13QJMM7PBwDzgIgAzm21mQ81sKHAWsNrMloRjbgKmAAeGn9rndM4518zqTfpmtgD4uFbzAGBBuP0kMC7OoWcAcwAk9QA6m9lCMzNgFjA2wZidc84lKNGa/lLg5HB7PNA7zj6nE5I+0BMoj9lWHtrikjRFUqmk0vXr1ycYonPOudoSTfrnABdIKgPygJ2xGyWNALabWfV1gHj1e6vr5GY2w8yKzay4W7duCYbonHOutuxEDjKz5cBoAEkHASfV2mUCX/TyIerZ94q53wv4MJHHds45l7iEevqSuoffWcDPgZtjtmURlXzurm4zs7XAFkklYdTOJODBJsTtnHMuAQ0ZsjkHWAgMkFQu6VzgDElvA8uJeuwzYw45Fig3s1W1TjWVaNTPO8BK4LEkxO+cc64RFA2mSV/FxcVWWlqa6jCcc65VkVRmZsW12/0buc45l0E86TvnXAbxpO+ccxnEk75zzmUQT/rOOZdBPOk751wG8aTvnHMZxJO+c85lEE/6zjmXQTzpO+dcBvGk75xzGcSTvnPOZRBP+s45l0E86bcxZWs2ccPT71C2ZlOqQ3HOpaGEVs5y6alszSYm3rKInZVV5GZnMfu7JRT1zU91WM65NOI9/TZk0aqN7KysosqgorKKRas2pjok51yaacjKWbdJWidpaUzbYZIWSnpd0kOSOsdsGxK2vRG2tw/tReH+O5KuD8smuiQq6V9AbnYW7QQ52VmU9C9IdUjOuTTTkJ7+7cCYWm23ANPMbDAwD7gIQFI2cCdwnpkdCowEKsIxNwFTgAPDT+1zuiYq6pvP7O+W8F+jB3hpxzkXV701fTNbIKmwVvMAYEG4/STwOHA5MBp4zcxeDcduBJDUA+hsZgvD/VnAWHyd3KQr6pvvyd45V6dEa/pLgZPD7fFA73D7IMAkPS5psaSfhfaeQHnM8eWhLS5JUySVSipdv359giE655yrLdGkfw5wgaQyIA/YGdqzgWOAieH3qZJOBOLV7+tckd3MZphZsZkVd+vWLcEQ2wYfgumcS6aEhmya2XKiUg6SDgJOCpvKgWfNbEPY9ihwOFGdv1fMKXoBHyYYc8bwIZjOuWRLqKcvqXv4nQX8HLg5bHocGCKpQ7ioexzwppmtBbZIKgmjdiYBDzY5+jbOh2A655KtIUM25wALgQGSyiWdC5wh6W1gOVGPfSaAmW0CrgFeBpYAi83skXCqqUSjft4BVuIXcevlQzCdc8kmszpL62mhuLjYSktLUx1GypSt2cSiVRsp6V/gpR3nXINJKjOz4trtPg1DmvMhmM65ZPJpGJxzLoN40nfOuQziSd855zKIJ33nnMsgnvSdcy6DeNJ3zrkM4knfOecyiCd951yb4JMTNox/OauJ/BuzzqWeT07YcJ70m8BfaM6lh3iTE/r/xfi8vNMEPgumc+nBJydsOO/pN0H1C62isspfaM6lUPX60F5qrZ/PstlEXtN3zqUjn2WzmfgsmM651sRr+s45l0EasnLWbZLWSVoa03aYpIWSXpf0kKTOob1Q0meSloSfm2OOKQr7vyPp+rBsonPOuRbUkJ7+7cCYWm23ANPMbDAwD7goZttKMxsafs6Lab8JmAIcGH5qn9M551wzqzfpm9kC4ONazQOABeH2k8C43Z1DUg+gs5kttOjK8SxgbKOjdc451ySJ1vSXAieH2+OB3jHb+kl6RdKzkr4W2noC5TH7lIe2uCRNkVQqqXT9+vUJhuicc662RJP+OcAFksqAPGBnaF8L9DGzYcB/AXeFen+8+n2dY0XNbIaZFZtZcbdu3RIM0TnnXG0JDdk0s+XAaABJBwEnhfbPgc/D7TJJK4GDiHr2vWJO0Qv4MPGwnXPOJSKhnr6k7uF3FvBz4OZwv5ukduF2f6ILtqvMbC2wRVJJGLUzCXgwCfE755xrhHp7+pLmACOBvSWVA78AOkm6IOxyPzAz3D4W+LWkSmAXcJ6ZVV8Enko0EmhP4LHw45xzrgW12WkYfHoE51wmy6hpGMrWbOKMvyyqmQhtzvd8ymPnnIM2Og3D/YvL2VlZhQE7K6u4f3F5vcc451wmaJNJv3bBKr0LWM4513LaZNIfd3gvctsJAbntxLjDe9V7jHPOZYI2WdMv6pvPnClH+oVc55yrpU0mffB57p1zLp42Wd5xzjkXnyd955zLIJ70nXMug3jSd865DJL20zBIWg+sacGH3BvY0IKP1xQea/PwWJOvtcQJbSfWvmb2lbnp0z7ptzRJpfHmq0hHHmvz8FiTr7XECW0/Vi/vOOdcBvGk75xzGcST/lfNSHUAjeCxNg+PNflaS5zQxmP1mr5zzmUQ7+k751wG8aTvnHMZxJO+cy4pJCnVMTRUJseasUk/k//Rm5PH2jxaSaw5qQ6gETI21oxK+pIOlTQSwNL8CrbH2jw81uSTdKSke4E/SDpEUrtUx1QXjzVDRu9IygL+DJwAvAe8CDxoZqWSssysKqUBxvBYm4fH2jwkdQceI4q3N9ATKDWzv0hSOr1ZeayRTOnp5wN5wEBgIrAR+ImkTun0HyhoTbF2ofXE2pqe172ATrSOWA8D3jazmcDVwP3AKZIOMjNLs7LUIFpPrM32vLbZpC9plKRR4W5n4Eigg5mtB+YCHwMXhH1T+o8t6d8lnR/upnus35b0x3C3gPSO9XBJB4W7XYCjSN9Y+0lqH+52JU1jlXSGpF9JOjk0vQIUS9rfzLYBLwOlwPchtWUpScdJGhHT9CpRrP3TMNaxki6VdFJoWkIzPa9tLumHOujdwKXAJgAzexd4Hvhx2G0t0TvnMEn7peofW1InSXOBnwKbJGWncayHSLoLuBy4MMTyDrAwDWPtJ+kR4Abgr5JGmdkq4IU0jLVQ0mPALcBsSYeE53UB8F/pEqsi5wE/A1YDV0n6LrAVmAVcGHb9BJgPdJDUo6XjBJCUJ+l+YB7wfUn5AGa2Efgb8KM0irWbpAeI/q0/BmZK+veYN/sfJjvWNpH0q3s+kroS/Wf52MyON7PSmN1uB46W1M/MKoGPgB3AnqmINegNfGRmJWY2B9hVK9b+6RCrpGOBvwCLzGwYcB1Q3YO6lfR7Xn8KLDGzI4EHgXNC+21pGuuLZnYi8DTwK0mHEL0GSlL9GqgW3miOBKaHksMFwEjgROBR4ABJXw/lp41ENejNqYgV2An8E/gP4ENgfMy2ucDBkk5Mk1j3B543s2PN7GbgJ8B/hm1zaIZY20TSB9oDmNnHwFXAHgCSzpb0DUl9zexpoo+iV4V9lwJ9gc9TEWswBOgVYj0f+IWkY4A3iXqlf4CUxlqdYN4ERpvZ9ZJygQOA6tryq8Bi4H9SHGt7qEmo24CK0N4ZWCbpAKJPUC+T+ue1OtbscP+NEM+fgSOACUTJ6mVS+LxKmhRKJF1D0zKgZ/hEOh9YCpQA64G7gGvD83wiICA3BbHuZWafE31ymg+8TVQmGRB2fRW4Ow1iHSmpA1BG9EkJRaNz3gw/AK+HWK9LZqytOumHuv2TRB81J4Tm64DhktYCJwP/D3hI0v7Ar4hetH+StJRocZbNLVEjjYn1fySdEZoXA2sl3UbUi/oEuAw4BbgG6C7pzymOdYKZbTCzbZLam9lOohfjRAAz2wT8GuiV4uf1KkmnhR7pc8CBkl4BxgDtiJLSccDvgB4pfl6rY60k+kg/TNJhkg4jSqT9QsxX0sLPayjj9JD0NDCZ6N/5T5I6A+8D3Yne9CFKSIOAAjO7E5gNTCN60/qZmX3SXHHuJtYbJO1tZjvCa3UhsA44DcDMqszsduCvwCUpjPVMok/PXczsI0ntzGwX0cX7LrVinUUyn1cza5U/RC+8F4kS5DCiF9ylYdu3gMkx+94G/D7c3ofoItnJKY71J0A20ZX5MiAn7HsWMCPc7p4Gsd4Z87xWx3hcaO8Wc1y3NIj1LuCnYdsA4P6YfS8H/pxGr4E5wPlEI4ouBx4merMqDn/Hj1s6VqBd+H0QcGe4nQ3cCNxB9CWh28JrtEvYfjvwm5hz5LbQ81lXrH8C5tba99TwNxwAdASy0ijW+2vtMws4Ldzetzme1+qPl62CovHLWFTfGgGUmdmDYdtTwDWSbjGzh6r3D/s+Anw9HPsRUX00lbH+kyjZ30pUcx5GVHe8i+jj57gQ+zqiXkqqY61+XqtjySHqjWyqPodFF57WpzjW+SHWvxL1oN+XNNDMlhHVy38sSWnyGphP9Bq418yuCLX7VWHb83xRxlkX4m3OOLOJPq21k/QoUUlsV4i9UtIPiC4mH0L0Gh1LVJb8HVGZ74Xqc1nUu05lrD8CPpR0nJk9G9rnSRoI/INoKOzxwLJ0jJXowvi7kn4NfFvSGDMrT2asraa8I+k7QDlwRWh6HThDUmG4nwOsJNRrIfrPJmky8Auif/B0iTUbeBf4HzNbAFxLNA77YqKPzM+F87REySGR53U+UY/0qOaOL1YDY10Vtm8hGvr4I0kXAv9LVONNl1iziZ7X6uGv74bjpgDnEpX+sNDNa8Y4jyP6pJkPvBPirQCOl3REiKGKKHn9PvzbzwCOkfRiOO6Z5oyxkbFaiPWXMceNJyqbPg0MCZ2AtItVUU3/HOA+ojeI482sPOnBtcTHmyR8POoEPEA0LGwxcHBov5boY/LzROWGwUS9+u5EY8ivInpBDk/TWB8lfIQDhhONwT0yTWN9JCbWHGAKUJimsT5G9DF+INGQtzuAkjSN9RFgn7D9x0QXb1vy9fo14KyY+zcCU4GziT6ZQNQ53Be4t/rfnOgLZD1bKs4EYr0H6Bdz3NfSPNa+RCN5rgUOb9bYWvKJaOKT2Cf8ng78LdxuR9SbOybc701UY8wOP31bQaztW8nzOhPYo5XEegctVK9N0mtgj3C/Qwri7EA02q26pjwR+F24vQT4YbhdDMxJ8XPaVmO9uyVjazXlHTN7L9y8Fugn6RsWXe3ebGbPhW3nAdvD/pVmtqblI210rBVxTtFiGhHrZ0BlCkKs0YhYt/HFdx5SopGvgcpwzPYUxLndzD4PsQGM4otrM98BBkp6mOgTyuKWji9WG461DFrwm9apfDdswrvo94FnY+4fQXRBtKZcki4/HqvH2hpiJfoUkkVUGjsgtB1AVMY5hhYu5XiszffT6mbZrB6RI+k+ohEFnxNdoFthZitTG92XeazNw2NNvtDLzCX6UtM8oguKG4nKEJ+mMrbaPNamaVVDNqFmRE4Hoou1I4Ffm1mLjcxpDI+1eXisyWdmJmkYUe25HzDTzG5NcVhxeaxN0+qSfnA+Uc1ulEVfuU5nHmvz8FiTr5xoaOM1aR4neKwJa3XlHfjSl67SnsfaPDxW5xLTKpO+c865xLSaIZvOOeeazpO+c85lEE/6zjmXQTzpO+dcBvGk71olSVtTHUO1+mKRtJe+WPi+OR7/0fAYhYoWW6m9vVjS9c31+K518dE7Lm2FbzMq3nBHSVvNrFMKwvqK+mIJ0yk/bGaDmjmOFnkc17p5T9+lldBbXSbpRqIvNF0u6WVJr0n6VR3HXBRvH0kPSCqT9EaYpx5J7STdLmmppNcl/Wdo31/SP8L+/yfp4N3E2E/SwvCYV8S0d5L0lKTF4dynhE3Tgf0lLZF01e5ijvNYP1O02AaS/qhoURsknSjpznB7taS9ax3XX9IrkoYrWo/14bqfdZdJPOm7dDSAaNm4i4GeRBOUDQWKJB0bu6Ok0cCBdexzjpkVEU1f+yNJBWGfnmY2yMwGE00ZDdHCID8M+/+UaP7zulwH3GRmw4F/xbTvAE41s8OJVme6OnxamQasNLOhZnZRPTHXtoBobnbC39FJUg7RZF3/F+8ARYuAzwW+Y2Yv7+bvcBmotU7D4Nq2NWa2SNIfgNHAK6G9E1GyXBCz7+jd7PMjSaeG9t6h/S2gv6Q/ES1g8oSkTkSrgN0bM7vtHruJ72hgXLj9V+D34baA34YEXkX0hrVPnON3F3NtZURvCnlEk7UtJkr+XwN+FGf/bkQzeI4zszd28ze4DOVJ36WjbeG3iBae+N/d7Bt3H0kjidZFPtLMtkt6hmjBmk2SDgO+AVwAnEa0YtUnZja0ETHGuxg2kSjpFplZhaTVQPuGxhz3Qb44z3eI1qJ9jehTxP5AvGX/NgPvE70xedJ3X+HlHZfOHgfOCT1xJPWU1L2B+3QBNoWEfzBQErbvDWSZ2VzgcqKl6T4lWox6fNhH4Y2hLs8DE8LtiTHtXYgWMq+QdDzREngQrdeb18i/K9YCopLTAqKSznnAEos/CmMn0cLlkySduZtzugzlPX2XtszsCUkDgYWh7LIV+A9gXQP2+QdwnqTXiEo6i8IhPYGZkqo7PJeE3xOBmyT9nGgN4LuBV+sI7ULgLkULrs+NaZ8NPCSplGhJvOUhxo2Sng/DKR8Ldf3d/l21/B/RLI0LzWybpB3UUc8Pj7dN0r8BT0raRtT7dw7wIZvOOZdRvLzjnHMZxMs7ztVB0mXA+FrN95rZb5rhsQqAp+JsOtHMNib78Vzm8vKOc85lEC/vOOdcBvGk75xzGcSTvnPOZRBP+s45l0E86TvnXAb5/+Naf1VoIbGyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make a scatter plot for release date\n",
    "movies_df[['release_date_wiki','release_date_kaggle']].plot(x='release_date_wiki', y='release_date_kaggle', style='.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# look for any movie whose release date according to Wikipedia is after 1996, but \n",
    "# whose release date according to Kaggle is before 1965:\n",
    "movies_df[(movies_df['release_date_wiki'] > '1996-01-01') & (movies_df['release_date_kaggle'] < '1965-01-01')]\n",
    "\n",
    "# get index for movies that fit the criteria\n",
    "movies_df[(movies_df['release_date_wiki'] > '1996-01-01') & (movies_df['release_date_kaggle'] < '1965-01-01')].index\n",
    "\n",
    "# drop rows that fit the criteria\n",
    "movies_df = movies_df.drop(movies_df[(movies_df['release_date_wiki'] > '1996-01-01') & (movies_df['release_date_kaggle'] < '1965-01-01')].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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_wiki</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>release_date_kaggle</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title_kaggle</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Black_Scorpion_(...</td>\n",
       "      <td>1995</td>\n",
       "      <td>https://www.imdb.com/title/tt0112519/</td>\n",
       "      <td>Black Scorpion</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Joan Severance, Bruce Abbott, Garrett Morris]</td>\n",
       "      <td>Geoff George</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1995-08-22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>92.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Justice has a nasty sting.</td>\n",
       "      <td>Black Scorpion</td>\n",
       "      <td>False</td>\n",
       "      <td>6.10</td>\n",
       "      <td>7.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Flirt_(1995_film)</td>\n",
       "      <td>1995</td>\n",
       "      <td>https://www.imdb.com/title/tt0113080/</td>\n",
       "      <td>Flirt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Bill Sage, Dwight Ewell, Miho Nikaido]</td>\n",
       "      <td>Michael Spiller</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[United States, Germany, Japan, [1]]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1995-09-14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>85.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flirt</td>\n",
       "      <td>False</td>\n",
       "      <td>7.50</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1121</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Let_It_Be_Me_(19...</td>\n",
       "      <td>1995</td>\n",
       "      <td>https://www.imdb.com/title/tt0113638/</td>\n",
       "      <td>Let It Be Me</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Miroslav Ondrícek</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1995-11-17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>95.00</td>\n",
       "      <td>[]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Let It Be Me</td>\n",
       "      <td>False</td>\n",
       "      <td>8.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1564</th>\n",
       "      <td>https://en.wikipedia.org/wiki/A_Brooklyn_State...</td>\n",
       "      <td>1997</td>\n",
       "      <td>https://www.imdb.com/title/tt0118782/</td>\n",
       "      <td>A Brooklyn State of Mind</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ken Kelsch</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1998-01-01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>89.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Brooklyn State of Mind</td>\n",
       "      <td>False</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1633</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Highball_(film)</td>\n",
       "      <td>1997</td>\n",
       "      <td>https://www.imdb.com/title/tt0119291/</td>\n",
       "      <td>Highball</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Justine Bateman, Peter Bogdanovich, Chris Eig...</td>\n",
       "      <td>Steven Bernstein</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>1997-01-01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>110.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Highball</td>\n",
       "      <td>False</td>\n",
       "      <td>4.50</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1775</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Velocity_Trap</td>\n",
       "      <td>1997</td>\n",
       "      <td>https://www.imdb.com/title/tt0120435/</td>\n",
       "      <td>Velocity Trap</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Olivier Gruner, Alicia Coppola, Ken Olandt]</td>\n",
       "      <td>Philip D. Schwartz</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1999-02-22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>86.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Crime at the Speed of Light</td>\n",
       "      <td>Velocity Trap</td>\n",
       "      <td>False</td>\n",
       "      <td>4.70</td>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2386</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Visit_(2000_...</td>\n",
       "      <td>2000</td>\n",
       "      <td>https://www.imdb.com/title/tt0199129/</td>\n",
       "      <td>The Visit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Hill Harper, Billy Dee Williams, Obba Babatun...</td>\n",
       "      <td>John L. Demps Jr.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>107.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Rumored</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Visit</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2786</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Stevie_(2002_film)</td>\n",
       "      <td>2002</td>\n",
       "      <td>https://www.imdb.com/title/tt0334416/</td>\n",
       "      <td>Stevie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Dana Kupper, Gordon Quinn, Peter Gilbert]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2002-09-09</td>\n",
       "      <td>97,000.00</td>\n",
       "      <td>140.00</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Stevie</td>\n",
       "      <td>False</td>\n",
       "      <td>6.70</td>\n",
       "      <td>13.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3174</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Return_to_Sender...</td>\n",
       "      <td>2004</td>\n",
       "      <td>https://www.imdb.com/title/tt0396190/</td>\n",
       "      <td>Return to Sender</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Aidan Quinn, Connie Nielsen, Mark Holton]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Denmark, USA, UK]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2004-09-17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>109.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>How can you save someone, who won't save herself?</td>\n",
       "      <td>Return to Sender</td>\n",
       "      <td>False</td>\n",
       "      <td>5.90</td>\n",
       "      <td>13.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3651</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Live_Free_or_Die...</td>\n",
       "      <td>2006</td>\n",
       "      <td>https://www.imdb.com/title/tt0432318/</td>\n",
       "      <td>Live Free or Die</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Aaron Stanford, Paul Schneider, Ebon Moss-Bac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>2006-03-11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>89.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Live Free or Die</td>\n",
       "      <td>False</td>\n",
       "      <td>5.50</td>\n",
       "      <td>8.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4967</th>\n",
       "      <td>https://en.wikipedia.org/wiki/For_the_Love_of_...</td>\n",
       "      <td>2012</td>\n",
       "      <td>https://www.imdb.com/title/tt1730294/</td>\n",
       "      <td>For the Love of Money</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Yehuda Levi, Edward Furlong, James Caan, Jeff...</td>\n",
       "      <td>Andrzej Sekuła</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>English/Hebrew</td>\n",
       "      <td>...</td>\n",
       "      <td>2012-06-08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>93.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>For the love of money is the root of all evil.</td>\n",
       "      <td>For the Love of Money</td>\n",
       "      <td>False</td>\n",
       "      <td>5.60</td>\n",
       "      <td>9.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    url  year  \\\n",
       "1008  https://en.wikipedia.org/wiki/Black_Scorpion_(...  1995   \n",
       "1061    https://en.wikipedia.org/wiki/Flirt_(1995_film)  1995   \n",
       "1121  https://en.wikipedia.org/wiki/Let_It_Be_Me_(19...  1995   \n",
       "1564  https://en.wikipedia.org/wiki/A_Brooklyn_State...  1997   \n",
       "1633      https://en.wikipedia.org/wiki/Highball_(film)  1997   \n",
       "1775        https://en.wikipedia.org/wiki/Velocity_Trap  1997   \n",
       "2386  https://en.wikipedia.org/wiki/The_Visit_(2000_...  2000   \n",
       "2786   https://en.wikipedia.org/wiki/Stevie_(2002_film)  2002   \n",
       "3174  https://en.wikipedia.org/wiki/Return_to_Sender...  2004   \n",
       "3651  https://en.wikipedia.org/wiki/Live_Free_or_Die...  2006   \n",
       "4967  https://en.wikipedia.org/wiki/For_the_Love_of_...  2012   \n",
       "\n",
       "                                  imdb_link                title_wiki  \\\n",
       "1008  https://www.imdb.com/title/tt0112519/            Black Scorpion   \n",
       "1061  https://www.imdb.com/title/tt0113080/                     Flirt   \n",
       "1121  https://www.imdb.com/title/tt0113638/              Let It Be Me   \n",
       "1564  https://www.imdb.com/title/tt0118782/  A Brooklyn State of Mind   \n",
       "1633  https://www.imdb.com/title/tt0119291/                  Highball   \n",
       "1775  https://www.imdb.com/title/tt0120435/             Velocity Trap   \n",
       "2386  https://www.imdb.com/title/tt0199129/                 The Visit   \n",
       "2786  https://www.imdb.com/title/tt0334416/                    Stevie   \n",
       "3174  https://www.imdb.com/title/tt0396190/          Return to Sender   \n",
       "3651  https://www.imdb.com/title/tt0432318/          Live Free or Die   \n",
       "4967  https://www.imdb.com/title/tt1730294/     For the Love of Money   \n",
       "\n",
       "     Based on                                           Starring  \\\n",
       "1008      NaN     [Joan Severance, Bruce Abbott, Garrett Morris]   \n",
       "1061      NaN            [Bill Sage, Dwight Ewell, Miho Nikaido]   \n",
       "1121      NaN                                                NaN   \n",
       "1564      NaN                                                NaN   \n",
       "1633      NaN  [Justine Bateman, Peter Bogdanovich, Chris Eig...   \n",
       "1775      NaN       [Olivier Gruner, Alicia Coppola, Ken Olandt]   \n",
       "2386      NaN  [Hill Harper, Billy Dee Williams, Obba Babatun...   \n",
       "2786      NaN                                                NaN   \n",
       "3174      NaN         [Aidan Quinn, Connie Nielsen, Mark Holton]   \n",
       "3651      NaN  [Aaron Stanford, Paul Schneider, Ebon Moss-Bac...   \n",
       "4967      NaN  [Yehuda Levi, Edward Furlong, James Caan, Jeff...   \n",
       "\n",
       "                                  Cinematography Release date  \\\n",
       "1008                                Geoff George          NaN   \n",
       "1061                             Michael Spiller          NaN   \n",
       "1121                           Miroslav Ondrícek          NaN   \n",
       "1564                                  Ken Kelsch          NaN   \n",
       "1633                            Steven Bernstein          NaN   \n",
       "1775                          Philip D. Schwartz          NaN   \n",
       "2386                           John L. Demps Jr.          NaN   \n",
       "2786  [Dana Kupper, Gordon Quinn, Peter Gilbert]          NaN   \n",
       "3174                                         NaN          NaN   \n",
       "3651                                         NaN          NaN   \n",
       "4967                              Andrzej Sekuła          NaN   \n",
       "\n",
       "                                   Country        Language  ...  \\\n",
       "1008                         United States             NaN  ...   \n",
       "1061  [United States, Germany, Japan, [1]]             NaN  ...   \n",
       "1121                                   NaN             NaN  ...   \n",
       "1564                                   NaN             NaN  ...   \n",
       "1633                         United States         English  ...   \n",
       "1775                         United States             NaN  ...   \n",
       "2386                                   NaN         English  ...   \n",
       "2786                         United States         English  ...   \n",
       "3174                    [Denmark, USA, UK]             NaN  ...   \n",
       "3651                         United States         English  ...   \n",
       "4967                         United States  English/Hebrew  ...   \n",
       "\n",
       "     release_date_kaggle              revenue              runtime  \\\n",
       "1008          1995-08-22                 0.00                92.00   \n",
       "1061          1995-09-14                 0.00                85.00   \n",
       "1121          1995-11-17                 0.00                95.00   \n",
       "1564          1998-01-01                 0.00                89.00   \n",
       "1633          1997-01-01                 0.00               110.00   \n",
       "1775          1999-02-22                 0.00                86.00   \n",
       "2386          2000-01-01                 0.00               107.00   \n",
       "2786          2002-09-09            97,000.00               140.00   \n",
       "3174          2004-09-17                 0.00               109.00   \n",
       "3651          2006-03-11                 0.00                89.00   \n",
       "4967          2012-06-08                 0.00                93.00   \n",
       "\n",
       "                                       spoken_languages    status  \\\n",
       "1008           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "1061  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "1121                                                 []  Released   \n",
       "1564           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "1633           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "1775           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "2386  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...   Rumored   \n",
       "2786                                                 []       NaN   \n",
       "3174           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "3651           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "4967  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
       "\n",
       "                                                tagline  \\\n",
       "1008                         Justice has a nasty sting.   \n",
       "1061                                                NaN   \n",
       "1121                                                NaN   \n",
       "1564                                                NaN   \n",
       "1633                                                NaN   \n",
       "1775                        Crime at the Speed of Light   \n",
       "2386                                                NaN   \n",
       "2786                                                NaN   \n",
       "3174  How can you save someone, who won't save herself?   \n",
       "3651                                                NaN   \n",
       "4967     For the love of money is the root of all evil.   \n",
       "\n",
       "                  title_kaggle  video         vote_average  \\\n",
       "1008            Black Scorpion  False                 6.10   \n",
       "1061                     Flirt  False                 7.50   \n",
       "1121              Let It Be Me  False                 8.00   \n",
       "1564  A Brooklyn State of Mind  False                 5.00   \n",
       "1633                  Highball  False                 4.50   \n",
       "1775             Velocity Trap  False                 4.70   \n",
       "2386                 The Visit  False                 0.00   \n",
       "2786                    Stevie  False                 6.70   \n",
       "3174          Return to Sender  False                 5.90   \n",
       "3651          Live Free or Die  False                 5.50   \n",
       "4967     For the Love of Money  False                 5.60   \n",
       "\n",
       "               vote_count  \n",
       "1008                 7.00  \n",
       "1061                 4.00  \n",
       "1121                 2.00  \n",
       "1564                 1.00  \n",
       "1633                 4.00  \n",
       "1775                 6.00  \n",
       "2386                 0.00  \n",
       "2786                13.00  \n",
       "3174                13.00  \n",
       "3651                 8.00  \n",
       "4967                 9.00  \n",
       "\n",
       "[11 rows x 44 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check if any null values exist in the release date data\n",
    "movies_df[movies_df['release_date_wiki'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "English                               5479\n",
       "NaN                                    134\n",
       "(English, Spanish)                      68\n",
       "(English, French)                       35\n",
       "(English, Japanese)                     25\n",
       "                                      ... \n",
       "Greek, English                           1\n",
       "(English, Russian, Serbo-Croatian)       1\n",
       "(English, Russian, Spanish)              1\n",
       "(Portuguese, English)                    1\n",
       "English/German/Korean                    1\n",
       "Name: Language, Length: 198, dtype: int64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the lists in Language to tuples\n",
    "movies_df['Language'].apply(lambda x: tuple(x) if type(x) == list else x).value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "en    5987\n",
       "fr      16\n",
       "es      10\n",
       "it       8\n",
       "de       6\n",
       "ja       4\n",
       "zh       4\n",
       "pt       4\n",
       "da       2\n",
       "hi       2\n",
       "he       1\n",
       "sv       1\n",
       "cn       1\n",
       "ru       1\n",
       "tr       1\n",
       "ar       1\n",
       "ko       1\n",
       "ab       1\n",
       "Name: original_language, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# collect the value counts of each row in the original_language column\n",
    "movies_df['original_language'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Production company(s)</th>\n",
       "      <th>production_companies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Silver Pictures</td>\n",
       "      <td>[{'name': 'Twentieth Century Fox Film Corporat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Avenue Pictures</td>\n",
       "      <td>[{'name': 'Avenue Pictures Productions', 'id':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[Carolco Pictures, IndieProd Company]</td>\n",
       "      <td>[{'name': 'IndieProd Company Productions', 'id...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'name': 'Orion Pictures', 'id': 41}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[{'name': 'Paramount Pictures', 'id': 4}]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>[Fabula, Komplizen Film]</td>\n",
       "      <td>[{'name': 'Komplizen Film', 'id': 1618}, {'nam...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>Ball &amp; Chain Productions</td>\n",
       "      <td>[{'name': 'Ball &amp; Chain Productions', 'id': 74...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>[Arte France Cinéma, Why Not Productions]</td>\n",
       "      <td>[{'name': 'ARTE France Cinéma', 'id': 94}, {'n...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>[Film Science, Rough House Pictures, Syncopate...</td>\n",
       "      <td>[{'name': 'Film Science', 'id': 1976}, {'name'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6051</th>\n",
       "      <td>[HanWay Films, Little Punk, See-Saw Films]</td>\n",
       "      <td>[{'name': 'HanWay Films', 'id': 2395}, {'name'...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6051 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Production company(s)  \\\n",
       "0                                       Silver Pictures   \n",
       "1                                       Avenue Pictures   \n",
       "2                 [Carolco Pictures, IndieProd Company]   \n",
       "3                                                   NaN   \n",
       "4                                                   NaN   \n",
       "...                                                 ...   \n",
       "6047                           [Fabula, Komplizen Film]   \n",
       "6048                           Ball & Chain Productions   \n",
       "6049          [Arte France Cinéma, Why Not Productions]   \n",
       "6050  [Film Science, Rough House Pictures, Syncopate...   \n",
       "6051         [HanWay Films, Little Punk, See-Saw Films]   \n",
       "\n",
       "                                   production_companies  \n",
       "0     [{'name': 'Twentieth Century Fox Film Corporat...  \n",
       "1     [{'name': 'Avenue Pictures Productions', 'id':...  \n",
       "2     [{'name': 'IndieProd Company Productions', 'id...  \n",
       "3                [{'name': 'Orion Pictures', 'id': 41}]  \n",
       "4             [{'name': 'Paramount Pictures', 'id': 4}]  \n",
       "...                                                 ...  \n",
       "6047  [{'name': 'Komplizen Film', 'id': 1618}, {'nam...  \n",
       "6048  [{'name': 'Ball & Chain Productions', 'id': 74...  \n",
       "6049  [{'name': 'ARTE France Cinéma', 'id': 94}, {'n...  \n",
       "6050  [{'name': 'Film Science', 'id': 1976}, {'name'...  \n",
       "6051  [{'name': 'HanWay Films', 'id': 2395}, {'name'...  \n",
       "\n",
       "[6051 rows x 2 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Review production company data\n",
    "movies_df[['Production company(s)','production_companies']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Competing data:\n",
    "# Wiki                     Movielens                Resolution\n",
    "#--------------------------------------------------------------------------\n",
    "# title_wiki               title_kaggle             Drop Wikipedia.\n",
    "# running_time             runtime                  Keep kaggle; fill in zeros with Wikipedia data.\n",
    "# budget_wiki              budget_kaggle            Keep Kaggle; fill in zeros with Wikipedia data.\n",
    "# box_office               revenue                  Keep Kaggle; fill in zeros with Wikipedia data.\n",
    "# release_date_wiki        release_date_kaggle      Drop Wikipedia.\n",
    "# Language                 original_language        Drop Wikipedia.\n",
    "# Production company(s)    production_companies     Drop Wikipedia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop the title_wiki, release_date_wiki, Language, and Production company(s) columns.\n",
    "movies_df.drop(columns=['title_wiki','release_date_wiki','Language','Production company(s)'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Based on</th>\n",
       "      <th>Starring</th>\n",
       "      <th>Cinematography</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Country</th>\n",
       "      <th>Director</th>\n",
       "      <th>Distributor</th>\n",
       "      <th>...</th>\n",
       "      <th>release_date_kaggle</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title_kaggle</th>\n",
       "      <th>video</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</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>[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>Renny Harlin</td>\n",
       "      <td>20th Century Fox</td>\n",
       "      <td>...</td>\n",
       "      <td>1990-07-11</td>\n",
       "      <td>20,423,389.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Kojak. Columbo. Dirty Harry. Wimps.</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>False</td>\n",
       "      <td>6.20</td>\n",
       "      <td>72.00</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>[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>James Foley</td>\n",
       "      <td>Avenue Pictures</td>\n",
       "      <td>...</td>\n",
       "      <td>1990-08-24</td>\n",
       "      <td>2,700,000.00</td>\n",
       "      <td>114.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>All they risked was everything.</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>False</td>\n",
       "      <td>6.50</td>\n",
       "      <td>17.00</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, 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>Roger Spottiswoode</td>\n",
       "      <td>TriStar Pictures</td>\n",
       "      <td>...</td>\n",
       "      <td>1990-08-10</td>\n",
       "      <td>33,461,269.00</td>\n",
       "      <td>112.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>The few. The proud. The totally insane.</td>\n",
       "      <td>Air America</td>\n",
       "      <td>False</td>\n",
       "      <td>5.30</td>\n",
       "      <td>146.00</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>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>Woody Allen</td>\n",
       "      <td>Orion Pictures</td>\n",
       "      <td>...</td>\n",
       "      <td>1990-12-25</td>\n",
       "      <td>7,331,647.00</td>\n",
       "      <td>102.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alice</td>\n",
       "      <td>False</td>\n",
       "      <td>6.30</td>\n",
       "      <td>57.00</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>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>John Cornell</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>...</td>\n",
       "      <td>1990-12-21</td>\n",
       "      <td>6,939,946.00</td>\n",
       "      <td>95.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Who does he think he is?</td>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>False</td>\n",
       "      <td>5.60</td>\n",
       "      <td>23.00</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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>https://en.wikipedia.org/wiki/A_Fantastic_Woman</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5639354/</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Daniela Vega, Francisco Reyes]</td>\n",
       "      <td>Benjamín Echazarreta</td>\n",
       "      <td>[12 February 2017, (, 2017-02-12, ), (, Berlin...</td>\n",
       "      <td>[Chile, Germany, Spain, United States, [2]]</td>\n",
       "      <td>Sebastián Lelio</td>\n",
       "      <td>[Participant Media (Chile), Piffl Medien (Germ...</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-04-06</td>\n",
       "      <td>3,700,000.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>[{'iso_639_1': 'es', 'name': 'Español'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A Fantastic Woman</td>\n",
       "      <td>False</td>\n",
       "      <td>7.20</td>\n",
       "      <td>13.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Permission_(film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5390066/</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Rebecca Hall, Dan Stevens, Morgan Spector, Fr...</td>\n",
       "      <td>Adam Bricker</td>\n",
       "      <td>[April 22, 2017, (, 2017-04-22, ), (, Tribeca ...</td>\n",
       "      <td>United States</td>\n",
       "      <td>Brian Crano</td>\n",
       "      <td>Good Deed Entertainment</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-04-22</td>\n",
       "      <td>nan</td>\n",
       "      <td>96.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Permission</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Loveless_(film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt6304162/</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Maryana Spivak, Aleksey Rozin, Matvey Novikov...</td>\n",
       "      <td>Mikhail Krichman</td>\n",
       "      <td>[18 May 2017, (, 2017-05-18, ), (, Cannes, ), ...</td>\n",
       "      <td>[Russia, France, Belgium, Germany, [3]]</td>\n",
       "      <td>Andrey Zvyagintsev</td>\n",
       "      <td>[Sony Pictures Releasing, (Russia), [1]]</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>4,800,000.00</td>\n",
       "      <td>128.00</td>\n",
       "      <td>[{'iso_639_1': 'ru', 'name': 'Pусский'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Loveless</td>\n",
       "      <td>False</td>\n",
       "      <td>7.80</td>\n",
       "      <td>26.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Gemini_(2017_film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt5795086/</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...</td>\n",
       "      <td>Andrew Reed</td>\n",
       "      <td>[March 12, 2017, (, 2017-03-12, ), (, SXSW, ),...</td>\n",
       "      <td>United States</td>\n",
       "      <td>Aaron Katz</td>\n",
       "      <td>Neon</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-03-12</td>\n",
       "      <td>200,340.00</td>\n",
       "      <td>92.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Post Production</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gemini</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6051</th>\n",
       "      <td>https://en.wikipedia.org/wiki/How_to_Talk_to_G...</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt3859310/</td>\n",
       "      <td>[\", How to Talk to Girls at Parties, \", by, Ne...</td>\n",
       "      <td>[Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...</td>\n",
       "      <td>Frank G. DeMarco</td>\n",
       "      <td>[May 21, 2017, (, 2017-05-21, ), (, Cannes, ),...</td>\n",
       "      <td>[United Kingdom, United States]</td>\n",
       "      <td>John Cameron Mitchell</td>\n",
       "      <td>[A24, StudioCanal UK]</td>\n",
       "      <td>...</td>\n",
       "      <td>2017-12-27</td>\n",
       "      <td>382,053.00</td>\n",
       "      <td>102.00</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Some girls are out of this world.</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>False</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6051 rows × 37 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",
       "6047    https://en.wikipedia.org/wiki/A_Fantastic_Woman  2018   \n",
       "6048    https://en.wikipedia.org/wiki/Permission_(film)  2018   \n",
       "6049      https://en.wikipedia.org/wiki/Loveless_(film)  2018   \n",
       "6050   https://en.wikipedia.org/wiki/Gemini_(2017_film)  2018   \n",
       "6051  https://en.wikipedia.org/wiki/How_to_Talk_to_G...  2018   \n",
       "\n",
       "                                  imdb_link  \\\n",
       "0     https://www.imdb.com/title/tt0098987/   \n",
       "1     https://www.imdb.com/title/tt0098994/   \n",
       "2     https://www.imdb.com/title/tt0099005/   \n",
       "3     https://www.imdb.com/title/tt0099012/   \n",
       "4     https://www.imdb.com/title/tt0099018/   \n",
       "...                                     ...   \n",
       "6047  https://www.imdb.com/title/tt5639354/   \n",
       "6048  https://www.imdb.com/title/tt5390066/   \n",
       "6049  https://www.imdb.com/title/tt6304162/   \n",
       "6050  https://www.imdb.com/title/tt5795086/   \n",
       "6051  https://www.imdb.com/title/tt3859310/   \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",
       "6047                                                NaN   \n",
       "6048                                                NaN   \n",
       "6049                                                NaN   \n",
       "6050                                                NaN   \n",
       "6051  [\", How to Talk to Girls at Parties, \", by, Ne...   \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",
       "6047                    [Daniela Vega, Francisco Reyes]  Benjamín Echazarreta   \n",
       "6048  [Rebecca Hall, Dan Stevens, Morgan Spector, Fr...          Adam Bricker   \n",
       "6049  [Maryana Spivak, Aleksey Rozin, Matvey Novikov...      Mikhail Krichman   \n",
       "6050  [Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...           Andrew Reed   \n",
       "6051  [Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...      Frank G. DeMarco   \n",
       "\n",
       "                                           Release date  \\\n",
       "0                     [July 11, 1990, (, 1990-07-11, )]   \n",
       "1     [May 17, 1990, (, 1990-05-17, ), (Cannes Film ...   \n",
       "2                   [August 10, 1990, (, 1990-08-10, )]   \n",
       "3                 [December 25, 1990, (, 1990-12-25, )]   \n",
       "4                                     December 19, 1990   \n",
       "...                                                 ...   \n",
       "6047  [12 February 2017, (, 2017-02-12, ), (, Berlin...   \n",
       "6048  [April 22, 2017, (, 2017-04-22, ), (, Tribeca ...   \n",
       "6049  [18 May 2017, (, 2017-05-18, ), (, Cannes, ), ...   \n",
       "6050  [March 12, 2017, (, 2017-03-12, ), (, SXSW, ),...   \n",
       "6051  [May 21, 2017, (, 2017-05-21, ), (, Cannes, ),...   \n",
       "\n",
       "                                          Country               Director  \\\n",
       "0                                   United States           Renny Harlin   \n",
       "1                                   United States            James Foley   \n",
       "2                                   United States     Roger Spottiswoode   \n",
       "3                                   United States            Woody Allen   \n",
       "4                                              US           John Cornell   \n",
       "...                                           ...                    ...   \n",
       "6047  [Chile, Germany, Spain, United States, [2]]        Sebastián Lelio   \n",
       "6048                                United States            Brian Crano   \n",
       "6049      [Russia, France, Belgium, Germany, [3]]     Andrey Zvyagintsev   \n",
       "6050                                United States             Aaron Katz   \n",
       "6051              [United Kingdom, United States]  John Cameron Mitchell   \n",
       "\n",
       "                                            Distributor  ...  \\\n",
       "0                                      20th Century Fox  ...   \n",
       "1                                       Avenue Pictures  ...   \n",
       "2                                      TriStar Pictures  ...   \n",
       "3                                        Orion Pictures  ...   \n",
       "4                                    Paramount Pictures  ...   \n",
       "...                                                 ...  ...   \n",
       "6047  [Participant Media (Chile), Piffl Medien (Germ...  ...   \n",
       "6048                            Good Deed Entertainment  ...   \n",
       "6049           [Sony Pictures Releasing, (Russia), [1]]  ...   \n",
       "6050                                               Neon  ...   \n",
       "6051                              [A24, StudioCanal UK]  ...   \n",
       "\n",
       "     release_date_kaggle              revenue              runtime  \\\n",
       "0             1990-07-11        20,423,389.00               104.00   \n",
       "1             1990-08-24         2,700,000.00               114.00   \n",
       "2             1990-08-10        33,461,269.00               112.00   \n",
       "3             1990-12-25         7,331,647.00               102.00   \n",
       "4             1990-12-21         6,939,946.00                95.00   \n",
       "...                  ...                  ...                  ...   \n",
       "6047          2017-04-06         3,700,000.00               104.00   \n",
       "6048          2017-04-22                  nan                96.00   \n",
       "6049          2017-06-01         4,800,000.00               128.00   \n",
       "6050          2017-03-12           200,340.00                92.00   \n",
       "6051          2017-12-27           382,053.00               102.00   \n",
       "\n",
       "                                       spoken_languages           status  \\\n",
       "0              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "1              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "2     [{'iso_639_1': 'en', 'name': 'English'}, {'iso...         Released   \n",
       "3              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "4              [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "...                                                 ...              ...   \n",
       "6047           [{'iso_639_1': 'es', 'name': 'Español'}]         Released   \n",
       "6048           [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "6049           [{'iso_639_1': 'ru', 'name': 'Pусский'}]         Released   \n",
       "6050           [{'iso_639_1': 'en', 'name': 'English'}]  Post Production   \n",
       "6051           [{'iso_639_1': 'en', 'name': 'English'}]         Released   \n",
       "\n",
       "                                      tagline  \\\n",
       "0         Kojak. Columbo. Dirty Harry. Wimps.   \n",
       "1             All they risked was everything.   \n",
       "2     The few. The proud. The totally insane.   \n",
       "3                                         NaN   \n",
       "4                    Who does he think he is?   \n",
       "...                                       ...   \n",
       "6047                                      NaN   \n",
       "6048                                      NaN   \n",
       "6049                                      NaN   \n",
       "6050                                      NaN   \n",
       "6051        Some girls are out of this world.   \n",
       "\n",
       "                         title_kaggle  video         vote_average  \\\n",
       "0     The Adventures of Ford Fairlane  False                 6.20   \n",
       "1                After Dark, My Sweet  False                 6.50   \n",
       "2                         Air America  False                 5.30   \n",
       "3                               Alice  False                 6.30   \n",
       "4                     Almost an Angel  False                 5.60   \n",
       "...                               ...    ...                  ...   \n",
       "6047                A Fantastic Woman  False                 7.20   \n",
       "6048                       Permission  False                 0.00   \n",
       "6049                         Loveless  False                 7.80   \n",
       "6050                           Gemini  False                 0.00   \n",
       "6051  How to Talk to Girls at Parties  False                 0.00   \n",
       "\n",
       "               vote_count  \n",
       "0                   72.00  \n",
       "1                   17.00  \n",
       "2                  146.00  \n",
       "3                   57.00  \n",
       "4                   23.00  \n",
       "...                   ...  \n",
       "6047                13.00  \n",
       "6048                 1.00  \n",
       "6049                26.00  \n",
       "6050                 0.00  \n",
       "6051                10.00  \n",
       "\n",
       "[6051 rows x 37 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make a function that fills in missing data for a column pair and then drops the redundant column.\n",
    "\n",
    "def fill_missing_kaggle_data(df, kaggle_column, wiki_column):\n",
    "    df[kaggle_column] = df.apply(\n",
    "        lambda row: row[wiki_column] if row[kaggle_column] == 0 else row[kaggle_column]\n",
    "        , axis=1)\n",
    "    df.drop(columns=wiki_column, inplace=True)\n",
    "    \n",
    "# run the function for the three column pairs\n",
    "fill_missing_kaggle_data(movies_df, 'runtime', 'running_time')\n",
    "fill_missing_kaggle_data(movies_df, 'budget_kaggle', 'budget_wiki')\n",
    "fill_missing_kaggle_data(movies_df, 'revenue', 'box_office')\n",
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "video\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False    6051\n",
       "Name: video, dtype: int64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check that there aren't any columns with only one value\n",
    "\n",
    "for col in movies_df.columns:\n",
    "    # convert lists to tuples\n",
    "    lists_to_tuples = lambda x: tuple(x) if type(x) == list else x\n",
    "    value_counts = movies_df[col].apply(lists_to_tuples).value_counts(dropna=False)\n",
    "    num_values = len(value_counts)\n",
    "    if num_values == 1:\n",
    "        print(col)\n",
    "        \n",
    "movies_df['video'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Based on',\n",
       " 'Cinematography',\n",
       " 'Composer(s)',\n",
       " 'Country',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Language',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Release date',\n",
       " 'Starring',\n",
       " 'Writer(s)',\n",
       " 'box_office',\n",
       " 'budget',\n",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'release_date',\n",
       " 'running_time',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>imdb_id</th>\n",
       "      <th>kaggle_id</th>\n",
       "      <th>title</th>\n",
       "      <th>original_title</th>\n",
       "      <th>tagline</th>\n",
       "      <th>belongs_to_collection</th>\n",
       "      <th>wikipedia_url</th>\n",
       "      <th>imdb_link</th>\n",
       "      <th>runtime</th>\n",
       "      <th>budget</th>\n",
       "      <th>...</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>distributor</th>\n",
       "      <th>producers</th>\n",
       "      <th>director</th>\n",
       "      <th>starring</th>\n",
       "      <th>cinematography</th>\n",
       "      <th>editors</th>\n",
       "      <th>writers</th>\n",
       "      <th>composers</th>\n",
       "      <th>based_on</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tt0098987</td>\n",
       "      <td>9548</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>Kojak. Columbo. Dirty Harry. Wimps.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Adventures_o...</td>\n",
       "      <td>https://www.imdb.com/title/tt0098987/</td>\n",
       "      <td>104.00</td>\n",
       "      <td>49,000,000.00</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>20th Century Fox</td>\n",
       "      <td>[Steve Perry, Joel Silver]</td>\n",
       "      <td>Renny Harlin</td>\n",
       "      <td>[Andrew Dice Clay, Wayne Newton, Priscilla Pre...</td>\n",
       "      <td>Oliver Wood</td>\n",
       "      <td>Michael Tronick</td>\n",
       "      <td>[David Arnott, James Cappe]</td>\n",
       "      <td>[Cliff Eidelman, Yello]</td>\n",
       "      <td>[Characters, by Rex Weiner]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tt0098994</td>\n",
       "      <td>25501</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>After Dark, My Sweet</td>\n",
       "      <td>All they risked was everything.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/After_Dark,_My_S...</td>\n",
       "      <td>https://www.imdb.com/title/tt0098994/</td>\n",
       "      <td>114.00</td>\n",
       "      <td>6,000,000.00</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>Avenue Pictures</td>\n",
       "      <td>[Ric Kidney, Robert Redlin]</td>\n",
       "      <td>James Foley</td>\n",
       "      <td>[Jason Patric, Rachel Ward, Bruce Dern, George...</td>\n",
       "      <td>Mark Plummer</td>\n",
       "      <td>Howard E. Smith</td>\n",
       "      <td>[James Foley, Robert Redlin]</td>\n",
       "      <td>Maurice Jarre</td>\n",
       "      <td>[the novel, After Dark, My Sweet, by, Jim Thom...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tt0099005</td>\n",
       "      <td>11856</td>\n",
       "      <td>Air America</td>\n",
       "      <td>Air America</td>\n",
       "      <td>The few. The proud. The totally insane.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Air_America_(film)</td>\n",
       "      <td>https://www.imdb.com/title/tt0099005/</td>\n",
       "      <td>112.00</td>\n",
       "      <td>35,000,000.00</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>TriStar Pictures</td>\n",
       "      <td>Daniel Melnick</td>\n",
       "      <td>Roger Spottiswoode</td>\n",
       "      <td>[Mel Gibson, Robert Downey Jr., Nancy Travis, ...</td>\n",
       "      <td>Roger Deakins</td>\n",
       "      <td>[John Bloom, Lois Freeman-Fox]</td>\n",
       "      <td>[John Eskow, Richard Rush]</td>\n",
       "      <td>Charles Gross</td>\n",
       "      <td>[Air America, by, Christopher Robbins]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tt0099012</td>\n",
       "      <td>8217</td>\n",
       "      <td>Alice</td>\n",
       "      <td>Alice</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Alice_(1990_film)</td>\n",
       "      <td>https://www.imdb.com/title/tt0099012/</td>\n",
       "      <td>102.00</td>\n",
       "      <td>12,000,000.00</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>Orion Pictures</td>\n",
       "      <td>Robert Greenhut</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>[Alec Baldwin, Blythe Danner, Judy Davis, Mia ...</td>\n",
       "      <td>Carlo Di Palma</td>\n",
       "      <td>Susan E. Morse</td>\n",
       "      <td>Woody Allen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tt0099018</td>\n",
       "      <td>25943</td>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>Almost an Angel</td>\n",
       "      <td>Who does he think he is?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Almost_an_Angel</td>\n",
       "      <td>https://www.imdb.com/title/tt0099018/</td>\n",
       "      <td>95.00</td>\n",
       "      <td>25,000,000.00</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>[Paul Hogan, Elias Koteas, Linda Kozlowski]</td>\n",
       "      <td>Russell Boyd</td>\n",
       "      <td>David Stiven</td>\n",
       "      <td>Paul Hogan</td>\n",
       "      <td>Maurice Jarre</td>\n",
       "      <td>NaN</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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>tt5639354</td>\n",
       "      <td>429191</td>\n",
       "      <td>A Fantastic Woman</td>\n",
       "      <td>Una mujer fantástica</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/A_Fantastic_Woman</td>\n",
       "      <td>https://www.imdb.com/title/tt5639354/</td>\n",
       "      <td>104.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'FR', 'name': 'France'}, {'iso...</td>\n",
       "      <td>[Participant Media (Chile), Piffl Medien (Germ...</td>\n",
       "      <td>[Juan de Dios Larraín, Pablo Larraín]</td>\n",
       "      <td>Sebastián Lelio</td>\n",
       "      <td>[Daniela Vega, Francisco Reyes]</td>\n",
       "      <td>Benjamín Echazarreta</td>\n",
       "      <td>Soledad Salfate</td>\n",
       "      <td>[Sebastián Lelio, Gonzalo Maza]</td>\n",
       "      <td>Matthew Herbert</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>tt5390066</td>\n",
       "      <td>390059</td>\n",
       "      <td>Permission</td>\n",
       "      <td>Permission</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Permission_(film)</td>\n",
       "      <td>https://www.imdb.com/title/tt5390066/</td>\n",
       "      <td>96.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>Good Deed Entertainment</td>\n",
       "      <td>[Brian Crano, Rebecca Hall]</td>\n",
       "      <td>Brian Crano</td>\n",
       "      <td>[Rebecca Hall, Dan Stevens, Morgan Spector, Fr...</td>\n",
       "      <td>Adam Bricker</td>\n",
       "      <td>Matt Friedman</td>\n",
       "      <td>Brian Crano</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>tt6304162</td>\n",
       "      <td>429174</td>\n",
       "      <td>Loveless</td>\n",
       "      <td>Нелюбовь</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Loveless_(film)</td>\n",
       "      <td>https://www.imdb.com/title/tt6304162/</td>\n",
       "      <td>128.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'RU', 'name': 'Russia'}, {'iso...</td>\n",
       "      <td>[Sony Pictures Releasing, (Russia), [1]]</td>\n",
       "      <td>[Alexander Rodnyansky, Sergey Melkumov, Gleb F...</td>\n",
       "      <td>Andrey Zvyagintsev</td>\n",
       "      <td>[Maryana Spivak, Aleksey Rozin, Matvey Novikov...</td>\n",
       "      <td>Mikhail Krichman</td>\n",
       "      <td>Anna Mass</td>\n",
       "      <td>[Oleg Negin, Andrey Zvyagintsev]</td>\n",
       "      <td>[Evgueni Galperine, Sacha Galperine]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>tt5795086</td>\n",
       "      <td>412302</td>\n",
       "      <td>Gemini</td>\n",
       "      <td>Gemini</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/Gemini_(2017_film)</td>\n",
       "      <td>https://www.imdb.com/title/tt5795086/</td>\n",
       "      <td>92.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>Neon</td>\n",
       "      <td>[Mynette Louie, Sara Murphy, Adele Romanski]</td>\n",
       "      <td>Aaron Katz</td>\n",
       "      <td>[Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...</td>\n",
       "      <td>Andrew Reed</td>\n",
       "      <td>Aaron Katz</td>\n",
       "      <td>Aaron Katz</td>\n",
       "      <td>Keegan DeWitt</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6051</th>\n",
       "      <td>tt3859310</td>\n",
       "      <td>341689</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>How to Talk to Girls at Parties</td>\n",
       "      <td>Some girls are out of this world.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://en.wikipedia.org/wiki/How_to_Talk_to_G...</td>\n",
       "      <td>https://www.imdb.com/title/tt3859310/</td>\n",
       "      <td>102.00</td>\n",
       "      <td>nan</td>\n",
       "      <td>...</td>\n",
       "      <td>[{'iso_3166_1': 'US', 'name': 'United States o...</td>\n",
       "      <td>[A24, StudioCanal UK]</td>\n",
       "      <td>[Iain Canning, Howard Gertler, John Cameron Mi...</td>\n",
       "      <td>John Cameron Mitchell</td>\n",
       "      <td>[Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...</td>\n",
       "      <td>Frank G. DeMarco</td>\n",
       "      <td>Brian A. Kates</td>\n",
       "      <td>[Philippa Goslett, John Cameron Mitchell]</td>\n",
       "      <td>[Nico Muhly, Jamie Stewart]</td>\n",
       "      <td>[\", How to Talk to Girls at Parties, \", by, Ne...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6051 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        imdb_id  kaggle_id                            title  \\\n",
       "0     tt0098987       9548  The Adventures of Ford Fairlane   \n",
       "1     tt0098994      25501             After Dark, My Sweet   \n",
       "2     tt0099005      11856                      Air America   \n",
       "3     tt0099012       8217                            Alice   \n",
       "4     tt0099018      25943                  Almost an Angel   \n",
       "...         ...        ...                              ...   \n",
       "6047  tt5639354     429191                A Fantastic Woman   \n",
       "6048  tt5390066     390059                       Permission   \n",
       "6049  tt6304162     429174                         Loveless   \n",
       "6050  tt5795086     412302                           Gemini   \n",
       "6051  tt3859310     341689  How to Talk to Girls at Parties   \n",
       "\n",
       "                       original_title  \\\n",
       "0     The Adventures of Ford Fairlane   \n",
       "1                After Dark, My Sweet   \n",
       "2                         Air America   \n",
       "3                               Alice   \n",
       "4                     Almost an Angel   \n",
       "...                               ...   \n",
       "6047             Una mujer fantástica   \n",
       "6048                       Permission   \n",
       "6049                         Нелюбовь   \n",
       "6050                           Gemini   \n",
       "6051  How to Talk to Girls at Parties   \n",
       "\n",
       "                                      tagline belongs_to_collection  \\\n",
       "0         Kojak. Columbo. Dirty Harry. Wimps.                   NaN   \n",
       "1             All they risked was everything.                   NaN   \n",
       "2     The few. The proud. The totally insane.                   NaN   \n",
       "3                                         NaN                   NaN   \n",
       "4                    Who does he think he is?                   NaN   \n",
       "...                                       ...                   ...   \n",
       "6047                                      NaN                   NaN   \n",
       "6048                                      NaN                   NaN   \n",
       "6049                                      NaN                   NaN   \n",
       "6050                                      NaN                   NaN   \n",
       "6051        Some girls are out of this world.                   NaN   \n",
       "\n",
       "                                          wikipedia_url  \\\n",
       "0     https://en.wikipedia.org/wiki/The_Adventures_o...   \n",
       "1     https://en.wikipedia.org/wiki/After_Dark,_My_S...   \n",
       "2      https://en.wikipedia.org/wiki/Air_America_(film)   \n",
       "3       https://en.wikipedia.org/wiki/Alice_(1990_film)   \n",
       "4         https://en.wikipedia.org/wiki/Almost_an_Angel   \n",
       "...                                                 ...   \n",
       "6047    https://en.wikipedia.org/wiki/A_Fantastic_Woman   \n",
       "6048    https://en.wikipedia.org/wiki/Permission_(film)   \n",
       "6049      https://en.wikipedia.org/wiki/Loveless_(film)   \n",
       "6050   https://en.wikipedia.org/wiki/Gemini_(2017_film)   \n",
       "6051  https://en.wikipedia.org/wiki/How_to_Talk_to_G...   \n",
       "\n",
       "                                  imdb_link              runtime  \\\n",
       "0     https://www.imdb.com/title/tt0098987/               104.00   \n",
       "1     https://www.imdb.com/title/tt0098994/               114.00   \n",
       "2     https://www.imdb.com/title/tt0099005/               112.00   \n",
       "3     https://www.imdb.com/title/tt0099012/               102.00   \n",
       "4     https://www.imdb.com/title/tt0099018/                95.00   \n",
       "...                                     ...                  ...   \n",
       "6047  https://www.imdb.com/title/tt5639354/               104.00   \n",
       "6048  https://www.imdb.com/title/tt5390066/                96.00   \n",
       "6049  https://www.imdb.com/title/tt6304162/               128.00   \n",
       "6050  https://www.imdb.com/title/tt5795086/                92.00   \n",
       "6051  https://www.imdb.com/title/tt3859310/               102.00   \n",
       "\n",
       "                   budget  ...  \\\n",
       "0           49,000,000.00  ...   \n",
       "1            6,000,000.00  ...   \n",
       "2           35,000,000.00  ...   \n",
       "3           12,000,000.00  ...   \n",
       "4           25,000,000.00  ...   \n",
       "...                   ...  ...   \n",
       "6047                  nan  ...   \n",
       "6048                  nan  ...   \n",
       "6049                  nan  ...   \n",
       "6050                  nan  ...   \n",
       "6051                  nan  ...   \n",
       "\n",
       "                                   production_countries  \\\n",
       "0     [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "1     [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "2     [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "3     [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "4     [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "...                                                 ...   \n",
       "6047  [{'iso_3166_1': 'FR', 'name': 'France'}, {'iso...   \n",
       "6048  [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "6049  [{'iso_3166_1': 'RU', 'name': 'Russia'}, {'iso...   \n",
       "6050  [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "6051  [{'iso_3166_1': 'US', 'name': 'United States o...   \n",
       "\n",
       "                                            distributor  \\\n",
       "0                                      20th Century Fox   \n",
       "1                                       Avenue Pictures   \n",
       "2                                      TriStar Pictures   \n",
       "3                                        Orion Pictures   \n",
       "4                                    Paramount Pictures   \n",
       "...                                                 ...   \n",
       "6047  [Participant Media (Chile), Piffl Medien (Germ...   \n",
       "6048                            Good Deed Entertainment   \n",
       "6049           [Sony Pictures Releasing, (Russia), [1]]   \n",
       "6050                                               Neon   \n",
       "6051                              [A24, StudioCanal UK]   \n",
       "\n",
       "                                              producers  \\\n",
       "0                            [Steve Perry, Joel Silver]   \n",
       "1                           [Ric Kidney, Robert Redlin]   \n",
       "2                                        Daniel Melnick   \n",
       "3                                       Robert Greenhut   \n",
       "4                                          John Cornell   \n",
       "...                                                 ...   \n",
       "6047              [Juan de Dios Larraín, Pablo Larraín]   \n",
       "6048                        [Brian Crano, Rebecca Hall]   \n",
       "6049  [Alexander Rodnyansky, Sergey Melkumov, Gleb F...   \n",
       "6050       [Mynette Louie, Sara Murphy, Adele Romanski]   \n",
       "6051  [Iain Canning, Howard Gertler, John Cameron Mi...   \n",
       "\n",
       "                   director  \\\n",
       "0              Renny Harlin   \n",
       "1               James Foley   \n",
       "2        Roger Spottiswoode   \n",
       "3               Woody Allen   \n",
       "4              John Cornell   \n",
       "...                     ...   \n",
       "6047        Sebastián Lelio   \n",
       "6048            Brian Crano   \n",
       "6049     Andrey Zvyagintsev   \n",
       "6050             Aaron Katz   \n",
       "6051  John Cameron Mitchell   \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",
       "6047                    [Daniela Vega, Francisco Reyes]  Benjamín Echazarreta   \n",
       "6048  [Rebecca Hall, Dan Stevens, Morgan Spector, Fr...          Adam Bricker   \n",
       "6049  [Maryana Spivak, Aleksey Rozin, Matvey Novikov...      Mikhail Krichman   \n",
       "6050  [Lola Kirke, Zoë Kravitz, Greta Lee, Michelle ...           Andrew Reed   \n",
       "6051  [Elle Fanning, Alex Sharp, Nicole Kidman, Ruth...      Frank G. DeMarco   \n",
       "\n",
       "                             editors  \\\n",
       "0                    Michael Tronick   \n",
       "1                    Howard E. Smith   \n",
       "2     [John Bloom, Lois Freeman-Fox]   \n",
       "3                     Susan E. Morse   \n",
       "4                       David Stiven   \n",
       "...                              ...   \n",
       "6047                 Soledad Salfate   \n",
       "6048                   Matt Friedman   \n",
       "6049                       Anna Mass   \n",
       "6050                      Aaron Katz   \n",
       "6051                  Brian A. Kates   \n",
       "\n",
       "                                        writers  \\\n",
       "0                   [David Arnott, James Cappe]   \n",
       "1                  [James Foley, Robert Redlin]   \n",
       "2                    [John Eskow, Richard Rush]   \n",
       "3                                   Woody Allen   \n",
       "4                                    Paul Hogan   \n",
       "...                                         ...   \n",
       "6047            [Sebastián Lelio, Gonzalo Maza]   \n",
       "6048                                Brian Crano   \n",
       "6049           [Oleg Negin, Andrey Zvyagintsev]   \n",
       "6050                                 Aaron Katz   \n",
       "6051  [Philippa Goslett, John Cameron Mitchell]   \n",
       "\n",
       "                                 composers  \\\n",
       "0                  [Cliff Eidelman, Yello]   \n",
       "1                            Maurice Jarre   \n",
       "2                            Charles Gross   \n",
       "3                                      NaN   \n",
       "4                            Maurice Jarre   \n",
       "...                                    ...   \n",
       "6047                       Matthew Herbert   \n",
       "6048                                   NaN   \n",
       "6049  [Evgueni Galperine, Sacha Galperine]   \n",
       "6050                         Keegan DeWitt   \n",
       "6051           [Nico Muhly, Jamie Stewart]   \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",
       "6047                                                NaN  \n",
       "6048                                                NaN  \n",
       "6049                                                NaN  \n",
       "6050                                                NaN  \n",
       "6051  [\", How to Talk to Girls at Parties, \", by, Ne...  \n",
       "\n",
       "[6051 rows x 31 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reorder the dataframe columns to make the dataset easier to read for the hackathon participants\n",
    "movies_df = movies_df.loc[:, ['imdb_id','id','title_kaggle','original_title','tagline','belongs_to_collection','url','imdb_link',\n",
    "                       'runtime','budget_kaggle','revenue','release_date_kaggle','popularity','vote_average','vote_count',\n",
    "                       'genres','original_language','overview','spoken_languages','Country',\n",
    "                       'production_companies','production_countries','Distributor',\n",
    "                       'Producer(s)','Director','Starring','Cinematography','Editor(s)','Writer(s)','Composer(s)','Based on'\n",
    "                      ]]\n",
    "\n",
    "# rename the dataframe columns to be consistent\n",
    "movies_df.rename({'id':'kaggle_id',\n",
    "                  'title_kaggle':'title',\n",
    "                  'url':'wikipedia_url',\n",
    "                  'budget_kaggle':'budget',\n",
    "                  'release_date_kaggle':'release_date',\n",
    "                  'Country':'country',\n",
    "                  'Distributor':'distributor',\n",
    "                  'Producer(s)':'producers',\n",
    "                  'Director':'director',\n",
    "                  'Starring':'starring',\n",
    "                  'Cinematography':'cinematography',\n",
    "                  'Editor(s)':'editors',\n",
    "                  'Writer(s)':'writers',\n",
    "                  'Composer(s)':'composers',\n",
    "                  'Based on':'based_on'\n",
    "                 }, axis='columns', inplace=True)\n",
    "\n",
    "movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "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>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>count</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>441</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "      <td>804</td>\n",
       "      <td>804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1.50</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2083</td>\n",
       "      <td>2083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1584</td>\n",
       "      <td>1584</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>239376</th>\n",
       "      <td>176267</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239377</th>\n",
       "      <td>176269</td>\n",
       "      <td>3.50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239378</th>\n",
       "      <td>176271</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239379</th>\n",
       "      <td>176273</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239380</th>\n",
       "      <td>176275</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239381 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        movieId               rating  count  timestamp\n",
       "0             1                 0.50    441        441\n",
       "1             1                 1.00    804        804\n",
       "2             1                 1.50    438        438\n",
       "3             1                 2.00   2083       2083\n",
       "4             1                 2.50   1584       1584\n",
       "...         ...                  ...    ...        ...\n",
       "239376   176267                 4.00      1          1\n",
       "239377   176269                 3.50      1          1\n",
       "239378   176271                 5.00      1          1\n",
       "239379   176273                 1.00      1          1\n",
       "239380   176275                 3.00      1          1\n",
       "\n",
       "[239381 rows x 4 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  use a groupby on the \"movieId\" and \"rating\" columns and take the count for each group.\n",
    "rating_counts = ratings.groupby(['movieId','rating'], as_index=False).count() \\\n",
    "                .rename({'userId':'count'}, axis=1)\n",
    "rating_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pivot this data so that movieId is the index, \n",
    "# the columns will be all the rating values, \n",
    "# and the rows will be the counts for each rating value.\n",
    "\n",
    "rating_counts = ratings.groupby(['movieId','rating'], as_index=False).count() \\\n",
    "                .rename({'userId':'count'}, axis=1) \\\n",
    "                .pivot(index='movieId',columns='rating', values='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename the columns so they're easier to understand. \n",
    "# We'll prepend rating_ to each column with a list comprehension:\n",
    "\n",
    "rating_counts.columns = ['rating_' + str(col) for col in rating_counts.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename the columns so they're easier to understand. We'll prepend rating_ to each column with a list comprehension:\n",
    "rating_counts.columns = ['rating_' + str(col) for col in rating_counts.columns]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge rating_counts into movies_df\n",
    "movies_with_ratings_df = pd.merge(movies_df, rating_counts, left_on='kaggle_id', right_index=True, how='left')\n",
    "\n",
    "# fill missing values from the merge\n",
    "movies_with_ratings_df[rating_counts.columns] = movies_with_ratings_df[rating_counts.columns].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create database engine to communicate with SQL server\n",
    "\"postgres://[user]:[password]@[location]:[port]/[database]\"\n",
    "\n",
    "# connection string for local server\n",
    "db_string = f\"postgres://postgres:{db_password}@127.0.0.1:5432/movie_data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create the database engine\n",
    "engine = create_engine(db_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Table 'movies' already exists.",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-97-5719dfaab22c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# save the movies_df DataFrame to a SQL table\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmovies_df\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_sql\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'movies'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcon\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\envs\\PythonData\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(self, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m   2613\u001b[0m             \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2614\u001b[0m             \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2615\u001b[1;33m             \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2616\u001b[0m         )\n\u001b[0;32m   2617\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\envs\\PythonData\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(frame, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m    596\u001b[0m         \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    597\u001b[0m         \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 598\u001b[1;33m         \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    599\u001b[0m     )\n\u001b[0;32m    600\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\envs\\PythonData\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(self, frame, name, if_exists, index, index_label, schema, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m   1391\u001b[0m             \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1392\u001b[0m         )\n\u001b[1;32m-> 1393\u001b[1;33m         \u001b[0mtable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1394\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1395\u001b[0m         \u001b[1;32mfrom\u001b[0m \u001b[0msqlalchemy\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\envs\\PythonData\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mcreate\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    721\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    722\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mif_exists\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"fail\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 723\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"Table '{self.name}' already exists.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    724\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mif_exists\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"replace\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    725\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpd_sql\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop_table\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mschema\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Table 'movies' already exists."
     ]
    }
   ],
   "source": [
    "# save the movies_df DataFrame to a SQL table\n",
    "movies_df.to_sql(name='movies', con=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reimport the CSV using the chunksize= parameter in read_csv()\n",
    "\n",
    "# Step 1: Print number of imported rows\n",
    "\n",
    "# create a variable for the number of rows imported\n",
    "rows_imported = 0\n",
    "\n",
    "# get the start_time from time.time()\n",
    "start_time = time.time()\n",
    "\n",
    "for data in pd.read_csv(f'{file_dir}ratings.csv', chunksize=1000000):\n",
    "\n",
    "    # print out the range of rows that are being imported\n",
    "    print(f'importing rows {rows_imported} to {rows_imported + len(data)}...', end='')\n",
    "\n",
    "    data.to_sql(name='ratings', con=engine, if_exists='append')\n",
    "\n",
    "    # increment the number of rows imported by the size of 'data'\n",
    "    rows_imported += len(data)\n",
    "\n",
    "    # add elapsed time to final print out\n",
    "    # print that the rows have finished importing\n",
    "    print(f'Done. {time.time() - start_time} total seconds elapsed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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