Clean_Practice.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing Dependencies\n",
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "# Import Modules\n",
    "from sqlalchemy import create_engine\n",
    "\n",
    "# db_password\n",
    "from config import db_password"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renaming json file\n",
    "file_dir = 'C:/Users/Greg/Documents/Analysis_Projects/Movies_ETL/Movies-ETL/Data'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:/Users/Greg/Documents/Analysis_Projects/Movies_ETL/Movies-ETL/Data'"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:/Users/Greg/Documents/Analysis_Projects/Movies_ETL/Movies-ETL/Datafilename'"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f'{file_dir}filename'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Storing json file in a dictionary\n",
    "with open(f'{file_dir}/wikipedia.movies.json', mode='r') as file:\n",
    "    wiki_movies_raw = json.load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7311"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking the length of the json file\n",
    "len(wiki_movies_raw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "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": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking integrity of the data\n",
    "# Looking at First 5 records\n",
    "wiki_movies_raw[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "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": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at the Last 5 records\n",
    "wiki_movies_raw[-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "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": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at some records in the middle\n",
    "wiki_movies_raw[3600:3605]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Greg\\anaconda3\\envs\\PythonData\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3063: DtypeWarning: Columns (10) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "# Using pandas to read kaggle csv files\n",
    "kaggle_metadata = pd.read_csv(f'{file_dir}/movies_metadata.csv')\n",
    "ratings = pd.read_csv(f'{file_dir}/ratings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
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       "      <td>NaN</td>\n",
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       "      <td>tt0113228</td>\n",
       "      <td>en</td>\n",
       "      <td>Grumpier Old Men</td>\n",
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       "      <td>...</td>\n",
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       "      <td>Released</td>\n",
       "      <td>Friends are the people who let you be yourself...</td>\n",
       "      <td>Waiting to Exhale</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 96871, 'name': 'Father of the Bride Col...</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 35, 'name': 'Comedy'}]</td>\n",
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       "      <td>en</td>\n",
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       "      <td>Father of the Bride Part II</td>\n",
       "      <td>False</td>\n",
       "      <td>5.7</td>\n",
       "      <td>173.0</td>\n",
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       "   adult                              belongs_to_collection    budget  \\\n",
       "0  False  {'id': 10194, 'name': 'Toy Story Collection', ...  30000000   \n",
       "1  False                                                NaN  65000000   \n",
       "2  False  {'id': 119050, 'name': 'Grumpy Old Men Collect...         0   \n",
       "3  False                                                NaN  16000000   \n",
       "4  False  {'id': 96871, 'name': 'Father of the Bride Col...         0   \n",
       "\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",
       "2          0.0   101.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "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]"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspecting metadata dataset\n",
    "kaggle_metadata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
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       "       adult belongs_to_collection budget  \\\n",
       "45461  False                   NaN      0   \n",
       "45462  False                   NaN      0   \n",
       "45463  False                   NaN      0   \n",
       "45464  False                   NaN      0   \n",
       "45465  False                   NaN      0   \n",
       "\n",
       "                                                  genres  \\\n",
       "45461  [{'id': 18, 'name': 'Drama'}, {'id': 10751, 'n...   \n",
       "45462                      [{'id': 18, 'name': 'Drama'}]   \n",
       "45463  [{'id': 28, 'name': 'Action'}, {'id': 18, 'nam...   \n",
       "45464                                                 []   \n",
       "45465                                                 []   \n",
       "\n",
       "                                   homepage      id    imdb_id  \\\n",
       "45461  http://www.imdb.com/title/tt6209470/  439050  tt6209470   \n",
       "45462                                   NaN  111109  tt2028550   \n",
       "45463                                   NaN   67758  tt0303758   \n",
       "45464                                   NaN  227506  tt0008536   \n",
       "45465                                   NaN  461257  tt6980792   \n",
       "\n",
       "      original_language       original_title  \\\n",
       "45461                fa              رگ خواب   \n",
       "45462                tl  Siglo ng Pagluluwal   \n",
       "45463                en             Betrayal   \n",
       "45464                en  Satana likuyushchiy   \n",
       "45465                en             Queerama   \n",
       "\n",
       "                                                overview  ... release_date  \\\n",
       "45461        Rising and falling between a man and woman.  ...          NaN   \n",
       "45462  An artist struggles to finish his work while a...  ...   2011-11-17   \n",
       "45463  When one of her hits goes wrong, a professiona...  ...   2003-08-01   \n",
       "45464  In a small town live two brothers, one a minis...  ...   1917-10-21   \n",
       "45465  50 years after decriminalisation of homosexual...  ...   2017-06-09   \n",
       "\n",
       "      revenue runtime                          spoken_languages    status  \\\n",
       "45461     0.0    90.0    [{'iso_639_1': 'fa', 'name': 'فارسی'}]  Released   \n",
       "45462     0.0   360.0         [{'iso_639_1': 'tl', 'name': ''}]  Released   \n",
       "45463     0.0    90.0  [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "45464     0.0    87.0                                        []  Released   \n",
       "45465     0.0    75.0  [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "\n",
       "                                          tagline                title  video  \\\n",
       "45461  Rising and falling between a man and woman               Subdue  False   \n",
       "45462                                         NaN  Century of Birthing  False   \n",
       "45463                      A deadly game of wits.             Betrayal  False   \n",
       "45464                                         NaN     Satan Triumphant  False   \n",
       "45465                                         NaN             Queerama  False   \n",
       "\n",
       "      vote_average vote_count  \n",
       "45461          4.0        1.0  \n",
       "45462          9.0        3.0  \n",
       "45463          3.8        6.0  \n",
       "45464          0.0        0.0  \n",
       "45465          0.0        0.0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspecting metadata dataset\n",
    "kaggle_metadata.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>34188</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 28, 'name': 'Action'}, {'id': 878, 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66664</td>\n",
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       "      <td>it</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>[{'iso_639_1': 'de', 'name': 'Deutsch'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shocking Dark</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>[{'id': 10749, 'name': 'Romance'}, {'id': 18, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79234</td>\n",
       "      <td>tt0108235</td>\n",
       "      <td>en</td>\n",
       "      <td>Strelets Neprikayannyy</td>\n",
       "      <td>After discovering a time tunnel to 1960-ies a ...</td>\n",
       "      <td>...</td>\n",
       "      <td>1993-06-06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>[{'iso_639_1': 'ru', 'name': 'Pусский'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Wandering Sagittarius</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>[{'id': 35, 'name': 'Comedy'}]</td>\n",
       "      <td>http://www.christophertitus.com/</td>\n",
       "      <td>327352</td>\n",
       "      <td>tt4816108</td>\n",
       "      <td>en</td>\n",
       "      <td>Christopher Titus: Angry Pursuit of Happiness</td>\n",
       "      <td>Known as one of the best and most prolific com...</td>\n",
       "      <td>...</td>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>We need comedy to get rid of our desire to kill</td>\n",
       "      <td>Christopher Titus: Angry Pursuit of Happiness</td>\n",
       "      <td>False</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16991</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57118</td>\n",
       "      <td>tt1606180</td>\n",
       "      <td>en</td>\n",
       "      <td>That's What I Am</td>\n",
       "      <td>A coming-of-age story that follows 12-year-old...</td>\n",
       "      <td>...</td>\n",
       "      <td>2011-04-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>I'm a Teacher. I'm a Singer. I'm a Writer.</td>\n",
       "      <td>That's What I Am</td>\n",
       "      <td>False</td>\n",
       "      <td>6.7</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31238</th>\n",
       "      <td>False</td>\n",
       "      <td>{'id': 106784, 'name': 'Love in the City Colle...</td>\n",
       "      <td>3500000</td>\n",
       "      <td>[{'id': 35, 'name': 'Comedy'}, {'id': 10749, '...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24686</td>\n",
       "      <td>tt1366687</td>\n",
       "      <td>en</td>\n",
       "      <td>Lyubov V Bolshom Gorode</td>\n",
       "      <td>Three Russian friends work in New York, party ...</td>\n",
       "      <td>...</td>\n",
       "      <td>2009-03-05</td>\n",
       "      <td>9112193.0</td>\n",
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       "      <td>[{'iso_639_1': 'en', 'name': 'English'}, {'iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Love and the City</td>\n",
       "      <td>False</td>\n",
       "      <td>5.1</td>\n",
       "      <td>14.0</td>\n",
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       "    <tr>\n",
       "      <th>14661</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 99, 'name': 'Documentary'}, {'id': 28,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5707</td>\n",
       "      <td>tt0250730</td>\n",
       "      <td>en</td>\n",
       "      <td>Shooting War</td>\n",
       "      <td>A remarkable film that takes a special look at...</td>\n",
       "      <td>...</td>\n",
       "      <td>2000-12-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Shooting War</td>\n",
       "      <td>False</td>\n",
       "      <td>5.3</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41665</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 14, 'name': 'Fantasy'}, {'id': 16, 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20089</td>\n",
       "      <td>tt0279487</td>\n",
       "      <td>ja</td>\n",
       "      <td>支配者の黄昏</td>\n",
       "      <td>Tsunami is an ancient gaurdian fom days long a...</td>\n",
       "      <td>...</td>\n",
       "      <td>1998-01-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>[{'iso_639_1': 'ja', 'name': '日本語'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>The Ultimate Clash Between Good and Evil</td>\n",
       "      <td>Twilight of the Dark Master</td>\n",
       "      <td>False</td>\n",
       "      <td>5.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31116</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 99, 'name': 'Documentary'}]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77171</td>\n",
       "      <td>tt2011972</td>\n",
       "      <td>en</td>\n",
       "      <td>More Brains! A Return to the Living Dead</td>\n",
       "      <td>Retrospective documentary about the making of ...</td>\n",
       "      <td>...</td>\n",
       "      <td>2011-10-18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>More Brains! A Return to the Living Dead</td>\n",
       "      <td>False</td>\n",
       "      <td>7.3</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17816</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 28, 'name': 'Action'}, {'id': 12, 'nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38437</td>\n",
       "      <td>tt0028668</td>\n",
       "      <td>en</td>\n",
       "      <td>Bulldog Drummond Escapes</td>\n",
       "      <td>Bulldog protects an heiress.</td>\n",
       "      <td>...</td>\n",
       "      <td>1937-04-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bulldog Drummond Escapes</td>\n",
       "      <td>False</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42694</th>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>[{'id': 27, 'name': 'Horror'}]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>414910</td>\n",
       "      <td>tt4341528</td>\n",
       "      <td>en</td>\n",
       "      <td>Tonight It's You</td>\n",
       "      <td>CJ ventures out for a late night hook up when ...</td>\n",
       "      <td>...</td>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tonight It's You</td>\n",
       "      <td>False</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       adult                              belongs_to_collection   budget  \\\n",
       "34188  False                                                NaN        0   \n",
       "43680  False                                                NaN        0   \n",
       "42731  False                                                NaN        0   \n",
       "16991  False                                                NaN        0   \n",
       "31238  False  {'id': 106784, 'name': 'Love in the City Colle...  3500000   \n",
       "14661  False                                                NaN        0   \n",
       "41665  False                                                NaN        0   \n",
       "31116  False                                                NaN        0   \n",
       "17816  False                                                NaN        0   \n",
       "42694  False                                                NaN        0   \n",
       "\n",
       "                                                  genres  \\\n",
       "34188  [{'id': 28, 'name': 'Action'}, {'id': 878, 'na...   \n",
       "43680  [{'id': 10749, 'name': 'Romance'}, {'id': 18, ...   \n",
       "42731                     [{'id': 35, 'name': 'Comedy'}]   \n",
       "16991  [{'id': 35, 'name': 'Comedy'}, {'id': 18, 'nam...   \n",
       "31238  [{'id': 35, 'name': 'Comedy'}, {'id': 10749, '...   \n",
       "14661  [{'id': 99, 'name': 'Documentary'}, {'id': 28,...   \n",
       "41665  [{'id': 14, 'name': 'Fantasy'}, {'id': 16, 'na...   \n",
       "31116                [{'id': 99, 'name': 'Documentary'}]   \n",
       "17816  [{'id': 28, 'name': 'Action'}, {'id': 12, 'nam...   \n",
       "42694                     [{'id': 27, 'name': 'Horror'}]   \n",
       "\n",
       "                               homepage      id    imdb_id original_language  \\\n",
       "34188                               NaN   66664  tt0098321                it   \n",
       "43680                               NaN   79234  tt0108235                en   \n",
       "42731  http://www.christophertitus.com/  327352  tt4816108                en   \n",
       "16991                               NaN   57118  tt1606180                en   \n",
       "31238                               NaN   24686  tt1366687                en   \n",
       "14661                               NaN    5707  tt0250730                en   \n",
       "41665                               NaN   20089  tt0279487                ja   \n",
       "31116                               NaN   77171  tt2011972                en   \n",
       "17816                               NaN   38437  tt0028668                en   \n",
       "42694                               NaN  414910  tt4341528                en   \n",
       "\n",
       "                                      original_title  \\\n",
       "34188                                  Shocking Dark   \n",
       "43680                         Strelets Neprikayannyy   \n",
       "42731  Christopher Titus: Angry Pursuit of Happiness   \n",
       "16991                               That's What I Am   \n",
       "31238                        Lyubov V Bolshom Gorode   \n",
       "14661                                   Shooting War   \n",
       "41665                                         支配者の黄昏   \n",
       "31116       More Brains! A Return to the Living Dead   \n",
       "17816                       Bulldog Drummond Escapes   \n",
       "42694                               Tonight It's You   \n",
       "\n",
       "                                                overview  ... release_date  \\\n",
       "34188  In a polluted future Venice researchers work t...  ...   1990-08-22   \n",
       "43680  After discovering a time tunnel to 1960-ies a ...  ...   1993-06-06   \n",
       "42731  Known as one of the best and most prolific com...  ...   2014-09-27   \n",
       "16991  A coming-of-age story that follows 12-year-old...  ...   2011-04-01   \n",
       "31238  Three Russian friends work in New York, party ...  ...   2009-03-05   \n",
       "14661  A remarkable film that takes a special look at...  ...   2000-12-07   \n",
       "41665  Tsunami is an ancient gaurdian fom days long a...  ...   1998-01-21   \n",
       "31116  Retrospective documentary about the making of ...  ...   2011-10-18   \n",
       "17816                       Bulldog protects an heiress.  ...   1937-04-21   \n",
       "42694  CJ ventures out for a late night hook up when ...  ...   2016-04-01   \n",
       "\n",
       "         revenue runtime                                   spoken_languages  \\\n",
       "34188        0.0    90.0  [{'iso_639_1': 'de', 'name': 'Deutsch'}, {'iso...   \n",
       "43680        0.0    96.0           [{'iso_639_1': 'ru', 'name': 'Pусский'}]   \n",
       "42731        0.0   105.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "16991        0.0   101.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "31238  9112193.0    88.0  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...   \n",
       "14661        0.0    88.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "41665        0.0    45.0               [{'iso_639_1': 'ja', 'name': '日本語'}]   \n",
       "31116        0.0   120.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "17816        0.0    67.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "42694        0.0    17.0           [{'iso_639_1': 'en', 'name': 'English'}]   \n",
       "\n",
       "         status                                          tagline  \\\n",
       "34188  Released                                              NaN   \n",
       "43680  Released                                              NaN   \n",
       "42731  Released  We need comedy to get rid of our desire to kill   \n",
       "16991  Released       I'm a Teacher. I'm a Singer. I'm a Writer.   \n",
       "31238  Released                                              NaN   \n",
       "14661  Released                                              NaN   \n",
       "41665  Released         The Ultimate Clash Between Good and Evil   \n",
       "31116  Released                                              NaN   \n",
       "17816  Released                                              NaN   \n",
       "42694  Released                                              NaN   \n",
       "\n",
       "                                               title  video vote_average  \\\n",
       "34188                                  Shocking Dark  False          5.6   \n",
       "43680                          Wandering Sagittarius  False          1.0   \n",
       "42731  Christopher Titus: Angry Pursuit of Happiness  False         10.0   \n",
       "16991                               That's What I Am  False          6.7   \n",
       "31238                              Love and the City  False          5.1   \n",
       "14661                                   Shooting War  False          5.3   \n",
       "41665                    Twilight of the Dark Master  False          5.5   \n",
       "31116       More Brains! A Return to the Living Dead  False          7.3   \n",
       "17816                       Bulldog Drummond Escapes  False          6.0   \n",
       "42694                               Tonight It's You  False          6.0   \n",
       "\n",
       "      vote_count  \n",
       "34188        8.0  \n",
       "43680        1.0  \n",
       "42731        2.0  \n",
       "16991       57.0  \n",
       "31238       14.0  \n",
       "14661        2.0  \n",
       "41665        2.0  \n",
       "31116       11.0  \n",
       "17816        3.0  \n",
       "42694        1.0  \n",
       "\n",
       "[10 rows x 24 columns]"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Random sample from metadata dataset\n",
    "sample_meta = kaggle_metadata.sample(n=10)\n",
    "sample_meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>userId</th>\n",
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       "      <th>rating</th>\n",
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       "      <td>858</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1221</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1246</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1425941556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating   timestamp\n",
       "0       1      110     1.0  1425941529\n",
       "1       1      147     4.5  1425942435\n",
       "2       1      858     5.0  1425941523\n",
       "3       1     1221     5.0  1425941546\n",
       "4       1     1246     5.0  1425941556"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspecting ratings dataset\n",
    "ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "          userId  movieId  rating   timestamp\n",
       "26024284  270896    58559     5.0  1257031564\n",
       "26024285  270896    60069     5.0  1257032032\n",
       "26024286  270896    63082     4.5  1257031764\n",
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       "26024288  270896    71878     2.0  1257031858"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspecting ratings dataset\n",
    "ratings.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "          userId  movieId  rating   timestamp\n",
       "19367159  201134    96079     3.5  1407337064\n",
       "23895038  248169     2598     1.0   956583710\n",
       "5508134    56791     3996     5.0  1160362711\n",
       "16037359  166928    81591     4.0  1337605954\n",
       "9204873    95055      615     3.0   831729287\n",
       "2083469    21652     6365     4.0  1434569799\n",
       "15762348  163963     8970     4.0  1331347849\n",
       "19685262  204458      454     3.0  1096738354\n",
       "19950487  207416    63992     3.0  1484926325\n",
       "25387462  264330     2395     3.5  1431897875"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Random sample from ratings dataset\n",
    "sample_ratings = ratings.sample(n=10)\n",
    "sample_ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Polish</th>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Adventures_o...</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>https://www.imdb.com/title/tt0098987/</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>Renny Harlin</td>\n",
       "      <td>[Steve Perry, Joel Silver]</td>\n",
       "      <td>[David Arnott, James Cappe, Daniel Waters]</td>\n",
       "      <td>[David Arnott, James Cappe]</td>\n",
       "      <td>[Characters, by Rex Weiner]</td>\n",
       "      <td>[Andrew Dice Clay, Wayne Newton, Priscilla Pre...</td>\n",
       "      <td>...</td>\n",
       "      <td>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>1</th>\n",
       "      <td>https://en.wikipedia.org/wiki/After_Dark,_My_S...</td>\n",
       "      <td>1990.0</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>1990.0</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>1990.0</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>1990.0</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",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 193 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 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": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Converting wikipedia movies file to dataframe\n",
    "wiki_movies_df = pd.DataFrame(wiki_movies_raw)\n",
    "wiki_movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['url',\n",
       " 'year',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'Directed by',\n",
       " 'Produced by',\n",
       " 'Screenplay by',\n",
       " 'Story by',\n",
       " 'Based on',\n",
       " 'Starring',\n",
       " 'Narrated by',\n",
       " 'Music by',\n",
       " 'Cinematography',\n",
       " 'Edited by',\n",
       " 'Productioncompany ',\n",
       " 'Distributed by',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Country',\n",
       " 'Language',\n",
       " 'Budget',\n",
       " 'Box office',\n",
       " 'Written by',\n",
       " 'Genre',\n",
       " 'Theme music composer',\n",
       " 'Country of origin',\n",
       " 'Original language(s)',\n",
       " 'Producer(s)',\n",
       " 'Editor(s)',\n",
       " 'Production company(s)',\n",
       " 'Original network',\n",
       " 'Original release',\n",
       " 'Productioncompanies ',\n",
       " 'Executive producer(s)',\n",
       " 'Production location(s)',\n",
       " 'Distributor',\n",
       " 'Picture format',\n",
       " 'Audio format',\n",
       " 'Voices of',\n",
       " 'Followed by',\n",
       " 'Composer(s)',\n",
       " 'Created by',\n",
       " 'Also known as',\n",
       " 'Opening theme',\n",
       " 'No. of episodes',\n",
       " 'Preceded by',\n",
       " 'Author',\n",
       " 'Publisher',\n",
       " 'Publication date',\n",
       " 'Media type',\n",
       " 'Pages',\n",
       " 'ISBN',\n",
       " 'OCLC',\n",
       " 'LC Class',\n",
       " 'Cover artist',\n",
       " 'Series',\n",
       " 'Set in',\n",
       " 'Adaptation by',\n",
       " 'Suggested by',\n",
       " 'Biographical data',\n",
       " 'Born',\n",
       " 'Died',\n",
       " 'Resting place',\n",
       " 'Occupation',\n",
       " 'Years active',\n",
       " 'Spouse(s)',\n",
       " 'Children',\n",
       " 'Parent(s)',\n",
       " 'Genres',\n",
       " 'Instruments',\n",
       " 'Labels',\n",
       " 'Website',\n",
       " 'Traditional',\n",
       " 'Mandarin',\n",
       " 'Type',\n",
       " 'Industry',\n",
       " 'Fate',\n",
       " 'Founded',\n",
       " 'Founder',\n",
       " 'Headquarters',\n",
       " 'Parent',\n",
       " 'Released',\n",
       " 'Recorded',\n",
       " 'Venue',\n",
       " 'Length',\n",
       " 'Label',\n",
       " 'Director',\n",
       " 'Producer',\n",
       " 'Area',\n",
       " 'Coordinates',\n",
       " 'Status',\n",
       " 'Opening date',\n",
       " 'Closing date',\n",
       " 'Replaced',\n",
       " 'Replaced by',\n",
       " 'Name',\n",
       " 'Attraction type',\n",
       " 'Music',\n",
       " 'Duration',\n",
       " 'Simplified Chinese',\n",
       " 'Traditional Chinese',\n",
       " 'Hanyu Pinyin',\n",
       " 'Literal meaning',\n",
       " 'Transcriptions',\n",
       " 'Bopomofo',\n",
       " 'Gwoyeu Romatzyh',\n",
       " 'Wade–Giles',\n",
       " 'IPA',\n",
       " 'Yale Romanization',\n",
       " 'Jyutping',\n",
       " 'Hokkien POJ',\n",
       " 'Animation by',\n",
       " 'Color process',\n",
       " 'Engine(s)',\n",
       " 'Genre(s)',\n",
       " 'Actor control',\n",
       " 'Production company',\n",
       " 'Release(s)',\n",
       " 'Format(s)',\n",
       " 'Simplified',\n",
       " 'Characters',\n",
       " 'Date premiered',\n",
       " 'Place premiered',\n",
       " 'Setting',\n",
       " 'Original language',\n",
       " 'Subject',\n",
       " 'Published',\n",
       " 'Dewey Decimal',\n",
       " 'Text',\n",
       " 'Illustrator',\n",
       " 'Original title',\n",
       " 'Published in English',\n",
       " 'French',\n",
       " 'Developed by',\n",
       " 'Ending theme',\n",
       " 'No. of seasons',\n",
       " 'Nationality',\n",
       " 'Portrayed by',\n",
       " 'Alias',\n",
       " 'Species',\n",
       " 'Gender',\n",
       " 'Family',\n",
       " 'Alma mater',\n",
       " 'Camera setup',\n",
       " 'Novel(s)',\n",
       " 'Comics',\n",
       " 'Film(s)',\n",
       " 'Screen story by',\n",
       " 'Hangul',\n",
       " 'Revised Romanization',\n",
       " 'McCune–Reischauer',\n",
       " 'Developer(s)',\n",
       " 'Publisher(s)',\n",
       " 'Designer(s)',\n",
       " 'Programmer(s)',\n",
       " 'Artist(s)',\n",
       " 'Writer(s)',\n",
       " 'Engine',\n",
       " 'Platform(s)',\n",
       " 'Release',\n",
       " 'Mode(s)',\n",
       " 'Original work',\n",
       " 'Television series',\n",
       " 'Japanese',\n",
       " 'Hepburn',\n",
       " 'Literally',\n",
       " 'Cantonese',\n",
       " 'Full name',\n",
       " 'Height',\n",
       " 'Seasons',\n",
       " 'Chinese',\n",
       " 'Other names',\n",
       " 'Relatives',\n",
       " 'Yiddish',\n",
       " 'Formerly',\n",
       " 'Key people',\n",
       " 'Total assets',\n",
       " 'Owner',\n",
       " 'Number of employees',\n",
       " 'Divisions',\n",
       " 'Subsidiaries',\n",
       " 'Arabic',\n",
       " 'Romanized',\n",
       " 'Predecessor',\n",
       " 'Founders',\n",
       " 'Area served',\n",
       " 'Products',\n",
       " 'Services',\n",
       " 'Russian',\n",
       " 'Hebrew',\n",
       " 'Revenue',\n",
       " 'Operating income',\n",
       " 'Polish']"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Printing list of columns in wiki_movies_df\n",
    "wiki_movies_df.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7076"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using list comprehension to filter data in wikimovies dataframe\n",
    "wiki_movies = [movie for movie in wiki_movies_raw\n",
    "              if ('Director' in movie or 'Directed by' in movie)\n",
    "              and 'imdb_link' in movie and 'No. of episodes' not in movie]\n",
    "len(wiki_movies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "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>Hepburn</th>\n",
       "      <th>Literally</th>\n",
       "      <th>Cantonese</th>\n",
       "      <th>Chinese</th>\n",
       "      <th>Yiddish</th>\n",
       "      <th>Arabic</th>\n",
       "      <th>Romanized</th>\n",
       "      <th>Russian</th>\n",
       "      <th>Hebrew</th>\n",
       "      <th>Polish</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Adventures_o...</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0098987/</td>\n",
       "      <td>The Adventures of Ford Fairlane</td>\n",
       "      <td>Renny Harlin</td>\n",
       "      <td>[Steve Perry, Joel Silver]</td>\n",
       "      <td>[David Arnott, James Cappe, Daniel Waters]</td>\n",
       "      <td>[David Arnott, James Cappe]</td>\n",
       "      <td>[Characters, by Rex Weiner]</td>\n",
       "      <td>[Andrew Dice Clay, Wayne Newton, Priscilla Pre...</td>\n",
       "      <td>...</td>\n",
       "      <td>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>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",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 75 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 75 columns]"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Converting wiki_movies file to dataframe\n",
    "wiki_movies_df1 = pd.DataFrame(wiki_movies)\n",
    "wiki_movies_df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "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": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Seeing at which movies are Arabic\n",
    "wiki_movies_df[wiki_movies_df['Arabic'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "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": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df[wiki_movies_df['Arabic'].notnull()]['url']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "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": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at list of columns\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating empty dictionary to hold alternative titles\n",
    "def clean_movie(movie):\n",
    "    movie = dict(movie) #create a non-destructive copy\n",
    "    alt_titles = {}\n",
    "    \n",
    "    # Creating list to loop through alternative title keys\n",
    "    for key in ['Also known as','Arabic','Cantonese','Chinese','French',\n",
    "                'Hangul','Hebrew','Hepburn','Japanese','Literally',\n",
    "                'Mandarin','McCune–Reischauer','Original title','Polish',\n",
    "                'Revised Romanization','Romanized','Russian',\n",
    "                'Simplified','Traditional','Yiddish']:\n",
    "         if key in movie: # Checking to see if current key exists in movie object\n",
    "            alt_titles[key] = movie[key]\n",
    "            movie.pop(key) # If current key exists in movie object, remove the key-value pairs and add to alternative titles\n",
    "    if len(alt_titles) > 0:\n",
    "        movie['alt_titles'] = alt_titles # Adding alternative dictionary titles to the movie object\n",
    "    \n",
    "    # Dealing with columns with slightly different 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",
    "    \n",
    "    # Consolidating column names\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": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List comprehension for list of cleaned movies\n",
    "clean_movies = [clean_movie(movie) for movie in wiki_movies]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "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": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setting dataframe created from clean_movies\n",
    "wiki_movies_df = pd.DataFrame(clean_movies)\n",
    "\n",
    "# Print out list of columns\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7076\n",
      "7033\n"
     ]
    },
    {
     "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>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": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removing duplicate rows\n",
    "wiki_movies_df['imdb_id'] = wiki_movies_df['imdb_link'].str.extract(r'(tt\\d{7})')\n",
    "print(len(wiki_movies_df))\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": 260,
   "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": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using list comprehension to count null values in each column\n",
    "[[column,wiki_movies_df[column].isnull().sum()] for column in wiki_movies_df.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['url',\n",
       " 'year',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'Based on',\n",
       " 'Starring',\n",
       " 'Cinematography',\n",
       " 'Release date',\n",
       " 'Running time',\n",
       " 'Country',\n",
       " 'Language',\n",
       " 'Budget',\n",
       " 'Box office',\n",
       " 'Director',\n",
       " 'Distributor',\n",
       " 'Editor(s)',\n",
       " 'Composer(s)',\n",
       " 'Producer(s)',\n",
       " 'Production company(s)',\n",
       " 'Writer(s)',\n",
       " 'imdb_id']"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking to see which columns have less than 90 percent of null values\n",
    "[column for column in wiki_movies_df.columns if wiki_movies_df[column].isnull().sum() < len(wiki_movies_df) * 0.9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Deleting columns with less than 10 percent of non-null values and keeping the rest\n",
    "wiki_columns_to_keep = [column for column in wiki_movies_df.columns if wiki_movies_df[column].isnull().sum() < len(wiki_movies_df) * 0.9]\n",
    "wiki_movies_df = wiki_movies_df[wiki_columns_to_keep]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "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",
       "    <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>95 minutes</td>\n",
       "      <td>US</td>\n",
       "      <td>...</td>\n",
       "      <td>$25 million</td>\n",
       "      <td>$6,939,946 (USA)</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>Paramount Pictures</td>\n",
       "      <td>David Stiven</td>\n",
       "      <td>Maurice Jarre</td>\n",
       "      <td>John Cornell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Paul Hogan</td>\n",
       "      <td>tt0099018</td>\n",
       "    </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>7071</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Holmes_%26_Watson</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt1255919/</td>\n",
       "      <td>Holmes &amp; Watson</td>\n",
       "      <td>[Sherlock Holmes, and, Dr. Watson, by, Sir Art...</td>\n",
       "      <td>[Will Ferrell, John C. Reilly, Rebecca Hall, R...</td>\n",
       "      <td>Oliver Wood</td>\n",
       "      <td>[December 25, 2018, (, 2018-12-25, ), (United ...</td>\n",
       "      <td>90 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$42 million</td>\n",
       "      <td>$41.9 million</td>\n",
       "      <td>Etan Cohen</td>\n",
       "      <td>Sony Pictures Releasing</td>\n",
       "      <td>Dean Zimmerman</td>\n",
       "      <td>Mark Mothersbaugh</td>\n",
       "      <td>[Will Ferrell, Adam McKay, Jimmy Miller, Clayt...</td>\n",
       "      <td>[Columbia Pictures, Gary Sanchez Productions, ...</td>\n",
       "      <td>Etan Cohen</td>\n",
       "      <td>tt1255919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7072</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Vice_(2018_film)</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt6266538/</td>\n",
       "      <td>Vice</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Christian Bale, Amy Adams, Steve Carell, Sam ...</td>\n",
       "      <td>Greig Fraser</td>\n",
       "      <td>[December 11, 2018, (, 2018-12-11, ), (, Samue...</td>\n",
       "      <td>132 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$60 million</td>\n",
       "      <td>$76.1 million</td>\n",
       "      <td>Adam McKay</td>\n",
       "      <td>Mirror Releasing</td>\n",
       "      <td>Hank Corwin</td>\n",
       "      <td>Nicholas Britell</td>\n",
       "      <td>[Brad Pitt, Dede Gardner, Jeremy Kleiner, Kevi...</td>\n",
       "      <td>[Plan B Entertainment, Gary Sanchez Production...</td>\n",
       "      <td>Adam McKay</td>\n",
       "      <td>tt6266538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7073</th>\n",
       "      <td>https://en.wikipedia.org/wiki/On_the_Basis_of_Sex</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt4669788/</td>\n",
       "      <td>On the Basis of Sex</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Felicity Jones, Armie Hammer, Justin Theroux,...</td>\n",
       "      <td>Michael Grady</td>\n",
       "      <td>[November 8, 2018, (, 2018-11-08, ), (, AFI Fe...</td>\n",
       "      <td>120 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$20 million</td>\n",
       "      <td>$38.4 million</td>\n",
       "      <td>Mimi Leder</td>\n",
       "      <td>Focus Features</td>\n",
       "      <td>Michelle Tesoro</td>\n",
       "      <td>Mychael Danna</td>\n",
       "      <td>Robert W. Cort</td>\n",
       "      <td>[Focus Features, [1], Participant Media, [1], ...</td>\n",
       "      <td>Daniel Stiepleman</td>\n",
       "      <td>tt4669788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7074</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Destroyer_(2018_...</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt7137380/</td>\n",
       "      <td>Destroyer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Nicole Kidman, Sebastian Stan, Toby Kebbell, ...</td>\n",
       "      <td>Julie Kirkwood</td>\n",
       "      <td>[August 31, 2018, (, 2018-08-31, ), (, Telluri...</td>\n",
       "      <td>123 minutes</td>\n",
       "      <td>United States</td>\n",
       "      <td>...</td>\n",
       "      <td>$9 million</td>\n",
       "      <td>$5.5 million</td>\n",
       "      <td>Karyn Kusama</td>\n",
       "      <td>Mirror Releasing</td>\n",
       "      <td>Plummy Tucker</td>\n",
       "      <td>Theodore Shapiro</td>\n",
       "      <td>[Fred Berger, Phil Hay, Matt Manfredi]</td>\n",
       "      <td>[30West, Automatik Entertainment, Annapurna Pi...</td>\n",
       "      <td>[Phil Hay, Matt Manfredi]</td>\n",
       "      <td>tt7137380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7075</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Black_Mirror:_Ba...</td>\n",
       "      <td>2018</td>\n",
       "      <td>https://www.imdb.com/title/tt9495224/</td>\n",
       "      <td>Bandersnatch</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Fionn Whitehead, Will Poulter, Craig Parkinso...</td>\n",
       "      <td>[Aaron Morton, Jake Polonsky]</td>\n",
       "      <td>[28 December 2018, (, 2018-12-28, )]</td>\n",
       "      <td>Variable; 90 minutes for default path</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>David Slade</td>\n",
       "      <td>Netflix</td>\n",
       "      <td>Tony Kearns</td>\n",
       "      <td>Brian Reitzell</td>\n",
       "      <td>Russell McLean</td>\n",
       "      <td>[House of Tomorrow, Netflix]</td>\n",
       "      <td>Charlie Brooker</td>\n",
       "      <td>tt9495224</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7033 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",
       "4         https://en.wikipedia.org/wiki/Almost_an_Angel  1990   \n",
       "...                                                 ...   ...   \n",
       "7071    https://en.wikipedia.org/wiki/Holmes_%26_Watson  2018   \n",
       "7072     https://en.wikipedia.org/wiki/Vice_(2018_film)  2018   \n",
       "7073  https://en.wikipedia.org/wiki/On_the_Basis_of_Sex  2018   \n",
       "7074  https://en.wikipedia.org/wiki/Destroyer_(2018_...  2018   \n",
       "7075  https://en.wikipedia.org/wiki/Black_Mirror:_Ba...  2018   \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",
       "7071  https://www.imdb.com/title/tt1255919/                  Holmes & Watson   \n",
       "7072  https://www.imdb.com/title/tt6266538/                             Vice   \n",
       "7073  https://www.imdb.com/title/tt4669788/              On the Basis of Sex   \n",
       "7074  https://www.imdb.com/title/tt7137380/                        Destroyer   \n",
       "7075  https://www.imdb.com/title/tt9495224/                     Bandersnatch   \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",
       "7071  [Sherlock Holmes, and, Dr. Watson, by, Sir Art...   \n",
       "7072                                                NaN   \n",
       "7073                                                NaN   \n",
       "7074                                                NaN   \n",
       "7075                                                NaN   \n",
       "\n",
       "                                               Starring  \\\n",
       "0     [Andrew Dice Clay, Wayne Newton, Priscilla Pre...   \n",
       "1     [Jason Patric, Rachel Ward, Bruce Dern, George...   \n",
       "2     [Mel Gibson, Robert Downey Jr., Nancy Travis, ...   \n",
       "3     [Alec Baldwin, Blythe Danner, Judy Davis, Mia ...   \n",
       "4           [Paul Hogan, Elias Koteas, Linda Kozlowski]   \n",
       "...                                                 ...   \n",
       "7071  [Will Ferrell, John C. Reilly, Rebecca Hall, R...   \n",
       "7072  [Christian Bale, Amy Adams, Steve Carell, Sam ...   \n",
       "7073  [Felicity Jones, Armie Hammer, Justin Theroux,...   \n",
       "7074  [Nicole Kidman, Sebastian Stan, Toby Kebbell, ...   \n",
       "7075  [Fionn Whitehead, Will Poulter, Craig Parkinso...   \n",
       "\n",
       "                     Cinematography  \\\n",
       "0                       Oliver Wood   \n",
       "1                      Mark Plummer   \n",
       "2                     Roger Deakins   \n",
       "3                    Carlo Di Palma   \n",
       "4                      Russell Boyd   \n",
       "...                             ...   \n",
       "7071                    Oliver Wood   \n",
       "7072                   Greig Fraser   \n",
       "7073                  Michael Grady   \n",
       "7074                 Julie Kirkwood   \n",
       "7075  [Aaron Morton, Jake Polonsky]   \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",
       "7071  [December 25, 2018, (, 2018-12-25, ), (United ...   \n",
       "7072  [December 11, 2018, (, 2018-12-11, ), (, Samue...   \n",
       "7073  [November 8, 2018, (, 2018-11-08, ), (, AFI Fe...   \n",
       "7074  [August 31, 2018, (, 2018-08-31, ), (, Telluri...   \n",
       "7075               [28 December 2018, (, 2018-12-28, )]   \n",
       "\n",
       "                               Running time         Country  ...       Budget  \\\n",
       "0                               102 minutes   United States  ...  $20 million   \n",
       "1                               114 minutes   United States  ...   $6 million   \n",
       "2                               113 minutes   United States  ...  $35 million   \n",
       "3                               106 minutes   United States  ...  $12 million   \n",
       "4                                95 minutes              US  ...  $25 million   \n",
       "...                                     ...             ...  ...          ...   \n",
       "7071                             90 minutes   United States  ...  $42 million   \n",
       "7072                            132 minutes   United States  ...  $60 million   \n",
       "7073                            120 minutes   United States  ...  $20 million   \n",
       "7074                            123 minutes   United States  ...   $9 million   \n",
       "7075  Variable; 90 minutes for default path  United Kingdom  ...          NaN   \n",
       "\n",
       "            Box office            Director              Distributor  \\\n",
       "0        $21.4 million        Renny Harlin         20th Century Fox   \n",
       "1         $2.7 million         James Foley          Avenue Pictures   \n",
       "2          $57,718,089  Roger Spottiswoode         TriStar Pictures   \n",
       "3           $7,331,647         Woody Allen           Orion Pictures   \n",
       "4     $6,939,946 (USA)        John Cornell       Paramount Pictures   \n",
       "...                ...                 ...                      ...   \n",
       "7071     $41.9 million          Etan Cohen  Sony Pictures Releasing   \n",
       "7072     $76.1 million          Adam McKay         Mirror Releasing   \n",
       "7073     $38.4 million          Mimi Leder           Focus Features   \n",
       "7074      $5.5 million        Karyn Kusama         Mirror Releasing   \n",
       "7075               NaN         David Slade                  Netflix   \n",
       "\n",
       "                           Editor(s)              Composer(s)  \\\n",
       "0                    Michael Tronick  [Cliff Eidelman, Yello]   \n",
       "1                    Howard E. Smith            Maurice Jarre   \n",
       "2     [John Bloom, Lois Freeman-Fox]            Charles Gross   \n",
       "3                     Susan E. Morse                      NaN   \n",
       "4                       David Stiven            Maurice Jarre   \n",
       "...                              ...                      ...   \n",
       "7071                  Dean Zimmerman        Mark Mothersbaugh   \n",
       "7072                     Hank Corwin         Nicholas Britell   \n",
       "7073                 Michelle Tesoro            Mychael Danna   \n",
       "7074                   Plummy Tucker         Theodore Shapiro   \n",
       "7075                     Tony Kearns           Brian Reitzell   \n",
       "\n",
       "                                            Producer(s)  \\\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",
       "7071  [Will Ferrell, Adam McKay, Jimmy Miller, Clayt...   \n",
       "7072  [Brad Pitt, Dede Gardner, Jeremy Kleiner, Kevi...   \n",
       "7073                                     Robert W. Cort   \n",
       "7074             [Fred Berger, Phil Hay, Matt Manfredi]   \n",
       "7075                                     Russell McLean   \n",
       "\n",
       "                                  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",
       "7071  [Columbia Pictures, Gary Sanchez Productions, ...   \n",
       "7072  [Plan B Entertainment, Gary Sanchez Production...   \n",
       "7073  [Focus Features, [1], Participant Media, [1], ...   \n",
       "7074  [30West, Automatik Entertainment, Annapurna Pi...   \n",
       "7075                       [House of Tomorrow, Netflix]   \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",
       "4                       Paul Hogan  tt0099018  \n",
       "...                            ...        ...  \n",
       "7071                    Etan Cohen  tt1255919  \n",
       "7072                    Adam McKay  tt6266538  \n",
       "7073             Daniel Stiepleman  tt4669788  \n",
       "7074     [Phil Hay, Matt Manfredi]  tt7137380  \n",
       "7075               Charlie Brooker  tt9495224  \n",
       "\n",
       "[7033 rows x 21 columns]"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wiki_movies_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "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",
       " 'imdb_id',\n",
       " 'imdb_link',\n",
       " 'title',\n",
       " 'url',\n",
       " 'year']"
      ]
     },
     "execution_count": 264,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cheking how many columns we have with this removal\n",
    "sorted(wiki_movies_df.columns.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "url                      object\n",
       "year                      int64\n",
       "imdb_link                object\n",
       "title                    object\n",
       "Based on                 object\n",
       "Starring                 object\n",
       "Cinematography           object\n",
       "Release date             object\n",
       "Running time             object\n",
       "Country                  object\n",
       "Language                 object\n",
       "Budget                   object\n",
       "Box office               object\n",
       "Director                 object\n",
       "Distributor              object\n",
       "Editor(s)                object\n",
       "Composer(s)              object\n",
       "Producer(s)              object\n",
       "Production company(s)    object\n",
       "Writer(s)                object\n",
       "imdb_id                  object\n",
       "dtype: object"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking data types of each column in the dataset\n",
    "wiki_movies_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moving towards placing correct datatypes for each column\n",
    "box_office = wiki_movies_df['Box office'].dropna() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "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": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Before using regular expressions we must see which data are not strings\n",
    "# as regular expressions can only be used on strings.\n",
    "\n",
    "# Using a lambda function instead of is_not_a_string function\n",
    "box_office[box_office.map(lambda x: type(x) != str)]\n",
    "\n",
    "# Making 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": 268,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Many lists in our dataset.  Need to join lists to make one string.\n",
    "# Using space as our joining character and applying join function only when\n",
    "# our data points are lists.\n",
    "import re\n",
    "\n",
    "box_office = box_office.apply(lambda x: ' '.join(x) if type(x) == list else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parsing through the box office data \n",
    "# Creating form for box office data in numerical values\n",
    "# We use \\ to slip the $ pass the back door \\$\n",
    "# d identifies numbers \\$d\n",
    "# + sign after the d represents one or more digits \\$d+\n",
    "# Identify decimal point as an optional character but decimal point is a special character like $\n",
    "# Will give decimal point an access pass with \\$d+\\.\n",
    "# But decimal point is optional, so we use special character ? to represent optional \\$d+\\.?\n",
    "# There may be an arbitrary number of digits after the decimal point, so our regex is \\d*\n",
    "# There may be a space after the number and before million or billion, so \\s is whitespace\n",
    "# But we use * to cover for if there are more than one whitespaces \\$d+\\.?\\d*\\s*\n",
    "# Matching million or billion with a character set [mb]illion\n",
    "# Full regex is now \\$d+\\.?\\d*\\s*[mb]illion\n",
    "# We want the box office numbers that escape this expression to remain so we put an r before the regex\n",
    "\n",
    "\n",
    "form_one = r'\\$\\d+\\.?\\d*\\s*[mb]illion'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3896"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# contains() method willbe used later to count uppercase and lowercase letters as the same\n",
    "\n",
    "box_office.str.contains(form_one, flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1544"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating form for box office data in alphabetical characters\n",
    "# We use \\ to slip the $ pass the back door \\$\n",
    "# A group of 1 to 3 digits (\\d represents digits)\n",
    "# One through Three repetitions is represented by {1,3}  \\$\\d{1,3}\n",
    "# Expression to match at least one group starting with a comma and followed by exactly three digits\n",
    "# comma and three digits ,\\d{3}\n",
    "# To match a repitition of this comma and three digits we put them in parantheses and follow it with a plus sign\n",
    "# (,\\d{3})+  This is also a non-capturing group, so we will add  a question mark and a colon before the comma\n",
    "# (?:,\\d{3})+\n",
    "# Full regex now becomes \\$\\d{1,3}(?:,\\d{3})+\n",
    "\n",
    "\n",
    "form_two = r'\\$\\d{1,3}(?:,\\d{3})+'\n",
    "box_office.str.contains(form_two, flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Checking to see if there are any box office data that are described by both forms\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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "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                         $6.9 millon\n",
       "Name: Box office, dtype: object"
      ]
     },
     "execution_count": 273,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "box_office[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(box_office[~matches_form_one & ~matches_form_two])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We need to address the following problems\n",
    "# 1. Some values have spaces in between the dollar sign and the number.\n",
    "# 2. Some values use a period as a thousands separator, not a comma.\n",
    "# 3. Some values are given as a range.\n",
    "# 4. “Million” is sometimes misspelled as “millon.”\n",
    "\n",
    "# Addressing problem 1.\n",
    "#form_one = r'\\$\\s*\\d+\\.?\\d*\\s*[mb]illion'\n",
    "#form_two = r'\\$\\s*\\d{1,3}(?:,\\d{3})+'\n",
    "\n",
    "# Addressing problem 2.\n",
    "#form_two = r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)'\n",
    "\n",
    "# Addressing problem 3.\n",
    "#box_office = box_office.str.replace(r'\\$.*[-—–](?![a-z])', '$', regex=True)\n",
    "\n",
    "# Addressing problem 4.\n",
    "#form_one = r'\\$\\s*\\d+\\.?\\d*\\s*[mb]illi?on'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "form_one = r'\\$\\s*\\d+\\.?\\d*\\s*[mb]illi?on'\n",
    "form_two = r'\\$\\s*\\d{1,3}(?:[,\\.]\\d{3})+(?!\\s[mb]illion)'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "box_office = box_office.str.replace(r'\\$.*[-—–](?![a-z])', '$', regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "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>$21.4 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>$2.7 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>$57,718,089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>$7,331,647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>$6,939,946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7070</th>\n",
       "      <td>$19.4 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7071</th>\n",
       "      <td>$41.9 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7072</th>\n",
       "      <td>$76.1 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7073</th>\n",
       "      <td>$38.4 million</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7074</th>\n",
       "      <td>$5.5 million</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5485 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  0\n",
       "0     $21.4 million\n",
       "1      $2.7 million\n",
       "2       $57,718,089\n",
       "3        $7,331,647\n",
       "4        $6,939,946\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",
       "\n",
       "[5485 rows x 1 columns]"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "box_office.str.extract(f'({form_one}|{form_two})')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to turn the extracted values into a numeric value\n",
    "\n",
    "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": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the box office values to numeric values\n",
    "wiki_movies_df['box_office'] = box_office.str.extract(f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping box office column\n",
    "wiki_movies_df.drop('Box office', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a budget variable\n",
    "budget = wiki_movies_df['Budget'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting any lists to strings\n",
    "budget = budget.map(lambda x: ' '.join(x) if type(x) == list else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing any values between a dollar sign and a hyphen\n",
    "budget = budget.str.replace(r'\\$.*[-—–](?![a-z])', '$', regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "136                         Unknown\n",
       "204     60 million Norwegian Kroner\n",
       "478                         Unknown\n",
       "973             $34 [3] [4] million\n",
       "1126               $120 [4] million\n",
       "1226                        Unknown\n",
       "1278                            HBO\n",
       "1374                     £6,000,000\n",
       "1397                     13 million\n",
       "1480                   £2.8 million\n",
       "1734                   CAD2,000,000\n",
       "1913     PHP 85 million (estimated)\n",
       "1948                    102,888,900\n",
       "1953                   3,500,000 DM\n",
       "1973                     ₤2,300,874\n",
       "2281                     $14 milion\n",
       "2451                     ₤6,350,000\n",
       "3144                   € 40 million\n",
       "3360               $150 [6] million\n",
       "3418                        $218.32\n",
       "3802                   £4.2 million\n",
       "3906                            N/A\n",
       "3959                    760,000 USD\n",
       "4470                       19 crore\n",
       "4641                    £17 million\n",
       "5034              $$200 [4] million\n",
       "5055           $155 [2] [3] million\n",
       "5419                $40 [4] million\n",
       "5424                            N/A\n",
       "5447                     £4 million\n",
       "5671                    €14 million\n",
       "5687                   $ dead link]\n",
       "6385               £ 12 million [3]\n",
       "6593                     £3 million\n",
       "6821                  £12.9 million\n",
       "6843                      3.5 crore\n",
       "6895                        919,000\n",
       "7070                   €4.3 million\n",
       "Name: Budget, dtype: object"
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Parse through box office data  and apply without modifications to budget data\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",
    "budget[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "136                         Unknown\n",
       "204     60 million Norwegian Kroner\n",
       "478                         Unknown\n",
       "973                     $34 million\n",
       "1126                   $120 million\n",
       "1226                        Unknown\n",
       "1278                            HBO\n",
       "1374                     £6,000,000\n",
       "1397                     13 million\n",
       "1480                   £2.8 million\n",
       "1734                   CAD2,000,000\n",
       "1913     PHP 85 million (estimated)\n",
       "1948                    102,888,900\n",
       "1953                   3,500,000 DM\n",
       "1973                     ₤2,300,874\n",
       "2281                     $14 milion\n",
       "2451                     ₤6,350,000\n",
       "3144                   € 40 million\n",
       "3360                   $150 million\n",
       "3418                        $218.32\n",
       "3802                   £4.2 million\n",
       "3906                            N/A\n",
       "3959                    760,000 USD\n",
       "4470                       19 crore\n",
       "4641                    £17 million\n",
       "5034                  $$200 million\n",
       "5055                   $155 million\n",
       "5419                    $40 million\n",
       "5424                            N/A\n",
       "5447                     £4 million\n",
       "5671                    €14 million\n",
       "5687                   $ dead link]\n",
       "6385                  £ 12 million \n",
       "6593                     £3 million\n",
       "6821                  £12.9 million\n",
       "6843                      3.5 crore\n",
       "6895                        919,000\n",
       "7070                   €4.3 million\n",
       "Name: Budget, dtype: object"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removing citation references\n",
    "budget = budget.str.replace(r'\\[\\d+\\]\\s*', '')\n",
    "budget[~matches_form_one & ~matches_form_two]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the box office values, changing “box_office” to “budget”\n",
    "wiki_movies_df['budget'] = budget.str.extract(f'({form_one}|{form_two})', flags=re.IGNORECASE)[0].apply(parse_dollars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop original Budget column\n",
    "wiki_movies_df.drop('Budget', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Working towards parsing release date\n",
    "# Make variable that holds the non-null values\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": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Full month name, one- to two-digit day, four-digit year\n",
    "date_form_one = r'(?:January|February|March|April|May|June|July|August|September|October|November|December)\\s[123]\\d,\\s\\d{4}'\n",
    "\n",
    "# Four-digit year, two-digit month, two-digit day, with any separator \n",
    "date_form_two = r'\\d{4}.[01]\\d.[123]\\d'\n",
    "\n",
    "# Full month name, four-digit year\n",
    "date_form_three = r'(?:January|February|March|April|May|June|July|August|September|October|November|December)\\s\\d{4}'\n",
    "\n",
    "# Four-digit year\n",
    "date_form_four = r'\\d{4}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "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": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the dates with this code\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": 292,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instead of creating our own function to parse data, we use built-in to_datetime() method\n",
    "# infer_datetime_format is set to True as there are different date formats\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": 293,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Working towards parsing Running Time\n",
    "# First a variable to hold the non-null values of Release date (conversion of list to strings)\n",
    "running_time = wiki_movies_df['Running time'].dropna().apply(lambda x: ' '.join(x) if type(x) == list else x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6528"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using string boundaries to see how running times look exactly\n",
    "running_time.str.contains(r'^\\d*\\s*minutes$', flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9                                                 102 min\n",
       "26                                                 93 min\n",
       "28                                                32 min.\n",
       "34                                                101 min\n",
       "35                                                 97 min\n",
       "                              ...                        \n",
       "6500       114 minutes [1] 120 minutes (extended edition)\n",
       "6643                                             104 mins\n",
       "6709    90 minutes (theatrical) [1] 91 minutes (unrate...\n",
       "7057    108 minutes (Original cut) 98 minutes (UK cut)...\n",
       "7075                Variable; 90 minutes for default path\n",
       "Name: Running time, Length: 366, dtype: object"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Above code returned 6528 entries\n",
    "# Checking to see what the other 366 entries look like\n",
    "running_time[running_time.str.contains(r'^\\d*\\s*minutes$', flags=re.IGNORECASE) != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6877"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Searching up only to the letter m\n",
    "running_time.str.contains(r'^\\d*\\s*m', flags=re.IGNORECASE).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "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": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This code provides the remainder after the letter m\n",
    "running_time[running_time.str.contains(r'^\\d*\\s*m', flags=re.IGNORECASE) != True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extracting values\n",
    "# Extracting only digits so we use capture groups around the \\d instances\n",
    "# And also add an alternating character\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": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Above code is for all strings\n",
    "# Need to convert them to numeric\n",
    "# Using the to_numeric() method and setting errors argument to 'coerce'\n",
    "# Coercing the errors will set the empty strings into Not a Number (NaN) \n",
    "# Use fillna() to change NaNs to zeros\n",
    "running_time_extract = running_time_extract.apply(lambda col: pd.to_numeric(col, errors='coerce')).fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert hour capture groups and minute capture groups to minutes if the pure minutes capture groups is zero\n",
    "# Saving the output to wiki_movies_df\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": 301,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping Running time from the dataset\n",
    "wiki_movies_df.drop('Running time', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "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": 302,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Working towards cleaning the Kaggle Data\n",
    "# Looking at data types for Kaggle Data Set\n",
    "kaggle_metadata.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "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": 303,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Before converting 'adult' and 'video' columns we need to check to see if there are in boolean form\n",
    "kaggle_metadata['adult'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>vote_average</th>\n",
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       "      <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",
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       "      <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": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removing bad data\n",
    "kaggle_metadata[~kaggle_metadata['adult'].isin(['True','False'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Keep rows where 'adult' column is false and then drop the 'adult' column\n",
    "kaggle_metadata = kaggle_metadata[kaggle_metadata['adult'] == 'False'].drop('adult',axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    45358\n",
       "True        93\n",
       "Name: video, dtype: int64"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at values in the video column\n",
    "kaggle_metadata['video'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        False\n",
       "1        False\n",
       "2        False\n",
       "3        False\n",
       "4        False\n",
       "         ...  \n",
       "45461    False\n",
       "45462    False\n",
       "45463    False\n",
       "45464    False\n",
       "45465    False\n",
       "Name: video, Length: 45454, dtype: bool"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert data types\n",
    "# Create boolean column\n",
    "kaggle_metadata['video'] == 'True'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assigning it back to video\n",
    "kaggle_metadata['video'] = kaggle_metadata['video'] == 'True'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using the to_numeric() method \n",
    "# Setting the errors argument to 'raise' so we can know if there is any data that can't be \n",
    "# converted to numbers\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": 310,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting release date to datetime\n",
    "# Using pandas built-in datetime() function\n",
    "kaggle_metadata['release_date'] = pd.to_datetime(kaggle_metadata['release_date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "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": [
    "# Performing reasonability checks on ratings data\n",
    "# null_counts is set to True as the dataset has a large number of rows\n",
    "ratings.info(null_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "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": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Specifying in to_datetime() that the origin is unix and the time unit is seconds\n",
    "pd.to_datetime(ratings['timestamp'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assigning to timestamp column\n",
    "ratings['timestamp'] = pd.to_datetime(ratings['timestamp'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2.602429e+07\n",
       "mean     3.528090e+00\n",
       "std      1.065443e+00\n",
       "min      5.000000e-01\n",
       "25%      3.000000e+00\n",
       "50%      3.500000e+00\n",
       "75%      4.000000e+00\n",
       "max      5.000000e+00\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 314,
     "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": [
    "# Getting a sense of how the dataset is distributed\n",
    "ratings['rating'].plot(kind='hist')\n",
    "ratings['rating'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merging datasets\n",
    "movies_df = pd.merge(wiki_movies_df, kaggle_metadata, on='imdb_id', suffixes=['_wiki','_kaggle'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "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>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": 316,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Working on printing out the list of columns to find out which ones are redundant\n",
    "# Taking a quick look at some of the titles\n",
    "movies_df[['title_wiki','title_kaggle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "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>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": 317,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Looking at rows where titles do not match\n",
    "movies_df[movies_df['title_wiki'] != movies_df['title_kaggle']][['title_wiki','title_kaggle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "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",
       "  </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": 318,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Confirming that there aren't any missing titles in the Kaggle dataset\n",
    "movies_df[(movies_df['title_kaggle'] == '') | (movies_df['title_kaggle'].isnull())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28d019df648>"
      ]
     },
     "execution_count": 319,
     "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": [
    "# Doing scatter plot and fill in any missing values with zero\n",
    "movies_df.fillna(0).plot(x='running_time', y='runtime', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28d01a20048>"
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Wv5PKZ2Yr3L0x02OFDCB/PX7b3f8APAz8uLfnuPub7r4yuL0TeJnY4rVE5wOLPOZZYEyQRETS5Cr8dtFtyzI+77uPvwoYnz5lJr+5+mR+u3Zz2jUgNoPoGw+vLVlhudT4uyJOd5SCXqtSi9/J4FZIN9E0M/sSgJnVA78CXsv3yWY2AzgaeC7locnAhoT7raQnDMzscjNrMrOmLVu2FBC2DCXx1cKJ4oO9be0drFi/I+Pzog4d3VG+/1QLm7bvzXiNlzZt58lX3iZslvZYsdYWZIq/0Nfq7Xcg0leFDCB/Erg7SAinEusi+m4+TzSzkcBi4LPunvq/NVNpsLS+q2BntYUQ6yYqIG4ZQrLN/V+zcTsfWfhMxrGBRLEPUU+7xt7uCJctaqI2HOoZR0i8frHWFmSKv9DX0voHKYWcLQMzOyYY1D2a2OY2HyHWIvhDPoO9ZlZLLBHc7e6/zHBKKzA14f4UcgxMS/VKLfxWF4azZx/IDb9ew96uXKkg9qF55KTRSdeorwnh7nR0O+0d+xLBiLpwn9YW9Dawmxp/bdioCVHQOgYVv5NSyDmAbGZP9vKwu/tpvTzXgJ8A72YrcW1mZxPbKS0+gHyzux/XW0waQJa29g6uf2ANj655K+s5IWBGwzA27ejMONAa34py+54urrx7JTs7unueO6I+zA3nHsmpR7ynJLuaJW6DCfRpHUOlbaUpla+3AeSc3UTufmqeL/J37v6TlMPzgU8AL5pZc3DsX4BpwbVvBx4hlghagN3EuqNEerV1V2eviWBYbYinrzuNhpH1WT804+sH2to70rpdIlEvOBEkDuzmKmyXunahLx/mWv8gxVRobaLeXE2sFdAj2A4zy3YhPec4cGUR45Ah7oGVG7hj2bqMj9WHQ1iIpG6TXB+a8W6Xa1O+0Rf6QVvJu5qJ5FLMZNDrh75IMbz/m7/jrR2dWR//zw/PYd4hDQV/+Baj7IQGdmUwK2RqaS6a4SMl8/u1b/GR2//YayJYMG8a58yZ1NP1U+jq3IaR9cyZOqbP3+LzHdjVymGpRGoZSMU75dtP8EZb9jn07504ilsuPrpnw/pyrs7N1cLQymGpVIWsQD4ox7GnixKRSIJP3vV8r4kA4B9OOqgnEVTC6txsLYxKiE0km0K6iRZnOHZ//Ia7X9X/cET2ufzHz/Hkq72vNp+4fx0fOmbfMpXWrXvwaHKPpUe9IlbnauWwVLKc3UTBvgVHAqPN7G8THtqf2I5nIkWXqdhcqjDwpbNmJR0bURemI5KcDDoizoi6cDHD6xMNMEsly6dlcDhwDjAGODfh5xjgstKFJtXqmp+vzOu8CKR1s+zqjDCsNvmf9bDa9BIT5aCVw1LJ8ll0tgRYYmbz3P2ZAYhJqtjv177FA6vezPv81Hn82b5l9/fbd3zh2oi6MLs6I32eftrbALNWFEs5FTKbqM3Mfg9McPfZZnYUcJ67/1uJYpMq88HvPsWrm3f1ek59jdHRva8bKLWbpVgLyBLFZwAB7O2KUh82LGR9ngmUaRGcZhlJueW9uY2Z/QH4AnCHux8dHFvj7rNLGF9Gqk00tNzx5Gvc/dx61m/b2+t5NSG44bzZeW08U6xv2W3tHcy/8YmMRfASS170R6bXKNa1RRL1qzZRgv3c/XlLrvXene1kkXwc/q8P05Fnd/7w2hpmTx7N09edlvODvlh1ezKVmIgrVqkJlbGQSlBIMnjHzA4hWGlsZhcC+XfuiqT4zN0r8k4EsK9LaCALtPW2/0CxZgJplpFUgkLWGVwJ3AEcYWYbgc8Cny5JVDLkXfPzlfz6xexVRyG2hqDcM28SZwDFZynVhy3vePLZ+F6zjKQS5D1m0PMEsxFAKNjTuCw0ZjC45VpDMHvSSP75jMM5fdaBFTPDpi+ziQrd+L5S3qsMXUUZMzCzz6XcB9gOrHD35oxPEknQsnkn1y7u/Z9KfRge+qe/6rlfKTX7C40j094GQM8GOpn2OaiU9yrVqZAxg8bg59fB/bOBF4ArzOwX7n5TsYOToeMrD7zIomfX93rOee87kJs/duwARVRavQ08gwaIpfIUkgwagGPcvR3AzL5KrDbRycAKQMlA0rS1d/DMn9tyJoILj57If3wk55bag0YxNr4XGUiFDCBPAxKLyXcB0919D5Cx7KKZ3WVmb5vZmiyPn2Jm282sOfj5SgHxyAArtA7/kuaNHPtvj3PVPX/Kee6Xzj4y7dr9qfvfsnkn9zdtoGVzeYa2irHxvchAKqRl8DPgWTNbEtw/F7gnGFBem+U5PwZuBRb1ct1l7n5OAXFIGRS6QratvYOr7809lHTh0RM56fAJzL/xiaRrO/R5RW5ql9SCedP4+vnvy+u5xZRaegL6tvG9yEAoaDaRmR0LnEhsI5vl7p5zSo+ZzQAeyrRS2cxOAa4pNBloNtHA6ssK2VwzhsIh47sfnsP8mePSrl1fY4DR0V34ityWzTs547tL044//s8n9+x5IFKt+jWbyMwOSLi7Lvjpeczd3+1nfPPMbBWwiVhieClLHJcDlwNMmzatny9Z3QqdwljICtnvPvYyv1q1qdfr3XrJ0T37FK/asC3t2mELpe2bl++Aa/OGbVmPKxmIZJdPN9EKYquOjdi4wdbg9hhgPZC2A1oBVhIbd2g3s7OAB4BDM53o7guBhRBrGfTjNataXwqi5btC9tAvPUxXjr8ZA86ZM6nXa0c8Cp6cDfIdcJ07dUxBx0UkJucAsrsf5O4HA48B57r7OHdvILbHwS/78+LuviM+O8ndHwFqzWxcf64p2fV128VcK2Sv/+UqDv/X3IkAoOn6M3Je+9sXzuHbF/ZtRe7MCaNYMC+55bhg3rReWwXaoF6ksAHk/+XuV8TvuPujZvaN/ry4mR0IbHZ3N7PjiCWntv5cU7LrT0G0bHX489mRLG7BvGkZXyfbtXvbWL43x04/gJ+/0IoRa9I2Tj8g67kqHS0SU2ihuuuBnxL7P/Zxcnxwm9k9wCnAODNrBb4K1AK4++3AhcCnzawb2ANc7IXWx5C89bcgWuoK2et/uaqg17+vqZWrTz8s4wd7ptW3fVmRG2/9JA4+Z1rtm3hu4irhbOeKDHWFJINLiH2Y/yq4vzQ4lpW753r8VmJTT2UA9HXjl0wDzg+s3MBPn28t6PWztUKyDWj3pVZPIa0flY4W2SfvZBDMGrq6hLHIAOht28VMUrtRPveBw7jl8VfZ2Zl9de2wGvjE8dP57+c3JE0ZzdQKydZN09fum0JaPyodLbJPITudPUmwl0Eidz+t2EHlonUGA6OtvYMTvvVEUpdLPlZcfwYNI+t5sHkj1/xiFWZGNBrlUycdzLxDxnHkpP0BeGnTDi5b1JR0/bqaED+79Dg+ftfzfd7568HmjWmtn2yJpJBzRQa7Yu10dk3C7WHABWinsyHt7ufWF5wIzp87secDu+mNd+mMOPHvED/4w+v84A+vEzIIGdSFw2nX7+yOcvGPniOcct1Cum8Kaf0U2lISGaoK6SZakXLo6WBfZBmC2to7+P6TrxX8vN+s2Uxbewdbd3VmLU4X9dhPdzTzNmfdEU/7llFo900hg88qHS1S2H4GifPzQsTKWR9Y9IikIrRu3RN8cy+s8RcOGa1b9/BaPwvEDasNEY069TXhfg10l0OlxCFSiEK6ieIrkSHWPfQGcGmxA5LKMGXs8J6NWArR0RXbBWxEXWpHT3Zhg1DI6IokD0k98k8n9WlXsXL2/VdKHCKFKqSE9Szg+8AqYA3wKKBR3CHqikV9+6sNhWJlJMaOqCMcshxnx5jB1847Mm3F8cwJo5gzdUxeLYK+rKwutkqJQ6QvCmkZ/ATYAdwc3L8E+G/gomIHJcWVT7dF4jmfv3clL6zPXPAt7s4Fx/LsundZ9MxfkquL1oRp3boHgP1qw0mti+G1IT7+/un87Ln17OqMJByvYfak0Tx93Wl96l6plPUClRKHSF8UkgwOd/c5CfefDKqNSgXLp9sifk7YLOlDOpthtSGuuHsl0aiT0rOTNNCbOoffgY80TuW/nl6XdHxPV3dPAujLh2alrBeolDhE+qKQbqI/mdn743fM7Hjg6eKHJMWSq9uirb2Dpa++zbX3r2JvVzSvRACwtytKVyQ9EdTX7Csol6243dgRdZgldx+l3i9UrkJ6A6VS4hDpi3z2M3iR2Je6WmCBma0P7k8n+w5nUgF667ZY3vIO1y1eTciMju7cCw/fO2EErds6sg4q71cb5vZPHMvJh43vOZZpDv+qDdsYVhOmK7LvOvGupf58aFbKeoFKiUOkUPl0E2lLykEqW7fFiLpwT4shHyccNIZbPtbI/BufyHpOFO9ZWZwoteunlF0plbJeoFLiEClEPvsZ/KW3n4EIsliqrW59tm6LXZ0RakP59xD+7bGx/QFybfAO5Pz9qitFpDIVtAdypehLbaJqnv+dOpso2z7B2YysD9MddW664KisG7zHu53y/f1qYZbIwOutNlFVJIO+bOg+VH3m7hX8+sW3+vTc+hrjhwsaOXLS6LRS0/r9ilS+YhWqG7Q0/zvm0H95mFzDBCGL1Q3KpKPbueKnK4m6J33z1+9XZPArZGrpoKX53zDvm4/nTATvGVGTNRHE7e6MpE1RzfT77YhECypJISLlVdJkYGZ3mdnbZrYmy+NmZjebWYuZrTazY0oRRzkHLQdy0Dq2bmALS199m5bNO3ted8YXH+bNHblf/4d/fzz14fQ5//Xh9H8m8YJ0kPz7HVYbO9fcOefW5Sz8w5+5v2kDLf0sXCcipVXqbqIfE9vWclGWx/8aODT4OR74QfBn0ZVj/vdADlovad7I5+9rJnF7gPqw0ZG6MiyDaWPrWXrdGbS1d2AhI3E1WX1NiP+8aA6f/8WqpLITuzoirNm4nTlTxwCx3++siftz1s3LAGKvG3G++egrPc9ZMG8aXz//ff19qyJSAiVtGbj7UuDdXk45H1jkMc8CY8xsYqniaRhZn1fhs2IYyKJlbe0dXHv/KlL3ocknEdz/D+/nlo820tbekbEF9e0Lj2LeIQ38nxNnpD33Gw+vTXo/uzoj1Ndk7xpa9Mx6tRBEKlS5B5AnAxsS7rcGx95MPdHMLgcuB5g2bdqABNcfAzmo2rp1D2ELAfmVk4irDxsfvfN56sPJLZfEFtTylneYf+MThDKUjEh9P5nGDlI1b9jGzAmjCopTREqv3APImYrSZPw66+4L3b3R3RvHjx+f6ZSKMpCD1lPGDifihW1PCbGWQ2f3vpbLNfevpmXzzp4WFNDTutmdoW5R6vtJbFnsV5v5n9bc4LoiUlnKnQxagakJ96cAm8oUS1H1Z9C60EHnhpH1fPvCOblPDNTXhKgLW89gb1xnd5Szbl7Gg80bgX2tm1T71Yazvp/z5k7m6etO457L5/HhxilJjy2YN02tApEKVe5uogeBq8zsXmIDx9vdPa2LaLDKZ9A6dSVuXwad29o7+Kd7m/OKKWzw7x+azdypYzjn1uVpj3dGnGsXr2b+zHEZWzd1YeOmYBwhW2KL1+aZM3UMl590MM0btjF36hglApEKVuqppfcAzwCHm1mrmV1qZleY2RXBKY8ArwMtwA+BfyxlPNmUcvpnb4PWS5o3Mv/GJ/j4j55j/o1PcPdzfyl40HlJ80aO/bfH844n4jCjYT9mThjFTRccRV1N+j+BxLGAtCmjwDX3r+Lplnfyer2ZE0ZxYeNUJQKRClfSloG7X5LjcQeuLGUMuZSrZlHibKP4IPMNv15LbcpWkb0NOv9+7VtcnWeLINEbbbtpPKiB+TPH8Z2LjuKf72umK2FIIHEsINuU0XjrQSuMRYaGcncTDajULplMH8gD9SGXcbZR2Ojqzm/Q+bRvP8nrbbv79Npzp45JSoJg1ISc4bU1PQkx8f3Hp4x2JuxBoHITIkNL1SSDTC2A6Q0jBmT6Z1t7By9t2g4YR07an4aR9Rn74yNR56vnHsk3Hl5LyGL995/7wGFJscz44sN5v+6dC47l0kUr0o5v292ZlgTra0J8/2PH9MSXSOU8RIa+cs8mGhDZFoCNqAuX/ENuSfNG3v9/f8+Cu15gwV3Pc/w3H+fB5o09/fH1NcZ+tWHqa4ybLjiKj71/OufNmcTuzijdEeebj7zCV0U9xXIAABK3SURBVJa8CBSWCAAu/+nKjMeXvvZO2iyhunCI0cNrMyZB7UEgMvRVRcsg2wKwXZ0RbrrgKK5NaTEU60MutjJ4NV0JK4G7o/CF+1cxf+a4YEGFxUZlPTZW0LJ5J/c1tSZdZ9Ez61n0zPqCXz+SpercnCmjC06C2s5RZGirimTQWzfHnKljivohlzgu0bp1D+FQ+rq6sIV4adMOrlu8Oqnez7WLV/PFM4/o1+vnUhs2xo0a1qckqO0cRYauqkgG8W6ObB9+xfqQSx2X+PLZs+iKpK8Mjq0WzvytfVyJP2zDIStJEhSRwa0qkgGUvpsj08ykrz/0Usaumq+ceySTRg9P25B+b1eU7khh9YVyMaCuJkRduHRJUEQGv6pJBqUS7xbavqcrbVzCMKIZthWdOnZ4bLpmSonp+rDxzOu9FXkt3BV/dTDTD9iPli27OPPICTQe1JAWeylbBtrrWGRwqJpkUIrFZYnX7IxEk/r/Afam1pTuEeuq6UwpMd0ZceYdfAA/TxlA7isDFi5dRyRISD9avq5nT4GBWGxXrgV9IlK4qp5aWkj5idSSFanXTE0Ecam/4JoQHDlpf7bu6kwbNXDgs/etzv+N5RDbpyb5VRY9s56mdW0l32thIPdzEJH+q4pkkKn6ZnxxWT5Sawg92Lwxa0XPVJccNy1pLcF3PjyXhpH1NG/Y1qf3kmr2pP0zHq8NW8aZTJB5nUEhv4989Pd3LiIDqyq6ifqzgjZbyYqHrjqRzgwzhVJ9cv4MPvfBw9L6zWc07NeHd5LuQ3MnsWbTjrTjFlu8kPE5Jx86joXLXk86VuzFdlq1LDK4VEXLYN9q3xD71YWpr8l/BW2mb7hhM3Z1Rrjq1Jm9Pvf8uRPZ1Rlh667OtMdqa8IZd/YphBGrM3TGEcmb/YTNuOZ/H8ZFx05N+wv+cOMUamvCfPmcWSVdUaxVyyKDS1W0DCD+HdmDlb659waOy/QNd1dnhDWbtvPR46dx65Ov0dG973ohIBSCkBlLmt/k181vEiVW+8eBr547i48dP53bnni1gCgyM+DCO55NOlYbtp4yFnEnz2zgtPdOoLM7yncef5VHX3yrZx3E7MmjSzbTR6uWRQYP8wxTHytdY2OjNzU15X1+W3sH8298Imle/7DaEE9fd1peH1B3P/sX/vWBNUnH4s9/uuUdvnD/KsIWojsawbGk8hOV4v5/eD8fv+v5Pv8ORGTwM7MV7t6Y6bGq6CZq3boHT1n85VHPezBz9uTRjKwPJx2LD4Ym1RfCKvYXOhCDxiIyeFXqZ1dRjagLJy3ugtgmLSPqwlmesU9bewfb93SlfdvvikYZURfuqS+0uzNCZ8TTXqdSnHzoOA3oikhWJU8GZnammf2PmbWY2RczPH6KmW03s+bg5yvFjmFXZyRt8/dhtbGqpdm0tXdw8+9f44Rv/Z4r715JJBqlNmxJg6G7OiPUpEzfTL1fSrUZ/vbqwiFSQ1gwbxqNBzVoQFdEsirpALKZhYHvAx8AWoEXzOxBd1+bcuoydz+nVHFMGTuczpRFYZ3d2b8VL2neyLX376so2tEd2+Grvga+/7GjOXLSaBpG1nP3s3+hvSM5oXRnKRtdbKcfMZ5lLW2MqImNUZx8aANLX9tCTcgwMz7/gcM5YERd0kb0GtAVkWxK3TI4Dmhx99fdvRO4Fzi/xK+ZZuuuTlI/o6NOximf8XUFmVYUmxmjh9f1bJn5jYdTc9rACBssb2mjszvKrs4InZEoj7+yhc4I7O6K0NHtfOfxVzn1iPekbUTfMLKeOVPHKBGISJJSJ4PJwIaE+63BsVTzzGyVmT1qZkdmupCZXW5mTWbWtGXLloKCyLbaN9Px3lYW7+2K9owzvLRpB6F+rxTomw/NnURduPe/Og0Oi0ghSp0MMn1apvajrASmu/sc4BbggUwXcveF7t7o7o3jx4/PdEpWc6eOyft4pnUFcfXh2GKzJc0buWxRE7u7iltuOh+1YePTp8zMGmOcBodFpBClTgatwNSE+1OATYknuPsOd28Pbj8C1JrZuGIGMXPCKBbMm5Z0bMG8aWldKBDrRvnyObOoC6fnMQtZ0gyicvjaeUcyc8KotMHgBfOmaXBYRPqs1CuQXwAONbODgI3AxcBHE08wswOBze7uZnYcsQTVVuxAXt+yK+n+upT7cUuaN/KNh9ZSGw7RFYkkNWM+3DiFXZ2RtH0LBsqIujCzJ40GMg8GX316eg0kEZF8lDQZuHu3mV0FPAaEgbvc/SUzuyJ4/HbgQuDTZtYN7AEu9iIvi25a18byluT8sqyljaZ1bWmbvcSL0mVyz/MbOG5GA7s7u4sZXlY1IUhsgETck7p+Uncq085lItJXJa9NFHT9PJJy7PaE27cCt5YyhsfWvpX1eGIyiA8eZ/vW3xVxPnvvnxiodWWXnXQw//XHN4LNcyJceUrvhfFERPqqKlYgHzxuZMbjdeFQ0mYrU8YOZ09X79/6uwcoEdSE4FMnHczT153GZScfDBgLl77es5+CiEgxVUUyeM+ozF0nP1y6jhO+9fukD1ez8kwXhVgCSN0EB+C2p1ro6NaOYSJSOlVRwvrZdZnHozujDlH43H3NzJq4P80btlFfExs4HmifPuVgPnXiwWkDwK1b96SVuIivIdD4gIgUS1Ukg83b9vb6eHcUzvzeUuprwr3WKyqlu5av41MnHsyclLUPazZuTyt5kbiGoK29QzOIRKTfqiIZbNieeyVudxS6y5QIAOrC4bRv+9lKXnz5nFk0jKxnSfNGrlu8mtpQiK5olJsuOIrz5mZa4C0i0ruqGDM4870Tyh1CTplWDGcqjRFfa5A4DVZjCSLSX1WRDPaUabVwvrLtyZypNEZ8rUGmRKF6RCLSV1XRTfTcunfzPjf+8Vrq9DGqvobOSISrTj2Ujx4/LWN/f3xT+WtTuoLi52qzGhEplqpIBu+bPJpnXk9PCEZ61bxSJ4G6cIhH/ulEdnVG8hr0zbYHQa5EISJSiKpIBuvfyVyHqNTrx8IhiKRkl8+cNjNjgbzeZCszoc1qRKRYqiIZvLA+/26iYqkLhzBzIgm76tTXGB89flovzyqc6hGJSDFURTKwMuxR/9XzZjGqvkbdOCIyKFRFMti+d2CqjMbVhY3Zk0YzZ+oYdeOIyKBQFcmg5IMDKcysZ1aPunFEZDCoinUGXQOcDL5y7iwlABEZVKoiGZRKCKgPJx9L3I1MRGSwUDLoo5DBN/5mNpayCjh1N7JSa2vvYNWGbSpDISL9UvIxAzM7E/gesW0vf+Tu30p53ILHzwJ2A3/v7itLHVd/RR3+9Vdr0o6PrAtxxn88yfRx+zFn8lhe3LSd3R3d1NeG2Lqnm1MPG8/Jh41nVet2Tj50HI+teZOH1rzFObMP5CPHTad5wzbmTh3Dtt2dPLZ2MwePG8Gh7xnJG227mRtUNI2f89KbO5IK1X357FnMnjy6JxnFB6637urseU58jcNgq3Y62OItF/2epK+syNsNJ1/cLAy8CnwAaAVeAC5x97UJ55wFfIZYMjge+J67H9/bdRsbG72pqSnvOGZ88eHCgx8EQhZLSolG1ofp6I7i7gyvrWFXZ3fSOQvmTePY6QcMqmqnqs6aH/2eJBczW+HujZkeK3U30XFAi7u/7u6dwL3A+SnnnA8s8phngTFmNrHEcQ0JqYkAoL0jQlfE6Y7Czo7utHMWPbOeL/yiedBUO1V11vzo9yT9VepkMBnYkHC/NThW6DmY2eVm1mRmTVu2bCl6oNXEGDzVTlWdNT/6PUl/lToZZNpQOPX7bD7n4O4L3b3R3RvHjx9flOCGgrqwMaIunPvEBM7gqXaaqYx3JcdbLvo9SX+VOhm0AlMT7k8BNvXhnH5541tnF/NyFWPBvGk886XT+dll7+ff/2Y2w2pDjKqvoTZs1IRiZbJTtk9mwbxp/MdFc3vOHVabeS+FShGvzjpY4i0X/Z6kv0o9gFxDbAD5dGAjsQHkj7r7SwnnnA1cxb4B5Jvd/bjerlvoAHJcqQaS60PQEYVxI2oYNayWbbs6B2Q2UWr108SZJKDZRNVIvyfpTW8DyCVNBsGLnwX8P2JTS+9y9383sysA3P32YGrprcCZxKaWftLde/2k72syEBGpZr0lg5KvM3D3R4BHUo7dnnDbgStLHYeIiGSnFcgiIqJkICIiSgYiIoKSgYiIMACziUrBzLYAf+nj08cB7xQxnMGiGt93Nb5nqM73XY3vGQp/39PdPeOq3UGZDPrDzJqyTa0ayqrxfVfje4bqfN/V+J6huO9b3UQiIqJkICIi1ZkMFpY7gDKpxvddje8ZqvN9V+N7hiK+76obMxARkXTV2DIQEZEUSgYiIlJdycDMzjSz/zGzFjP7YrnjGQhmdpeZvW1ma8ody0Axs6lm9qSZvWxmL5nZ1eWOqdTMbJiZPW9mq4L3fEO5YxooZhY2sz+Z2UPljmWgmNkbZvaimTWbWVFKOFfNmIGZhYntrfABYhvqvABc4u5ryxpYiZnZyUA7sX2mZ5c7noEQ7KE90d1XmtkoYAXwoaH8dx2Ugh/h7u1mVgssB64O9hUf0szsc0AjsL+7n1PueAaCmb0BNLp70RbaVVPL4Digxd1fd/dO4F7g/DLHVHLuvhR4t9xxDCR3f9PdVwa3dwIvk2Ff7aHEY9qDu7XBz5D/pmdmU4CzgR+VO5bBrpqSwWRgQ8L9Vob4B4SAmc0AjgaeK28kpRd0lzQDbwO/c/ch/56JbZx1LaRs7D30OfBbM1thZpcX44LVlAwsw7Eh/82pmpnZSGAx8Fl331HueErN3SPuPpfYPuLHmdmQ7hY0s3OAt919RbljKYP57n4M8NfAlUF3cL9UUzJoBaYm3J8CbCpTLFJiQb/5YuBud/9lueMZSO6+DXiK2FayQ9l84Lyg//xe4DQz+2l5QxoY7r4p+PNt4FfEusH7pZqSwQvAoWZ2kJnVARcDD5Y5JimBYDD1TuBld/9OueMZCGY23szGBLeHA2cAr5Q3qtJy9y+5+xR3n0Hs//MT7v7xModVcmY2IpgYgZmNAD4I9Hu2YNUkA3fvBq4CHiM2oHifu79U3qhKz8zuAZ4BDjezVjO7tNwxDYD5wCeIfVNsDn7OKndQJTYReNLMVhP74vM7d6+aqZZVZgKw3MxWAc8DD7v7b/p70aqZWioiItlVTctARESyUzIQERElAxERUTIQERGUDEREKl4hBSfNbFpQqPFPZrY635l0SgYiIpXvx+S/iPB6YlPnjya2/uK2fJ6kZCBDlpnN6E/p7qBM8Lg+PvdDZjarr68dXOMKM1sQ3H7KzBoznPNIfLGZDF2ZCk6a2SFm9pugPtEyMzsifjqwf3B7NHlWWqgpWrQikuhDwENAn8tmu/vteZwz1BfTSXYLgSvc/TUzO55YC+A04GvEith9BhhBbDV6TmoZyFBXY2Y/CfpO7zez/RK/8ZtZo5k9FdxuMLPfBn2td5BQ3NDMvmxmr5jZ78zsHjO7Jjie9u3MzE4AzgO+Hax+PiQ1KDN7j5mtCG7PMTM3s2nB/T8HcX4t/joJzwsF7+ffgvt9br3I4BUUYTwB+EVQqfYOYqvQAS4BfuzuU4CzgP82s5yf9UoGMtQdDix096OAHcA/9nLuV4HlQV/rg0D8w7kRuIBYKey/JbaRStxC4DPufixwDXCbu/8xeP4X3H2uu/859YWCAmPDzGx/4CSgCTjJzKYTq8S5O0N8NcDdwKvufn3evwEZikLAtuDfV/znvcFjlwL3Abj7M8AwIOcXBiUDGeo2uPvTwe2fAif2cu7JwTm4+8PA1uD4icASd98TbJbza8j57SwffyRWR+lk4JvBnycBy7Kcfwewxt3/vYDXkCEoKMm+zswuglhxRjObEzy8Hjg9OP5eYslgS65rKhnIUJdafMuBbvb92x+W43zIvBcG9P7tLB/LiH34TweWAHOIJZ6lWc7/I3CqmaXGLENcloKTHwMuDQrWvcS+nRs/D1wWHL8H+HvPowidkoEMddPMbF5w+xJiewO/ARwbHLsg4dylxP6DYWZ/DYwNji8HzrXYpvMjiW2zmOvb2U5gVI7YlgIfB15z9yix2SJnAU9nOf9O4BFiLRFN/qgi7n6Ju09099qgbPed7r7O3c909znuPsvdvx6cu9bd5wfH57r7b/N5DSUDGepeBv4uKO18APAD4Abge2a2DIgknHsDcLKZrSRWI349gLu/QGwMYBXwS2L9+9uD52T7dnYv8IVgMDptADm47hvBzXhLYDmxlsbWTOcHz/kOsJI8BwVF8qUS1iJ5MLOR7t5uZvsR+/C+3N1XljsukWJRU1MkPwuDRWTDgJ8oEchQo5aBSImZ2feJzRpK9D13/69yxCOSiZKBiIhoAFlERJQMREQEJQMREUHJQEREgP8P4oNsgVtn+PEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Comparing budget_wiki and budget_kaggle with scatter plot\n",
    "movies_df.fillna(0).plot(x='budget_wiki',y='budget_kaggle', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28d00100c88>"
      ]
     },
     "execution_count": 321,
     "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": [
    "# Scatter plot for box office and revenue columns\n",
    "movies_df.fillna(0).plot(x='box_office', y='revenue', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28d038d1148>"
      ]
     },
     "execution_count": 322,
     "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": [
    "# Scatter plot for every movie with less than $1 million at the 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": 323,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x28d038e1388>"
      ]
     },
     "execution_count": 323,
     "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": [
    "# Creating regular line plot and changing the style to only put dots \n",
    "# with style='.' to the plot() method. This is done to compare release dates, which is non-numeric data\n",
    "movies_df[['release_date_wiki','release_date_kaggle']].plot(x='release_date_wiki', y='release_date_kaggle', style='.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "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>3607</th>\n",
       "      <td>https://en.wikipedia.org/wiki/The_Holiday</td>\n",
       "      <td>2006</td>\n",
       "      <td>https://www.imdb.com/title/tt00457939/</td>\n",
       "      <td>The Holiday</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Kate Winslet, Cameron Diaz, Jude Law, Jack Bl...</td>\n",
       "      <td>Dean Cundey</td>\n",
       "      <td>[December 8, 2006, (, 2006-12-08, )]</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>...</td>\n",
       "      <td>1953-08-28</td>\n",
       "      <td>30500000.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>[{'iso_639_1': 'en', 'name': 'English'}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Pouring out of impassioned pages...brawling th...</td>\n",
       "      <td>From Here to Eternity</td>\n",
       "      <td>False</td>\n",
       "      <td>7.2</td>\n",
       "      <td>137.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            url  year  \\\n",
       "3607  https://en.wikipedia.org/wiki/The_Holiday  2006   \n",
       "\n",
       "                                   imdb_link   title_wiki Based on  \\\n",
       "3607  https://www.imdb.com/title/tt00457939/  The Holiday      NaN   \n",
       "\n",
       "                                               Starring Cinematography  \\\n",
       "3607  [Kate Winslet, Cameron Diaz, Jude Law, Jack Bl...    Dean Cundey   \n",
       "\n",
       "                              Release date        Country Language  ...  \\\n",
       "3607  [December 8, 2006, (, 2006-12-08, )]  United States  English  ...   \n",
       "\n",
       "     release_date_kaggle     revenue runtime  \\\n",
       "3607          1953-08-28  30500000.0   118.0   \n",
       "\n",
       "                              spoken_languages    status  \\\n",
       "3607  [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
       "\n",
       "                                                tagline  \\\n",
       "3607  Pouring out of impassioned pages...brawling th...   \n",
       "\n",
       "               title_kaggle  video  vote_average  vote_count  \n",
       "3607  From Here to Eternity  False           7.2       137.0  \n",
       "\n",
       "[1 rows x 44 columns]"
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Singling outlier for 2006\n",
    "movies_df[(movies_df['release_date_wiki'] > '1996-01-01') & (movies_df['release_date_kaggle'] < '1965-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([3607], dtype='int64')"
      ]
     },
     "execution_count": 325,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The Holiday in the Wikipedia data got merged with From Here to Eternity. \n",
    "# Therefor row will have to be dropped from the DataFrame\n",
    "# Retrieving index of the row\n",
    "movies_df[(movies_df['release_date_wiki'] > '1996-01-01') & (movies_df['release_date_kaggle'] < '1965-01-01')].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping row\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": 327,
   "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>0.0</td>\n",
       "      <td>92.0</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>6.1</td>\n",
       "      <td>7.0</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>0.0</td>\n",
       "      <td>85.0</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>7.5</td>\n",
       "      <td>4.0</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>0.0</td>\n",
       "      <td>95.0</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>8.0</td>\n",
       "      <td>2.0</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>0.0</td>\n",
       "      <td>89.0</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>5.0</td>\n",
       "      <td>1.0</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>0.0</td>\n",
       "      <td>110.0</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>4.5</td>\n",
       "      <td>4.0</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>0.0</td>\n",
       "      <td>86.0</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>4.7</td>\n",
       "      <td>6.0</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>0.0</td>\n",
       "      <td>107.0</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>0.0</td>\n",
       "      <td>0.0</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>97000.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Stevie</td>\n",
       "      <td>False</td>\n",
       "      <td>6.7</td>\n",
       "      <td>13.0</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>0.0</td>\n",
       "      <td>109.0</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>5.9</td>\n",
       "      <td>13.0</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>0.0</td>\n",
       "      <td>89.0</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>5.5</td>\n",
       "      <td>8.0</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>0.0</td>\n",
       "      <td>93.0</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>5.6</td>\n",
       "      <td>9.0</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      0.0    92.0   \n",
       "1061          1995-09-14      0.0    85.0   \n",
       "1121          1995-11-17      0.0    95.0   \n",
       "1564          1998-01-01      0.0    89.0   \n",
       "1633          1997-01-01      0.0   110.0   \n",
       "1775          1999-02-22      0.0    86.0   \n",
       "2386          2000-01-01      0.0   107.0   \n",
       "2786          2002-09-09  97000.0   140.0   \n",
       "3174          2004-09-17      0.0   109.0   \n",
       "3651          2006-03-11      0.0    89.0   \n",
       "4967          2012-06-08      0.0    93.0   \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  vote_count  \n",
       "1008            Black Scorpion  False           6.1         7.0  \n",
       "1061                     Flirt  False           7.5         4.0  \n",
       "1121              Let It Be Me  False           8.0         2.0  \n",
       "1564  A Brooklyn State of Mind  False           5.0         1.0  \n",
       "1633                  Highball  False           4.5         4.0  \n",
       "1775             Velocity Trap  False           4.7         6.0  \n",
       "2386                 The Visit  False           0.0         0.0  \n",
       "2786                    Stevie  False           6.7        13.0  \n",
       "3174          Return to Sender  False           5.9        13.0  \n",
       "3651          Live Free or Die  False           5.5         8.0  \n",
       "4967     For the Love of Money  False           5.6         9.0  \n",
       "\n",
       "[11 rows x 44 columns]"
      ]
     },
     "execution_count": 327,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking to see of there are any null values\n",
    "movies_df[movies_df['release_date_wiki'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "English                              5479\n",
       "[English, Spanish]                     68\n",
       "[English, French]                      35\n",
       "[English, Japanese]                    25\n",
       "[English, Russian]                     23\n",
       "                                     ... \n",
       "[English, Mandarin, Shanghainese]       1\n",
       "[Aramaic, Latin, Hebrew]                1\n",
       "[Spanish, Quechua]                      1\n",
       "[English, Scottish Gaelic]              1\n",
       "[English, Greek, French]                1\n",
       "Name: Language, Length: 197, dtype: int64"
      ]
     },
     "execution_count": 328,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Value  counts for language data\n",
    "movies_df['Language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "English                                5479\n",
       "NaN                                     134\n",
       "(English, Spanish)                       68\n",
       "(English, French)                        35\n",
       "(English, Japanese)                      25\n",
       "                                       ... \n",
       "(English, Spanish, Inuktitut)             1\n",
       "(Chinese, English)                        1\n",
       "(English, Romanian)                       1\n",
       "(English, Somali)                         1\n",
       "(English, Italian, Russian, German)       1\n",
       "Name: Language, Length: 198, dtype: int64"
      ]
     },
     "execution_count": 329,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# However, need to convert lists in languag data into tuples so that the value_counts()\n",
    "# method could work\n",
    "movies_df['Language'].apply(lambda x: tuple(x) if type(x) == list else x).value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "en    5987\n",
       "fr      16\n",
       "es      10\n",
       "it       8\n",
       "de       6\n",
       "pt       4\n",
       "zh       4\n",
       "ja       4\n",
       "hi       2\n",
       "da       2\n",
       "cn       1\n",
       "he       1\n",
       "ar       1\n",
       "tr       1\n",
       "sv       1\n",
       "ko       1\n",
       "ru       1\n",
       "ab       1\n",
       "Name: original_language, dtype: int64"
      ]
     },
     "execution_count": 330,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Kaggle data has no lists, so value_counts() will work\n",
    "movies_df['original_language'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "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": 331,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Working on production companies data\n",
    "# Taking a quick look at the data\n",
    "movies_df[['Production company(s)','production_companies']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping 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": 333,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make function to fill in missing data for a column pair and then drops the redundant column\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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "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>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>20423389.0</td>\n",
       "      <td>104.0</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>6.2</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://en.wikipedia.org/wiki/After_Dark,_My_S...</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0098994/</td>\n",
       "      <td>[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>2700000.0</td>\n",
       "      <td>114.0</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>6.5</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Air_America_(film)</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099005/</td>\n",
       "      <td>[Air America, 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>33461269.0</td>\n",
       "      <td>112.0</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>5.3</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Alice_(1990_film)</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099012/</td>\n",
       "      <td>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>7331647.0</td>\n",
       "      <td>102.0</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>6.3</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://en.wikipedia.org/wiki/Almost_an_Angel</td>\n",
       "      <td>1990</td>\n",
       "      <td>https://www.imdb.com/title/tt0099018/</td>\n",
       "      <td>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>6939946.0</td>\n",
       "      <td>95.0</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>5.6</td>\n",
       "      <td>23.0</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>3700000.0</td>\n",
       "      <td>104.0</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>7.2</td>\n",
       "      <td>13.0</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>96.0</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>0.0</td>\n",
       "      <td>1.0</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>4800000.0</td>\n",
       "      <td>128.0</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>7.8</td>\n",
       "      <td>26.0</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>200340.0</td>\n",
       "      <td>92.0</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>0.0</td>\n",
       "      <td>0.0</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>382053.0</td>\n",
       "      <td>102.0</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>0.0</td>\n",
       "      <td>10.0</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  20423389.0   104.0   \n",
       "1             1990-08-24   2700000.0   114.0   \n",
       "2             1990-08-10  33461269.0   112.0   \n",
       "3             1990-12-25   7331647.0   102.0   \n",
       "4             1990-12-21   6939946.0    95.0   \n",
       "...                  ...         ...     ...   \n",
       "6047          2017-04-06   3700000.0   104.0   \n",
       "6048          2017-04-22         NaN    96.0   \n",
       "6049          2017-06-01   4800000.0   128.0   \n",
       "6050          2017-03-12    200340.0    92.0   \n",
       "6051          2017-12-27    382053.0   102.0   \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  vote_count  \n",
       "0     The Adventures of Ford Fairlane  False          6.2        72.0  \n",
       "1                After Dark, My Sweet  False          6.5        17.0  \n",
       "2                         Air America  False          5.3       146.0  \n",
       "3                               Alice  False          6.3        57.0  \n",
       "4                     Almost an Angel  False          5.6        23.0  \n",
       "...                               ...    ...          ...         ...  \n",
       "6047                A Fantastic Woman  False          7.2        13.0  \n",
       "6048                       Permission  False          0.0         1.0  \n",
       "6049                         Loveless  False          7.8        26.0  \n",
       "6050                           Gemini  False          0.0         0.0  \n",
       "6051  How to Talk to Girls at Parties  False          0.0        10.0  \n",
       "\n",
       "[6051 rows x 37 columns]"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run function for the three column pairs that we want to fill in zeros\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": 335,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "video\n"
     ]
    }
   ],
   "source": [
    "# Checking to see if there are any columns with only one value \n",
    "# Then converting lists to tuples for value_counts() to work\n",
    "for col in movies_df.columns:\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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    6051\n",
       "Name: video, dtype: int64"
      ]
     },
     "execution_count": 336,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df['video'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renaming columns\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",
    "                      ]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renaming columns\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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transforming and Merging Stage\n",
    "# Groupby() on movieId and rating \n",
    "rating_counts = ratings.groupby(['movieId','rating'], as_index=False).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_counts = ratings.groupby(['movieId','rating'], as_index=False).count() \\\n",
    "                .rename({'userId':'count'}, axis=1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pivoting data\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": 342,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renaming columns to make it easier to understand\n",
    "rating_counts.columns = ['rating_' + str(col) for col in rating_counts.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using left merge\n",
    "movies_with_ratings_df = pd.merge(movies_df, rating_counts, left_on='kaggle_id', right_index=True, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "# As not every movie got a rating for each rating level, \n",
    "# there will be missing values instead of zeros\n",
    "movies_with_ratings_df[rating_counts.columns] = movies_with_ratings_df[rating_counts.columns].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "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>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>rating_0.5</th>\n",
       "      <th>rating_1.0</th>\n",
       "      <th>rating_1.5</th>\n",
       "      <th>rating_2.0</th>\n",
       "      <th>rating_2.5</th>\n",
       "      <th>rating_3.0</th>\n",
       "      <th>rating_3.5</th>\n",
       "      <th>rating_4.0</th>\n",
       "      <th>rating_4.5</th>\n",
       "      <th>rating_5.0</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>104.0</td>\n",
       "      <td>49000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>114.0</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>112.0</td>\n",
       "      <td>35000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>102.0</td>\n",
       "      <td>12000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>95.0</td>\n",
       "      <td>25000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</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>104.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>96.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>128.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>92.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6051 rows × 41 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      budget  ...  \\\n",
       "0     https://www.imdb.com/title/tt0098987/    104.0  49000000.0  ...   \n",
       "1     https://www.imdb.com/title/tt0098994/    114.0   6000000.0  ...   \n",
       "2     https://www.imdb.com/title/tt0099005/    112.0  35000000.0  ...   \n",
       "3     https://www.imdb.com/title/tt0099012/    102.0  12000000.0  ...   \n",
       "4     https://www.imdb.com/title/tt0099018/     95.0  25000000.0  ...   \n",
       "...                                     ...      ...         ...  ...   \n",
       "6047  https://www.imdb.com/title/tt5639354/    104.0         NaN  ...   \n",
       "6048  https://www.imdb.com/title/tt5390066/     96.0         NaN  ...   \n",
       "6049  https://www.imdb.com/title/tt6304162/    128.0         NaN  ...   \n",
       "6050  https://www.imdb.com/title/tt5795086/     92.0         NaN  ...   \n",
       "6051  https://www.imdb.com/title/tt3859310/    102.0         NaN  ...   \n",
       "\n",
       "      rating_0.5 rating_1.0  rating_1.5  rating_2.0  rating_2.5 rating_3.0  \\\n",
       "0            0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "1            0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "2            0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "3            0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "4            3.0        0.0         3.0         2.0         5.0       26.0   \n",
       "...          ...        ...         ...         ...         ...        ...   \n",
       "6047         0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "6048         0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "6049         0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "6050         0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "6051         0.0        0.0         0.0         0.0         0.0        0.0   \n",
       "\n",
       "     rating_3.5 rating_4.0 rating_4.5 rating_5.0  \n",
       "0           0.0        0.0        0.0        0.0  \n",
       "1           0.0        0.0        0.0        0.0  \n",
       "2           0.0        0.0        0.0        0.0  \n",
       "3           0.0        0.0        0.0        0.0  \n",
       "4          37.0       46.0       16.0       11.0  \n",
       "...         ...        ...        ...        ...  \n",
       "6047        0.0        0.0        0.0        0.0  \n",
       "6048        0.0        0.0        0.0        0.0  \n",
       "6049        0.0        0.0        0.0        0.0  \n",
       "6050        0.0        0.0        0.0        0.0  \n",
       "6051        0.0        0.0        0.0        0.0  \n",
       "\n",
       "[6051 rows x 41 columns]"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Viewing dataset\n",
    "movies_with_ratings_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [],
   "source": [
    "db_string = f\"postgres://postgres:{db_password}@127.0.0.1:5432/movie_data\"\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine(db_string)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies_df.to_sql(name='movies', con=engine)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "importing rows 0 to 1000000...Done. 336.10666823387146 total seconds elapsed\n",
      "importing rows 1000000 to 2000000...Done. 577.8438110351562 total seconds elapsed\n",
      "importing rows 2000000 to 3000000...Done. 774.6062943935394 total seconds elapsed\n",
      "importing rows 3000000 to 4000000...Done. 923.3397998809814 total seconds elapsed\n",
      "importing rows 4000000 to 5000000...Done. 1059.0975267887115 total seconds elapsed\n",
      "importing rows 5000000 to 6000000...Done. 1190.5278344154358 total seconds elapsed\n",
      "importing rows 6000000 to 7000000...Done. 1321.625033378601 total seconds elapsed\n",
      "importing rows 7000000 to 8000000...Done. 1455.1986045837402 total seconds elapsed\n",
      "importing rows 8000000 to 9000000...Done. 1589.8223669528961 total seconds elapsed\n",
      "importing rows 9000000 to 10000000...Done. 1721.2466893196106 total seconds elapsed\n",
      "importing rows 10000000 to 11000000...Done. 1852.6510660648346 total seconds elapsed\n",
      "importing rows 11000000 to 12000000...Done. 1983.297470331192 total seconds elapsed\n",
      "importing rows 12000000 to 13000000...Done. 2114.8883485794067 total seconds elapsed\n",
      "importing rows 13000000 to 14000000...Done. 2247.2721037864685 total seconds elapsed\n",
      "importing rows 14000000 to 15000000...Done. 2409.1539254188538 total seconds elapsed\n",
      "importing rows 15000000 to 16000000...Done. 2560.7742063999176 total seconds elapsed\n",
      "importing rows 16000000 to 17000000...Done. 2691.755714416504 total seconds elapsed\n",
      "importing rows 17000000 to 18000000...Done. 2824.4286966323853 total seconds elapsed\n",
      "importing rows 18000000 to 19000000...Done. 2954.3480467796326 total seconds elapsed\n",
      "importing rows 19000000 to 20000000...Done. 3085.408343076706 total seconds elapsed\n",
      "importing rows 20000000 to 21000000...Done. 3215.786465883255 total seconds elapsed\n",
      "importing rows 21000000 to 22000000...Done. 3348.3796610832214 total seconds elapsed\n",
      "importing rows 22000000 to 23000000...Done. 3482.042473077774 total seconds elapsed\n",
      "importing rows 23000000 to 24000000...Done. 3615.2151186466217 total seconds elapsed\n",
      "importing rows 24000000 to 25000000...Done. 3748.684969186783 total seconds elapsed\n",
      "importing rows 25000000 to 26000000...Done. 3881.2881360054016 total seconds elapsed\n",
      "importing rows 26000000 to 26024289...Done. 3884.545421361923 total seconds elapsed\n"
     ]
    }
   ],
   "source": [
    "# Importing Ratings Data\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",
    "    # print that the rows have finished importing\n",
    "    # add elapsed time to final print out\n",
    "    print(f'Done. {time.time() - start_time} total seconds elapsed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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