Movie_recommendation_project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "eae71986",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "7fb2dcb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies=pd.read_csv('tmdb_5000_movies.csv')\n",
    "credits=pd.read_csv('tmdb_5000_credits.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "e1a0a362",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "a6ace0e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "credits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "eed3beae",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9fcdc9e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies=movies.merge(credits,on='title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b6a3cdbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5abe18f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d53ed84c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Useful Columns:-\n",
    "#genres\n",
    "#id\n",
    "#keywords\n",
    "#Overview\n",
    "#title\n",
    "#cast\n",
    "#crew\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0a679ee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# movies['original_language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "556b946a",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies=movies[['title','id','overview','keywords','genres','cast','crew']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "40a6e2b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(1)['cast']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "12173000",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b6396649",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "899be3bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "373da665",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "06f9ae1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.iloc[0].genres"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "77a73f60",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "910cf0b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert(obj):\n",
    "    L=[]\n",
    "    for i in ast.literal_eval(obj):\n",
    "        L.append(i['name'])\n",
    "    return L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "48bdf879",
   "metadata": {},
   "outputs": [],
   "source": [
    "ast.literal_eval('[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 878, \"name\": \"Science Fiction\"}]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5496da20",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['genres']=movies['genres'].apply(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2ab036ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "60ab3237",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.iloc[0].keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "44eda39f",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['keywords']=movies['keywords'].apply(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "678e491a",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "74daf54f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# movies.iloc[0].cast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "45153056",
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert3(obj):\n",
    "    L=[]\n",
    "    cnt=0\n",
    "    for i in ast.literal_eval(obj):\n",
    "        if cnt!=3:\n",
    "            L.append(i['name'])\n",
    "            cnt=cnt+1\n",
    "        else:\n",
    "            break\n",
    "        \n",
    "    return L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c50e8c59",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['cast']=movies['cast'].apply(convert3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "37e01da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d8fefd59",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# for i in ast.literal_eval(movies.iloc[0].crew):\n",
    "#     L1=[]\n",
    "#     if i['job']=='Director':\n",
    "#         L1.append(i['name'])\n",
    "#     print(L1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fcb98672",
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert4(obj):\n",
    "    L=[]\n",
    "    for i in ast.literal_eval(obj):\n",
    "        if i['job']=='Director':\n",
    "        \n",
    "            L.append(i['name'])\n",
    "    return L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "87ccb3cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['crew']=movies['crew'].apply(convert4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e958a054",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b8b91bb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "000140a0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ac926d6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_string(x):\n",
    "    if isinstance(x, str):\n",
    "        return x.split(\" \")\n",
    "    else:\n",
    "        return []\n",
    "\n",
    "movies['overview'] = movies['overview'].apply(split_string)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "76b26f48",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['overview']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "367a9fa7",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "12600c82",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['keywords']=movies['keywords'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
    "movies['genres']=movies['genres'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
    "movies['cast']=movies['cast'].apply(lambda x:[i.replace(\" \",\"\") for i in x])\n",
    "movies['crew']=movies['crew'].apply(lambda x:[i.replace(\" \",\"\") for i in x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4715ab94",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "718c1fe5",
   "metadata": {},
   "outputs": [],
   "source": [
    "movies['tags']=movies['overview']+movies['keywords']+movies['genres']+movies['cast']+movies['crew']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e05b7e58",
   "metadata": {},
   "outputs": [],
   "source": [
    " movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "3732dfcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df=movies[['title','id','tags']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f79158c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5dfaee2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df['tags']=new_df['tags'].apply(lambda x:\" \".join(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "2f363c8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6b6f8940",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df['tags'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "6cd3f172",
   "metadata": {},
   "outputs": [],
   "source": [
    "#lower case\n",
    "new_df['tags'].apply(lambda x: x.lower())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "8b5d9804",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c710cb20",
   "metadata": {},
   "outputs": [],
   "source": [
    "cv=CountVectorizer(max_features=5000,stop_words='english')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "a6d3be40",
   "metadata": {},
   "outputs": [],
   "source": [
    "vectors=cv.fit_transform(new_df['tags']).toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "63402ed5",
   "metadata": {},
   "outputs": [],
   "source": [
    "vectors[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "e1a56b46",
   "metadata": {},
   "outputs": [],
   "source": [
    "cv.get_feature_names_out()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "fa1b29ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Now we will use steming to drop similar features\n",
    "!pip install nltk\n",
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "9de70b8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.stem.porter import PorterStemmer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "69e81f9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ps=PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "df8453ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "def stem(text):\n",
    "    y=[]\n",
    "    for i in text.split():\n",
    "        y.append(ps.stem(i))\n",
    "    return \" \".join(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c8d13744",
   "metadata": {},
   "outputs": [],
   "source": [
    "ps.stem(\"dancing\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "c1c42a26",
   "metadata": {},
   "outputs": [],
   "source": [
    "stem(\"loving\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e0810e7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "stem('In the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization. cultureclash future spacewar spacecolony society spacetravel futuristic romance space alien tribe alienplanet cgi marine soldier battle loveaffair antiwar powerrelations mindandsoul 3d Action Adventure Fantasy ScienceFiction SamWorthington ZoeSaldana SigourneyWeaver JamesCameron'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "c35ebc5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df['tags'].apply(stem)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "7759d336",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cv.get_feature_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "96cd0c59",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "939deb97",
   "metadata": {},
   "outputs": [],
   "source": [
    "cosine_similarity(vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "004396f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "cosine_similarity(vectors).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f28fede3",
   "metadata": {},
   "outputs": [],
   "source": [
    "similarity=cosine_similarity(vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "ec4b7f77",
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted(list(enumerate(similarity[0])),reverse=True,key=lambda x:x[1])[1:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "cc3b9a2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommend(movie):\n",
    "    movie_index=new_df[new_df['title']==movie].index[0]\n",
    "    distances=similarity[movie_index]\n",
    "    movies_list=sorted(list(enumerate(distances)),reverse=True,key=lambda x:x[1])[1:6]\n",
    "    for i in movies_list:\n",
    "        print(new_df.iloc[i[0]].title)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "14d476e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df[new_df['title']=='Spectre'].index[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "3895b480",
   "metadata": {},
   "outputs": [],
   "source": [
    "recommend('Spiderman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9261f62b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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