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+ "id": "c04aac25-dad2-4b5b-b7e9-6102add4febb",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import pandas as pd\n",
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+ "import numpy as np\n",
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+ "import matplotlib.pyplot as plt\n",
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+ "import seaborn as sns"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "id": "6b397e38-4659-4205-9716-f72f20e5d865",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "movies = pd.read_csv('data/tmdb_5000_movies.csv')\n",
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+ "credits = pd.read_csv('data/tmdb_5000_credits.csv')"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "id": "c3ad363c-de60-4f3f-829f-75dc4ec20b37",
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+ {
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+ "text/html": [
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+ "<div>\n",
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+ "<style scoped>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
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+ " }\n",
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+ "</style>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
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+ " <th>budget</th>\n",
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+ " <th>genres</th>\n",
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+ " <th>homepage</th>\n",
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+ " <th>id</th>\n",
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+ " <th>keywords</th>\n",
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+ " <th>original_language</th>\n",
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+ " <th>original_title</th>\n",
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+ " <th>overview</th>\n",
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+ " <th>popularity</th>\n",
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+ " <th>production_companies</th>\n",
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+ " <th>production_countries</th>\n",
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+ " <th>release_date</th>\n",
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+ " <th>revenue</th>\n",
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+ " <th>runtime</th>\n",
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+ " <th>spoken_languages</th>\n",
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+ " <th>status</th>\n",
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+ " <th>tagline</th>\n",
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+ " <th>title</th>\n",
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+ " <th>vote_average</th>\n",
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+ " <th>vote_count</th>\n",
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+ " </tr>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <td>237000000</td>\n",
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+ " <td>http://www.avatarmovie.com/</td>\n",
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+ " <td>Avatar</td>\n",
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+ " <td>7.2</td>\n",
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+ " <td>http://disney.go.com/disneypictures/pirates/</td>\n",
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+ " <td>6.9</td>\n",
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+ " <td>6.3</td>\n",
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+ " <td>http://www.thedarkknightrises.com/</td>\n",
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+ " <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
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+ " <td>en</td>\n",
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+ " <td>The Legend Ends</td>\n",
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+ " <td>The Dark Knight Rises</td>\n",
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+ " <td>7.6</td>\n",
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+ " <td>9106</td>\n",
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+ " <td>260000000</td>\n",
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+ " <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
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+ " <td>http://movies.disney.com/john-carter</td>\n",
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+ " <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
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+ " <td>en</td>\n",
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+ "0 237000000 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam... \n",
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+ "4 260000000 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam... \n",
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+ " homepage id \\\n",
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+ "0 http://www.avatarmovie.com/ 19995 \n",
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+ "1 http://disney.go.com/disneypictures/pirates/ 285 \n",
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+ "0 [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":... en \n",
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+ "4 [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":... en \n",
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+ "0 Avatar \n",
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+ "1 [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"... \n",
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+ "2 [{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"... 2015-10-26 880674609 \n",
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+ "4 [{\"iso_3166_1\": \"US\", \"name\": \"United States o... 2012-03-07 284139100 \n",
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+ " runtime spoken_languages status \\\n",
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+ "0 162.0 [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso... Released \n",
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+ "1 169.0 [{\"iso_639_1\": \"en\", \"name\": \"English\"}] Released \n",
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+ "2 148.0 [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},... Released \n",
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+ "3 165.0 [{\"iso_639_1\": \"en\", \"name\": \"English\"}] Released \n",
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+ "4 132.0 [{\"iso_639_1\": \"en\", \"name\": \"English\"}] Released \n",
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+ "2 A Plan No One Escapes \n",
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+ "4 Lost in our world, found in another. \n",
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+ "3 The Dark Knight Rises 7.6 9106 \n",
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+ "4 John Carter 6.1 2124 "
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+ "execution_count": 3,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
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+ "movies.head()"
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+ ]
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+ },
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+ {
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+ "execution_count": 4,
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+ "id": "2d4d19ed-104f-46c1-96c9-5ffd94cf8b15",
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+ "metadata": {},
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+ " vertical-align: top;\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
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+ " }\n",
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+ "</style>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
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+ " <th>movie_id</th>\n",
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+ " <th>title</th>\n",
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+ " <th>cast</th>\n",
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+ " <th>crew</th>\n",
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+ " </tr>\n",
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+ " <th>0</th>\n",
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+ " <td>Spectre</td>\n",
329
+ " <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
330
+ " <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
331
+ " </tr>\n",
332
+ " <tr>\n",
333
+ " <th>3</th>\n",
334
+ " <td>49026</td>\n",
335
+ " <td>The Dark Knight Rises</td>\n",
336
+ " <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
337
+ " <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
338
+ " </tr>\n",
339
+ " <tr>\n",
340
+ " <th>4</th>\n",
341
+ " <td>49529</td>\n",
342
+ " <td>John Carter</td>\n",
343
+ " <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
344
+ " <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
345
+ " </tr>\n",
346
+ " </tbody>\n",
347
+ "</table>\n",
348
+ "</div>"
349
+ ],
350
+ "text/plain": [
351
+ " movie_id title \\\n",
352
+ "0 19995 Avatar \n",
353
+ "1 285 Pirates of the Caribbean: At World's End \n",
354
+ "2 206647 Spectre \n",
355
+ "3 49026 The Dark Knight Rises \n",
356
+ "4 49529 John Carter \n",
357
+ "\n",
358
+ " cast \\\n",
359
+ "0 [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"... \n",
360
+ "1 [{\"cast_id\": 4, \"character\": \"Captain Jack Spa... \n",
361
+ "2 [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr... \n",
362
+ "3 [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba... \n",
363
+ "4 [{\"cast_id\": 5, \"character\": \"John Carter\", \"c... \n",
364
+ "\n",
365
+ " crew \n",
366
+ "0 [{\"credit_id\": \"52fe48009251416c750aca23\", \"de... \n",
367
+ "1 [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de... \n",
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+ "2 [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de... \n",
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370
+ "4 [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de... "
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+ ]
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+ },
373
+ "execution_count": 4,
374
+ "metadata": {},
375
+ "output_type": "execute_result"
376
+ }
377
+ ],
378
+ "source": [
379
+ "credits.head()"
380
+ ]
381
+ },
382
+ {
383
+ "cell_type": "code",
384
+ "execution_count": 5,
385
+ "id": "1203ff17-269a-4641-8045-5a16e204460c",
386
+ "metadata": {},
387
+ "outputs": [],
388
+ "source": [
389
+ "movies = movies.merge(credits, on='title')"
390
+ ]
391
+ },
392
+ {
393
+ "cell_type": "code",
394
+ "execution_count": 6,
395
+ "id": "1764ac22-2898-453b-a19c-da36b619a2ce",
396
+ "metadata": {},
397
+ "outputs": [
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+ {
399
+ "name": "stdout",
400
+ "output_type": "stream",
401
+ "text": [
402
+ "<class 'pandas.core.frame.DataFrame'>\n",
403
+ "RangeIndex: 4809 entries, 0 to 4808\n",
404
+ "Data columns (total 23 columns):\n",
405
+ " # Column Non-Null Count Dtype \n",
406
+ "--- ------ -------------- ----- \n",
407
+ " 0 budget 4809 non-null int64 \n",
408
+ " 1 genres 4809 non-null object \n",
409
+ " 2 homepage 1713 non-null object \n",
410
+ " 3 id 4809 non-null int64 \n",
411
+ " 4 keywords 4809 non-null object \n",
412
+ " 5 original_language 4809 non-null object \n",
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+ " 6 original_title 4809 non-null object \n",
414
+ " 7 overview 4806 non-null object \n",
415
+ " 8 popularity 4809 non-null float64\n",
416
+ " 9 production_companies 4809 non-null object \n",
417
+ " 10 production_countries 4809 non-null object \n",
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+ " 11 release_date 4808 non-null object \n",
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+ " 12 revenue 4809 non-null int64 \n",
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+ " 13 runtime 4807 non-null float64\n",
421
+ " 14 spoken_languages 4809 non-null object \n",
422
+ " 15 status 4809 non-null object \n",
423
+ " 16 tagline 3965 non-null object \n",
424
+ " 17 title 4809 non-null object \n",
425
+ " 18 vote_average 4809 non-null float64\n",
426
+ " 19 vote_count 4809 non-null int64 \n",
427
+ " 20 movie_id 4809 non-null int64 \n",
428
+ " 21 cast 4809 non-null object \n",
429
+ " 22 crew 4809 non-null object \n",
430
+ "dtypes: float64(3), int64(5), object(15)\n",
431
+ "memory usage: 864.2+ KB\n"
432
+ ]
433
+ }
434
+ ],
435
+ "source": [
436
+ "movies.info()"
437
+ ]
438
+ },
439
+ {
440
+ "cell_type": "code",
441
+ "execution_count": 7,
442
+ "id": "5f039dca-eeae-44cd-8cab-4ea1e28c2b62",
443
+ "metadata": {},
444
+ "outputs": [],
445
+ "source": [
446
+ "movies = movies[['movie_id', 'title', 'genres', 'overview', 'keywords', 'cast', 'crew']]"
447
+ ]
448
+ },
449
+ {
450
+ "cell_type": "code",
451
+ "execution_count": 8,
452
+ "id": "533b1e16-c9d3-42b0-82bc-80a4d4fdc029",
453
+ "metadata": {},
454
+ "outputs": [
455
+ {
456
+ "data": {
457
+ "text/html": [
458
+ "<div>\n",
459
+ "<style scoped>\n",
460
+ " .dataframe tbody tr th:only-of-type {\n",
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+ " vertical-align: middle;\n",
462
+ " }\n",
463
+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
466
+ " }\n",
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+ "\n",
468
+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
470
+ " }\n",
471
+ "</style>\n",
472
+ "<table border=\"1\" class=\"dataframe\">\n",
473
+ " <thead>\n",
474
+ " <tr style=\"text-align: right;\">\n",
475
+ " <th></th>\n",
476
+ " <th>movie_id</th>\n",
477
+ " <th>title</th>\n",
478
+ " <th>genres</th>\n",
479
+ " <th>overview</th>\n",
480
+ " <th>keywords</th>\n",
481
+ " <th>cast</th>\n",
482
+ " <th>crew</th>\n",
483
+ " </tr>\n",
484
+ " </thead>\n",
485
+ " <tbody>\n",
486
+ " <tr>\n",
487
+ " <th>0</th>\n",
488
+ " <td>19995</td>\n",
489
+ " <td>Avatar</td>\n",
490
+ " <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
491
+ " <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
492
+ " <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
493
+ " <td>[{\"cast_id\": 242, \"character\": \"Jake Sully\", \"...</td>\n",
494
+ " <td>[{\"credit_id\": \"52fe48009251416c750aca23\", \"de...</td>\n",
495
+ " </tr>\n",
496
+ " <tr>\n",
497
+ " <th>1</th>\n",
498
+ " <td>285</td>\n",
499
+ " <td>Pirates of the Caribbean: At World's End</td>\n",
500
+ " <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
501
+ " <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
502
+ " <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
503
+ " <td>[{\"cast_id\": 4, \"character\": \"Captain Jack Spa...</td>\n",
504
+ " <td>[{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de...</td>\n",
505
+ " </tr>\n",
506
+ " <tr>\n",
507
+ " <th>2</th>\n",
508
+ " <td>206647</td>\n",
509
+ " <td>Spectre</td>\n",
510
+ " <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
511
+ " <td>A cryptic message from Bond’s past sends him o...</td>\n",
512
+ " <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
513
+ " <td>[{\"cast_id\": 1, \"character\": \"James Bond\", \"cr...</td>\n",
514
+ " <td>[{\"credit_id\": \"54805967c3a36829b5002c41\", \"de...</td>\n",
515
+ " </tr>\n",
516
+ " <tr>\n",
517
+ " <th>3</th>\n",
518
+ " <td>49026</td>\n",
519
+ " <td>The Dark Knight Rises</td>\n",
520
+ " <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
521
+ " <td>Following the death of District Attorney Harve...</td>\n",
522
+ " <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
523
+ " <td>[{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba...</td>\n",
524
+ " <td>[{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de...</td>\n",
525
+ " </tr>\n",
526
+ " <tr>\n",
527
+ " <th>4</th>\n",
528
+ " <td>49529</td>\n",
529
+ " <td>John Carter</td>\n",
530
+ " <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
531
+ " <td>John Carter is a war-weary, former military ca...</td>\n",
532
+ " <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
533
+ " <td>[{\"cast_id\": 5, \"character\": \"John Carter\", \"c...</td>\n",
534
+ " <td>[{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de...</td>\n",
535
+ " </tr>\n",
536
+ " </tbody>\n",
537
+ "</table>\n",
538
+ "</div>"
539
+ ],
540
+ "text/plain": [
541
+ " movie_id title \\\n",
542
+ "0 19995 Avatar \n",
543
+ "1 285 Pirates of the Caribbean: At World's End \n",
544
+ "2 206647 Spectre \n",
545
+ "3 49026 The Dark Knight Rises \n",
546
+ "4 49529 John Carter \n",
547
+ "\n",
548
+ " genres \\\n",
549
+ "0 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam... \n",
550
+ "1 [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"... \n",
551
+ "2 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam... \n",
552
+ "3 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam... \n",
553
+ "4 [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam... \n",
554
+ "\n",
555
+ " overview \\\n",
556
+ "0 In the 22nd century, a paraplegic Marine is di... \n",
557
+ "1 Captain Barbossa, long believed to be dead, ha... \n",
558
+ "2 A cryptic message from Bond’s past sends him o... \n",
559
+ "3 Following the death of District Attorney Harve... \n",
560
+ "4 John Carter is a war-weary, former military ca... \n",
561
+ "\n",
562
+ " keywords \\\n",
563
+ "0 [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":... \n",
564
+ "1 [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na... \n",
565
+ "2 [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name... \n",
566
+ "3 [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,... \n",
567
+ "4 [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":... \n",
568
+ "\n",
569
+ " cast \\\n",
570
+ "0 [{\"cast_id\": 242, \"character\": \"Jake Sully\", \"... \n",
571
+ "1 [{\"cast_id\": 4, \"character\": \"Captain Jack Spa... \n",
572
+ "2 [{\"cast_id\": 1, \"character\": \"James Bond\", \"cr... \n",
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+ "3 [{\"cast_id\": 2, \"character\": \"Bruce Wayne / Ba... \n",
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+ "4 [{\"cast_id\": 5, \"character\": \"John Carter\", \"c... \n",
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+ "\n",
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+ " crew \n",
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+ "0 [{\"credit_id\": \"52fe48009251416c750aca23\", \"de... \n",
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+ "1 [{\"credit_id\": \"52fe4232c3a36847f800b579\", \"de... \n",
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+ "2 [{\"credit_id\": \"54805967c3a36829b5002c41\", \"de... \n",
580
+ "3 [{\"credit_id\": \"52fe4781c3a36847f81398c3\", \"de... \n",
581
+ "4 [{\"credit_id\": \"52fe479ac3a36847f813eaa3\", \"de... "
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+ ]
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+ },
584
+ "execution_count": 8,
585
+ "metadata": {},
586
+ "output_type": "execute_result"
587
+ }
588
+ ],
589
+ "source": [
590
+ "movies.head()"
591
+ ]
592
+ },
593
+ {
594
+ "cell_type": "code",
595
+ "execution_count": 9,
596
+ "id": "309f68b0-46b9-492e-bf0c-605fc91e1e57",
597
+ "metadata": {},
598
+ "outputs": [],
599
+ "source": [
600
+ "movies = movies.dropna()"
601
+ ]
602
+ },
603
+ {
604
+ "cell_type": "code",
605
+ "execution_count": 10,
606
+ "id": "8a22d175-b884-43f5-b013-5fd549100b19",
607
+ "metadata": {},
608
+ "outputs": [
609
+ {
610
+ "data": {
611
+ "text/plain": [
612
+ "movie_id 0\n",
613
+ "title 0\n",
614
+ "genres 0\n",
615
+ "overview 0\n",
616
+ "keywords 0\n",
617
+ "cast 0\n",
618
+ "crew 0\n",
619
+ "dtype: int64"
620
+ ]
621
+ },
622
+ "execution_count": 10,
623
+ "metadata": {},
624
+ "output_type": "execute_result"
625
+ }
626
+ ],
627
+ "source": [
628
+ "movies.isnull().sum()"
629
+ ]
630
+ },
631
+ {
632
+ "cell_type": "code",
633
+ "execution_count": 11,
634
+ "id": "d9f5ccca-3a68-43cd-841e-97e8fdd7f68f",
635
+ "metadata": {},
636
+ "outputs": [
637
+ {
638
+ "data": {
639
+ "text/plain": [
640
+ "0"
641
+ ]
642
+ },
643
+ "execution_count": 11,
644
+ "metadata": {},
645
+ "output_type": "execute_result"
646
+ }
647
+ ],
648
+ "source": [
649
+ "movies.duplicated().sum()"
650
+ ]
651
+ },
652
+ {
653
+ "cell_type": "code",
654
+ "execution_count": 12,
655
+ "id": "517bee9d-a24c-4763-943c-9d81ad7307af",
656
+ "metadata": {},
657
+ "outputs": [],
658
+ "source": [
659
+ "import ast\n",
660
+ "\n",
661
+ "def get_name(string):\n",
662
+ " List = []\n",
663
+ " for i in ast.literal_eval(string):\n",
664
+ " List.append(i['name'])\n",
665
+ " return List\n",
666
+ "\n",
667
+ "\n",
668
+ "def get_cast(string):\n",
669
+ " List = []\n",
670
+ " for i in ast.literal_eval(string):\n",
671
+ " List.append(i['name'])\n",
672
+ " if len(List)==3:\n",
673
+ " return List\n",
674
+ " return List\n",
675
+ "\n",
676
+ "\n",
677
+ "def get_director_name(string):\n",
678
+ " List = []\n",
679
+ " for i in ast.literal_eval(string):\n",
680
+ " if i['job']=='Director':\n",
681
+ " List.append(i['name'])\n",
682
+ " return List\n",
683
+ " return List"
684
+ ]
685
+ },
686
+ {
687
+ "cell_type": "code",
688
+ "execution_count": 13,
689
+ "id": "0be843da-f3f6-43b9-8ef6-da85b57775a5",
690
+ "metadata": {},
691
+ "outputs": [],
692
+ "source": [
693
+ "movies['genres'] = movies['genres'].apply(get_name)\n",
694
+ "movies['keywords'] = movies['keywords'].apply(get_name)"
695
+ ]
696
+ },
697
+ {
698
+ "cell_type": "code",
699
+ "execution_count": 14,
700
+ "id": "a0503645-58d4-4d19-9a9f-5414f8130e24",
701
+ "metadata": {},
702
+ "outputs": [],
703
+ "source": [
704
+ "movies['cast'] = movies['cast'].apply(get_cast)"
705
+ ]
706
+ },
707
+ {
708
+ "cell_type": "code",
709
+ "execution_count": 15,
710
+ "id": "b9b60133-4d3f-4197-af98-b188fa9ccf4c",
711
+ "metadata": {},
712
+ "outputs": [],
713
+ "source": [
714
+ "movies['crew'] = movies['crew'].apply(get_director_name)"
715
+ ]
716
+ },
717
+ {
718
+ "cell_type": "code",
719
+ "execution_count": 16,
720
+ "id": "607f9f9b-f4aa-4e56-a74a-e8dcf351c38f",
721
+ "metadata": {},
722
+ "outputs": [],
723
+ "source": [
724
+ "movies['overview'] = movies['overview'].apply(lambda x: x.split())"
725
+ ]
726
+ },
727
+ {
728
+ "cell_type": "code",
729
+ "execution_count": 17,
730
+ "id": "f0e93004-ae79-4b40-9323-7cb9fd9908bf",
731
+ "metadata": {},
732
+ "outputs": [],
733
+ "source": [
734
+ "movies['genres'] = movies['genres'].apply(lambda x: [i.replace(' ', '') for i in x])\n",
735
+ "movies['overview'] = movies['overview'].apply(lambda x: [i.replace(' ', '') for i in x])\n",
736
+ "movies['keywords'] = movies['keywords'].apply(lambda x: [i.replace(' ', '') for i in x])\n",
737
+ "movies['cast'] = movies['cast'].apply(lambda x: [i.replace(' ', '') for i in x])\n",
738
+ "movies['crew'] = movies['crew'].apply(lambda x: [i.replace(' ', '') for i in x])"
739
+ ]
740
+ },
741
+ {
742
+ "cell_type": "code",
743
+ "execution_count": 18,
744
+ "id": "0019446c-147f-493c-a0c7-6679b13b5b5d",
745
+ "metadata": {},
746
+ "outputs": [
747
+ {
748
+ "data": {
749
+ "text/plain": [
750
+ "movie_id 0\n",
751
+ "title 0\n",
752
+ "genres 0\n",
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+ "overview 0\n",
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+ "keywords 0\n",
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+ "cast 0\n",
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+ "crew 0\n",
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+ "dtype: int64"
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+ ]
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+ },
760
+ "execution_count": 18,
761
+ "metadata": {},
762
+ "output_type": "execute_result"
763
+ }
764
+ ],
765
+ "source": [
766
+ "movies.isnull().sum()"
767
+ ]
768
+ },
769
+ {
770
+ "cell_type": "code",
771
+ "execution_count": 19,
772
+ "id": "d6b495e5-1d34-46fc-9d15-9385c15e0840",
773
+ "metadata": {},
774
+ "outputs": [
775
+ {
776
+ "data": {
777
+ "text/html": [
778
+ "<div>\n",
779
+ "<style scoped>\n",
780
+ " .dataframe tbody tr th:only-of-type {\n",
781
+ " vertical-align: middle;\n",
782
+ " }\n",
783
+ "\n",
784
+ " .dataframe tbody tr th {\n",
785
+ " vertical-align: top;\n",
786
+ " }\n",
787
+ "\n",
788
+ " .dataframe thead th {\n",
789
+ " text-align: right;\n",
790
+ " }\n",
791
+ "</style>\n",
792
+ "<table border=\"1\" class=\"dataframe\">\n",
793
+ " <thead>\n",
794
+ " <tr style=\"text-align: right;\">\n",
795
+ " <th></th>\n",
796
+ " <th>movie_id</th>\n",
797
+ " <th>title</th>\n",
798
+ " <th>genres</th>\n",
799
+ " <th>overview</th>\n",
800
+ " <th>keywords</th>\n",
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+ " <th>cast</th>\n",
802
+ " <th>crew</th>\n",
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+ " </tr>\n",
804
+ " </thead>\n",
805
+ " <tbody>\n",
806
+ " <tr>\n",
807
+ " <th>0</th>\n",
808
+ " <td>19995</td>\n",
809
+ " <td>Avatar</td>\n",
810
+ " <td>[Action, Adventure, Fantasy, ScienceFiction]</td>\n",
811
+ " <td>[In, the, 22nd, century,, a, paraplegic, Marin...</td>\n",
812
+ " <td>[cultureclash, future, spacewar, spacecolony, ...</td>\n",
813
+ " <td>[SamWorthington, ZoeSaldana, SigourneyWeaver]</td>\n",
814
+ " <td>[JamesCameron]</td>\n",
815
+ " </tr>\n",
816
+ " <tr>\n",
817
+ " <th>1</th>\n",
818
+ " <td>285</td>\n",
819
+ " <td>Pirates of the Caribbean: At World's End</td>\n",
820
+ " <td>[Adventure, Fantasy, Action]</td>\n",
821
+ " <td>[Captain, Barbossa,, long, believed, to, be, d...</td>\n",
822
+ " <td>[ocean, drugabuse, exoticisland, eastindiatrad...</td>\n",
823
+ " <td>[JohnnyDepp, OrlandoBloom, KeiraKnightley]</td>\n",
824
+ " <td>[GoreVerbinski]</td>\n",
825
+ " </tr>\n",
826
+ " <tr>\n",
827
+ " <th>2</th>\n",
828
+ " <td>206647</td>\n",
829
+ " <td>Spectre</td>\n",
830
+ " <td>[Action, Adventure, Crime]</td>\n",
831
+ " <td>[A, cryptic, message, from, Bond’s, past, send...</td>\n",
832
+ " <td>[spy, basedonnovel, secretagent, sequel, mi6, ...</td>\n",
833
+ " <td>[DanielCraig, ChristophWaltz, LéaSeydoux]</td>\n",
834
+ " <td>[SamMendes]</td>\n",
835
+ " </tr>\n",
836
+ " <tr>\n",
837
+ " <th>3</th>\n",
838
+ " <td>49026</td>\n",
839
+ " <td>The Dark Knight Rises</td>\n",
840
+ " <td>[Action, Crime, Drama, Thriller]</td>\n",
841
+ " <td>[Following, the, death, of, District, Attorney...</td>\n",
842
+ " <td>[dccomics, crimefighter, terrorist, secretiden...</td>\n",
843
+ " <td>[ChristianBale, MichaelCaine, GaryOldman]</td>\n",
844
+ " <td>[ChristopherNolan]</td>\n",
845
+ " </tr>\n",
846
+ " <tr>\n",
847
+ " <th>4</th>\n",
848
+ " <td>49529</td>\n",
849
+ " <td>John Carter</td>\n",
850
+ " <td>[Action, Adventure, ScienceFiction]</td>\n",
851
+ " <td>[John, Carter, is, a, war-weary,, former, mili...</td>\n",
852
+ " <td>[basedonnovel, mars, medallion, spacetravel, p...</td>\n",
853
+ " <td>[TaylorKitsch, LynnCollins, SamanthaMorton]</td>\n",
854
+ " <td>[AndrewStanton]</td>\n",
855
+ " </tr>\n",
856
+ " <tr>\n",
857
+ " <th>...</th>\n",
858
+ " <td>...</td>\n",
859
+ " <td>...</td>\n",
860
+ " <td>...</td>\n",
861
+ " <td>...</td>\n",
862
+ " <td>...</td>\n",
863
+ " <td>...</td>\n",
864
+ " <td>...</td>\n",
865
+ " </tr>\n",
866
+ " <tr>\n",
867
+ " <th>4804</th>\n",
868
+ " <td>9367</td>\n",
869
+ " <td>El Mariachi</td>\n",
870
+ " <td>[Action, Crime, Thriller]</td>\n",
871
+ " <td>[El, Mariachi, just, wants, to, play, his, gui...</td>\n",
872
+ " <td>[unitedstates–mexicobarrier, legs, arms, paper...</td>\n",
873
+ " <td>[CarlosGallardo, JaimedeHoyos, PeterMarquardt]</td>\n",
874
+ " <td>[RobertRodriguez]</td>\n",
875
+ " </tr>\n",
876
+ " <tr>\n",
877
+ " <th>4805</th>\n",
878
+ " <td>72766</td>\n",
879
+ " <td>Newlyweds</td>\n",
880
+ " <td>[Comedy, Romance]</td>\n",
881
+ " <td>[A, newlywed, couple's, honeymoon, is, upended...</td>\n",
882
+ " <td>[]</td>\n",
883
+ " <td>[EdwardBurns, KerryBishé, MarshaDietlein]</td>\n",
884
+ " <td>[EdwardBurns]</td>\n",
885
+ " </tr>\n",
886
+ " <tr>\n",
887
+ " <th>4806</th>\n",
888
+ " <td>231617</td>\n",
889
+ " <td>Signed, Sealed, Delivered</td>\n",
890
+ " <td>[Comedy, Drama, Romance, TVMovie]</td>\n",
891
+ " <td>[\"Signed,, Sealed,, Delivered\", introduces, a,...</td>\n",
892
+ " <td>[date, loveatfirstsight, narration, investigat...</td>\n",
893
+ " <td>[EricMabius, KristinBooth, CrystalLowe]</td>\n",
894
+ " <td>[ScottSmith]</td>\n",
895
+ " </tr>\n",
896
+ " <tr>\n",
897
+ " <th>4807</th>\n",
898
+ " <td>126186</td>\n",
899
+ " <td>Shanghai Calling</td>\n",
900
+ " <td>[]</td>\n",
901
+ " <td>[When, ambitious, New, York, attorney, Sam, is...</td>\n",
902
+ " <td>[]</td>\n",
903
+ " <td>[DanielHenney, ElizaCoupe, BillPaxton]</td>\n",
904
+ " <td>[DanielHsia]</td>\n",
905
+ " </tr>\n",
906
+ " <tr>\n",
907
+ " <th>4808</th>\n",
908
+ " <td>25975</td>\n",
909
+ " <td>My Date with Drew</td>\n",
910
+ " <td>[Documentary]</td>\n",
911
+ " <td>[Ever, since, the, second, grade, when, he, fi...</td>\n",
912
+ " <td>[obsession, camcorder, crush, dreamgirl]</td>\n",
913
+ " <td>[DrewBarrymore, BrianHerzlinger, CoreyFeldman]</td>\n",
914
+ " <td>[BrianHerzlinger]</td>\n",
915
+ " </tr>\n",
916
+ " </tbody>\n",
917
+ "</table>\n",
918
+ "<p>4806 rows × 7 columns</p>\n",
919
+ "</div>"
920
+ ],
921
+ "text/plain": [
922
+ " movie_id title \\\n",
923
+ "0 19995 Avatar \n",
924
+ "1 285 Pirates of the Caribbean: At World's End \n",
925
+ "2 206647 Spectre \n",
926
+ "3 49026 The Dark Knight Rises \n",
927
+ "4 49529 John Carter \n",
928
+ "... ... ... \n",
929
+ "4804 9367 El Mariachi \n",
930
+ "4805 72766 Newlyweds \n",
931
+ "4806 231617 Signed, Sealed, Delivered \n",
932
+ "4807 126186 Shanghai Calling \n",
933
+ "4808 25975 My Date with Drew \n",
934
+ "\n",
935
+ " genres \\\n",
936
+ "0 [Action, Adventure, Fantasy, ScienceFiction] \n",
937
+ "1 [Adventure, Fantasy, Action] \n",
938
+ "2 [Action, Adventure, Crime] \n",
939
+ "3 [Action, Crime, Drama, Thriller] \n",
940
+ "4 [Action, Adventure, ScienceFiction] \n",
941
+ "... ... \n",
942
+ "4804 [Action, Crime, Thriller] \n",
943
+ "4805 [Comedy, Romance] \n",
944
+ "4806 [Comedy, Drama, Romance, TVMovie] \n",
945
+ "4807 [] \n",
946
+ "4808 [Documentary] \n",
947
+ "\n",
948
+ " overview \\\n",
949
+ "0 [In, the, 22nd, century,, a, paraplegic, Marin... \n",
950
+ "1 [Captain, Barbossa,, long, believed, to, be, d... \n",
951
+ "2 [A, cryptic, message, from, Bond’s, past, send... \n",
952
+ "3 [Following, the, death, of, District, Attorney... \n",
953
+ "4 [John, Carter, is, a, war-weary,, former, mili... \n",
954
+ "... ... \n",
955
+ "4804 [El, Mariachi, just, wants, to, play, his, gui... \n",
956
+ "4805 [A, newlywed, couple's, honeymoon, is, upended... \n",
957
+ "4806 [\"Signed,, Sealed,, Delivered\", introduces, a,... \n",
958
+ "4807 [When, ambitious, New, York, attorney, Sam, is... \n",
959
+ "4808 [Ever, since, the, second, grade, when, he, fi... \n",
960
+ "\n",
961
+ " keywords \\\n",
962
+ "0 [cultureclash, future, spacewar, spacecolony, ... \n",
963
+ "1 [ocean, drugabuse, exoticisland, eastindiatrad... \n",
964
+ "2 [spy, basedonnovel, secretagent, sequel, mi6, ... \n",
965
+ "3 [dccomics, crimefighter, terrorist, secretiden... \n",
966
+ "4 [basedonnovel, mars, medallion, spacetravel, p... \n",
967
+ "... ... \n",
968
+ "4804 [unitedstates–mexicobarrier, legs, arms, paper... \n",
969
+ "4805 [] \n",
970
+ "4806 [date, loveatfirstsight, narration, investigat... \n",
971
+ "4807 [] \n",
972
+ "4808 [obsession, camcorder, crush, dreamgirl] \n",
973
+ "\n",
974
+ " cast crew \n",
975
+ "0 [SamWorthington, ZoeSaldana, SigourneyWeaver] [JamesCameron] \n",
976
+ "1 [JohnnyDepp, OrlandoBloom, KeiraKnightley] [GoreVerbinski] \n",
977
+ "2 [DanielCraig, ChristophWaltz, LéaSeydoux] [SamMendes] \n",
978
+ "3 [ChristianBale, MichaelCaine, GaryOldman] [ChristopherNolan] \n",
979
+ "4 [TaylorKitsch, LynnCollins, SamanthaMorton] [AndrewStanton] \n",
980
+ "... ... ... \n",
981
+ "4804 [CarlosGallardo, JaimedeHoyos, PeterMarquardt] [RobertRodriguez] \n",
982
+ "4805 [EdwardBurns, KerryBishé, MarshaDietlein] [EdwardBurns] \n",
983
+ "4806 [EricMabius, KristinBooth, CrystalLowe] [ScottSmith] \n",
984
+ "4807 [DanielHenney, ElizaCoupe, BillPaxton] [DanielHsia] \n",
985
+ "4808 [DrewBarrymore, BrianHerzlinger, CoreyFeldman] [BrianHerzlinger] \n",
986
+ "\n",
987
+ "[4806 rows x 7 columns]"
988
+ ]
989
+ },
990
+ "execution_count": 19,
991
+ "metadata": {},
992
+ "output_type": "execute_result"
993
+ }
994
+ ],
995
+ "source": [
996
+ "movies"
997
+ ]
998
+ },
999
+ {
1000
+ "cell_type": "code",
1001
+ "execution_count": 20,
1002
+ "id": "63cb68c3-8bcb-413b-bca2-f2ab12f6bcb2",
1003
+ "metadata": {},
1004
+ "outputs": [],
1005
+ "source": [
1006
+ "movies['tags'] = movies['overview'] + movies['genres'] + movies['keywords'] + movies['cast'] + movies['crew']\n",
1007
+ "movies = movies[['movie_id', 'title', 'tags']]"
1008
+ ]
1009
+ },
1010
+ {
1011
+ "cell_type": "code",
1012
+ "execution_count": 21,
1013
+ "id": "3eccb9ec-d8af-4cb6-99f5-256f8722d643",
1014
+ "metadata": {},
1015
+ "outputs": [
1016
+ {
1017
+ "name": "stderr",
1018
+ "output_type": "stream",
1019
+ "text": [
1020
+ "C:\\Users\\thaku\\AppData\\Local\\Temp\\ipykernel_7988\\2153568569.py:1: SettingWithCopyWarning: \n",
1021
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
1022
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
1023
+ "\n",
1024
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
1025
+ " movies['tags'] = movies['tags'].apply(lambda x: \" \".join(x))\n"
1026
+ ]
1027
+ }
1028
+ ],
1029
+ "source": [
1030
+ "movies['tags'] = movies['tags'].apply(lambda x: \" \".join(x))"
1031
+ ]
1032
+ },
1033
+ {
1034
+ "cell_type": "code",
1035
+ "execution_count": 22,
1036
+ "id": "2d415c55-fdcf-4d26-9feb-2eb20659831c",
1037
+ "metadata": {},
1038
+ "outputs": [
1039
+ {
1040
+ "name": "stderr",
1041
+ "output_type": "stream",
1042
+ "text": [
1043
+ "C:\\Users\\thaku\\AppData\\Local\\Temp\\ipykernel_7988\\3982405354.py:1: SettingWithCopyWarning: \n",
1044
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
1045
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
1046
+ "\n",
1047
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
1048
+ " movies['tags'] = movies['tags'].apply(lambda x: x.lower())\n"
1049
+ ]
1050
+ }
1051
+ ],
1052
+ "source": [
1053
+ "movies['tags'] = movies['tags'].apply(lambda x: x.lower())"
1054
+ ]
1055
+ },
1056
+ {
1057
+ "cell_type": "code",
1058
+ "execution_count": 23,
1059
+ "id": "0b5ebd6d-6e36-4fbd-9fb3-3e933a27bfc1",
1060
+ "metadata": {},
1061
+ "outputs": [
1062
+ {
1063
+ "data": {
1064
+ "text/plain": [
1065
+ "'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. action adventure fantasy sciencefiction cultureclash future spacewar spacecolony society spacetravel futuristic romance space alien tribe alienplanet cgi marine soldier battle loveaffair antiwar powerrelations mindandsoul 3d samworthington zoesaldana sigourneyweaver jamescameron'"
1066
+ ]
1067
+ },
1068
+ "execution_count": 23,
1069
+ "metadata": {},
1070
+ "output_type": "execute_result"
1071
+ }
1072
+ ],
1073
+ "source": [
1074
+ "movies.iloc[0]['tags']"
1075
+ ]
1076
+ },
1077
+ {
1078
+ "cell_type": "code",
1079
+ "execution_count": 24,
1080
+ "id": "bf04370b-e001-4271-8c96-f4280ab66bec",
1081
+ "metadata": {
1082
+ "scrolled": true
1083
+ },
1084
+ "outputs": [
1085
+ {
1086
+ "ename": "TypeError",
1087
+ "evalue": "PorterStemmer.stem() missing 1 required positional argument: 'word'",
1088
+ "output_type": "error",
1089
+ "traceback": [
1090
+ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
1091
+ "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
1092
+ "Cell \u001b[1;32mIn[24], line 12\u001b[0m\n\u001b[0;32m 9\u001b[0m List\u001b[38;5;241m.\u001b[39mappend(ps\u001b[38;5;241m.\u001b[39mstem(i))\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(List)\n\u001b[1;32m---> 12\u001b[0m movies[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtags\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mmovies\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtags\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstem\u001b[49m\u001b[43m)\u001b[49m\n",
1093
+ "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\pandas\\core\\series.py:4924\u001b[0m, in \u001b[0;36mSeries.apply\u001b[1;34m(self, func, convert_dtype, args, by_row, **kwargs)\u001b[0m\n\u001b[0;32m 4789\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply\u001b[39m(\n\u001b[0;32m 4790\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 4791\u001b[0m func: AggFuncType,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 4796\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[0;32m 4797\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Series:\n\u001b[0;32m 4798\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 4799\u001b[0m \u001b[38;5;124;03m Invoke function on values of Series.\u001b[39;00m\n\u001b[0;32m 4800\u001b[0m \n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 4915\u001b[0m \u001b[38;5;124;03m dtype: float64\u001b[39;00m\n\u001b[0;32m 4916\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m 4917\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mSeriesApply\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 4918\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4919\u001b[0m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4920\u001b[0m \u001b[43m \u001b[49m\u001b[43mconvert_dtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert_dtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4921\u001b[0m \u001b[43m \u001b[49m\u001b[43mby_row\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mby_row\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4922\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4923\u001b[0m \u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m-> 4924\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
1094
+ "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\pandas\\core\\apply.py:1427\u001b[0m, in \u001b[0;36mSeriesApply.apply\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 1424\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapply_compat()\n\u001b[0;32m 1426\u001b[0m \u001b[38;5;66;03m# self.func is Callable\u001b[39;00m\n\u001b[1;32m-> 1427\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_standard\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
1095
+ "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\pandas\\core\\apply.py:1507\u001b[0m, in \u001b[0;36mSeriesApply.apply_standard\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 1501\u001b[0m \u001b[38;5;66;03m# row-wise access\u001b[39;00m\n\u001b[0;32m 1502\u001b[0m \u001b[38;5;66;03m# apply doesn't have a `na_action` keyword and for backward compat reasons\u001b[39;00m\n\u001b[0;32m 1503\u001b[0m \u001b[38;5;66;03m# we need to give `na_action=\"ignore\"` for categorical data.\u001b[39;00m\n\u001b[0;32m 1504\u001b[0m \u001b[38;5;66;03m# TODO: remove the `na_action=\"ignore\"` when that default has been changed in\u001b[39;00m\n\u001b[0;32m 1505\u001b[0m \u001b[38;5;66;03m# Categorical (GH51645).\u001b[39;00m\n\u001b[0;32m 1506\u001b[0m action \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(obj\u001b[38;5;241m.\u001b[39mdtype, CategoricalDtype) \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m-> 1507\u001b[0m mapped \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_map_values\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1508\u001b[0m \u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcurried\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mna_action\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maction\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconvert_dtype\u001b[49m\n\u001b[0;32m 1509\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1511\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(mapped) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(mapped[\u001b[38;5;241m0\u001b[39m], ABCSeries):\n\u001b[0;32m 1512\u001b[0m \u001b[38;5;66;03m# GH#43986 Need to do list(mapped) in order to get treated as nested\u001b[39;00m\n\u001b[0;32m 1513\u001b[0m \u001b[38;5;66;03m# See also GH#25959 regarding EA support\u001b[39;00m\n\u001b[0;32m 1514\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj\u001b[38;5;241m.\u001b[39m_constructor_expanddim(\u001b[38;5;28mlist\u001b[39m(mapped), index\u001b[38;5;241m=\u001b[39mobj\u001b[38;5;241m.\u001b[39mindex)\n",
1096
+ "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\pandas\\core\\base.py:921\u001b[0m, in \u001b[0;36mIndexOpsMixin._map_values\u001b[1;34m(self, mapper, na_action, convert)\u001b[0m\n\u001b[0;32m 918\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(arr, ExtensionArray):\n\u001b[0;32m 919\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mmap(mapper, na_action\u001b[38;5;241m=\u001b[39mna_action)\n\u001b[1;32m--> 921\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43malgorithms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43marr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mna_action\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mna_action\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n",
1097
+ "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\pandas\\core\\algorithms.py:1743\u001b[0m, in \u001b[0;36mmap_array\u001b[1;34m(arr, mapper, na_action, convert)\u001b[0m\n\u001b[0;32m 1741\u001b[0m values \u001b[38;5;241m=\u001b[39m arr\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mobject\u001b[39m, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m 1742\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m na_action \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 1743\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_infer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1744\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 1745\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mmap_infer_mask(\n\u001b[0;32m 1746\u001b[0m values, mapper, mask\u001b[38;5;241m=\u001b[39misna(values)\u001b[38;5;241m.\u001b[39mview(np\u001b[38;5;241m.\u001b[39muint8), convert\u001b[38;5;241m=\u001b[39mconvert\n\u001b[0;32m 1747\u001b[0m )\n",
1098
+ "File \u001b[1;32mlib.pyx:2972\u001b[0m, in \u001b[0;36mpandas._libs.lib.map_infer\u001b[1;34m()\u001b[0m\n",
1099
+ "Cell \u001b[1;32mIn[24], line 9\u001b[0m, in \u001b[0;36mstem\u001b[1;34m(text)\u001b[0m\n\u001b[0;32m 7\u001b[0m List \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m text\u001b[38;5;241m.\u001b[39msplit():\n\u001b[1;32m----> 9\u001b[0m List\u001b[38;5;241m.\u001b[39mappend(\u001b[43mps\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstem\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(List)\n",
1100
+ "\u001b[1;31mTypeError\u001b[0m: PorterStemmer.stem() missing 1 required positional argument: 'word'"
1101
+ ]
1102
+ }
1103
+ ],
1104
+ "source": [
1105
+ "# import nltk\n",
1106
+ "# from nltk.stem.porter import PorterStemmer\n",
1107
+ "\n",
1108
+ "# ps = PorterStemmer\n",
1109
+ "\n",
1110
+ "# def stem(text):\n",
1111
+ "# List = []\n",
1112
+ "# for i in text.split():\n",
1113
+ "# List.append(ps.stem(i))\n",
1114
+ "# return \" \".join(List)\n",
1115
+ "\n",
1116
+ "# movies['tags'] = movies['tags'].apply(stem)"
1117
+ ]
1118
+ },
1119
+ {
1120
+ "cell_type": "code",
1121
+ "execution_count": 25,
1122
+ "id": "a0ee92b1-3376-432e-9d9c-2ee37a236d9d",
1123
+ "metadata": {},
1124
+ "outputs": [
1125
+ {
1126
+ "data": {
1127
+ "text/html": [
1128
+ "<div>\n",
1129
+ "<style scoped>\n",
1130
+ " .dataframe tbody tr th:only-of-type {\n",
1131
+ " vertical-align: middle;\n",
1132
+ " }\n",
1133
+ "\n",
1134
+ " .dataframe tbody tr th {\n",
1135
+ " vertical-align: top;\n",
1136
+ " }\n",
1137
+ "\n",
1138
+ " .dataframe thead th {\n",
1139
+ " text-align: right;\n",
1140
+ " }\n",
1141
+ "</style>\n",
1142
+ "<table border=\"1\" class=\"dataframe\">\n",
1143
+ " <thead>\n",
1144
+ " <tr style=\"text-align: right;\">\n",
1145
+ " <th></th>\n",
1146
+ " <th>movie_id</th>\n",
1147
+ " <th>title</th>\n",
1148
+ " <th>tags</th>\n",
1149
+ " </tr>\n",
1150
+ " </thead>\n",
1151
+ " <tbody>\n",
1152
+ " <tr>\n",
1153
+ " <th>0</th>\n",
1154
+ " <td>19995</td>\n",
1155
+ " <td>Avatar</td>\n",
1156
+ " <td>in the 22nd century, a paraplegic marine is di...</td>\n",
1157
+ " </tr>\n",
1158
+ " <tr>\n",
1159
+ " <th>1</th>\n",
1160
+ " <td>285</td>\n",
1161
+ " <td>Pirates of the Caribbean: At World's End</td>\n",
1162
+ " <td>captain barbossa, long believed to be dead, ha...</td>\n",
1163
+ " </tr>\n",
1164
+ " <tr>\n",
1165
+ " <th>2</th>\n",
1166
+ " <td>206647</td>\n",
1167
+ " <td>Spectre</td>\n",
1168
+ " <td>a cryptic message from bond’s past sends him o...</td>\n",
1169
+ " </tr>\n",
1170
+ " <tr>\n",
1171
+ " <th>3</th>\n",
1172
+ " <td>49026</td>\n",
1173
+ " <td>The Dark Knight Rises</td>\n",
1174
+ " <td>following the death of district attorney harve...</td>\n",
1175
+ " </tr>\n",
1176
+ " <tr>\n",
1177
+ " <th>4</th>\n",
1178
+ " <td>49529</td>\n",
1179
+ " <td>John Carter</td>\n",
1180
+ " <td>john carter is a war-weary, former military ca...</td>\n",
1181
+ " </tr>\n",
1182
+ " <tr>\n",
1183
+ " <th>...</th>\n",
1184
+ " <td>...</td>\n",
1185
+ " <td>...</td>\n",
1186
+ " <td>...</td>\n",
1187
+ " </tr>\n",
1188
+ " <tr>\n",
1189
+ " <th>4804</th>\n",
1190
+ " <td>9367</td>\n",
1191
+ " <td>El Mariachi</td>\n",
1192
+ " <td>el mariachi just wants to play his guitar and ...</td>\n",
1193
+ " </tr>\n",
1194
+ " <tr>\n",
1195
+ " <th>4805</th>\n",
1196
+ " <td>72766</td>\n",
1197
+ " <td>Newlyweds</td>\n",
1198
+ " <td>a newlywed couple's honeymoon is upended by th...</td>\n",
1199
+ " </tr>\n",
1200
+ " <tr>\n",
1201
+ " <th>4806</th>\n",
1202
+ " <td>231617</td>\n",
1203
+ " <td>Signed, Sealed, Delivered</td>\n",
1204
+ " <td>\"signed, sealed, delivered\" introduces a dedic...</td>\n",
1205
+ " </tr>\n",
1206
+ " <tr>\n",
1207
+ " <th>4807</th>\n",
1208
+ " <td>126186</td>\n",
1209
+ " <td>Shanghai Calling</td>\n",
1210
+ " <td>when ambitious new york attorney sam is sent t...</td>\n",
1211
+ " </tr>\n",
1212
+ " <tr>\n",
1213
+ " <th>4808</th>\n",
1214
+ " <td>25975</td>\n",
1215
+ " <td>My Date with Drew</td>\n",
1216
+ " <td>ever since the second grade when he first saw ...</td>\n",
1217
+ " </tr>\n",
1218
+ " </tbody>\n",
1219
+ "</table>\n",
1220
+ "<p>4806 rows × 3 columns</p>\n",
1221
+ "</div>"
1222
+ ],
1223
+ "text/plain": [
1224
+ " movie_id title \\\n",
1225
+ "0 19995 Avatar \n",
1226
+ "1 285 Pirates of the Caribbean: At World's End \n",
1227
+ "2 206647 Spectre \n",
1228
+ "3 49026 The Dark Knight Rises \n",
1229
+ "4 49529 John Carter \n",
1230
+ "... ... ... \n",
1231
+ "4804 9367 El Mariachi \n",
1232
+ "4805 72766 Newlyweds \n",
1233
+ "4806 231617 Signed, Sealed, Delivered \n",
1234
+ "4807 126186 Shanghai Calling \n",
1235
+ "4808 25975 My Date with Drew \n",
1236
+ "\n",
1237
+ " tags \n",
1238
+ "0 in the 22nd century, a paraplegic marine is di... \n",
1239
+ "1 captain barbossa, long believed to be dead, ha... \n",
1240
+ "2 a cryptic message from bond’s past sends him o... \n",
1241
+ "3 following the death of district attorney harve... \n",
1242
+ "4 john carter is a war-weary, former military ca... \n",
1243
+ "... ... \n",
1244
+ "4804 el mariachi just wants to play his guitar and ... \n",
1245
+ "4805 a newlywed couple's honeymoon is upended by th... \n",
1246
+ "4806 \"signed, sealed, delivered\" introduces a dedic... \n",
1247
+ "4807 when ambitious new york attorney sam is sent t... \n",
1248
+ "4808 ever since the second grade when he first saw ... \n",
1249
+ "\n",
1250
+ "[4806 rows x 3 columns]"
1251
+ ]
1252
+ },
1253
+ "execution_count": 25,
1254
+ "metadata": {},
1255
+ "output_type": "execute_result"
1256
+ }
1257
+ ],
1258
+ "source": [
1259
+ "movies"
1260
+ ]
1261
+ },
1262
+ {
1263
+ "cell_type": "code",
1264
+ "execution_count": 26,
1265
+ "id": "9f521536-b865-49f5-8996-dcbc7982e641",
1266
+ "metadata": {},
1267
+ "outputs": [],
1268
+ "source": [
1269
+ "from sklearn.feature_extraction.text import CountVectorizer\n",
1270
+ "\n",
1271
+ "cv = CountVectorizer(max_features=5000, stop_words='english')"
1272
+ ]
1273
+ },
1274
+ {
1275
+ "cell_type": "code",
1276
+ "execution_count": 27,
1277
+ "id": "2a802077-3472-476f-a649-c40158bc97cb",
1278
+ "metadata": {},
1279
+ "outputs": [],
1280
+ "source": [
1281
+ "vectors = cv.fit_transform(movies['tags']).toarray()"
1282
+ ]
1283
+ },
1284
+ {
1285
+ "cell_type": "code",
1286
+ "execution_count": 28,
1287
+ "id": "3aed858d-ed14-4840-ac00-ce11406db70b",
1288
+ "metadata": {},
1289
+ "outputs": [
1290
+ {
1291
+ "data": {
1292
+ "text/plain": [
1293
+ "array([[0, 0, 0, ..., 0, 0, 0],\n",
1294
+ " [0, 0, 0, ..., 0, 0, 0],\n",
1295
+ " [0, 0, 0, ..., 0, 0, 0],\n",
1296
+ " ...,\n",
1297
+ " [0, 0, 0, ..., 0, 0, 0],\n",
1298
+ " [0, 0, 0, ..., 0, 0, 0],\n",
1299
+ " [0, 0, 0, ..., 0, 0, 0]], dtype=int64)"
1300
+ ]
1301
+ },
1302
+ "execution_count": 28,
1303
+ "metadata": {},
1304
+ "output_type": "execute_result"
1305
+ }
1306
+ ],
1307
+ "source": [
1308
+ "vectors"
1309
+ ]
1310
+ },
1311
+ {
1312
+ "cell_type": "code",
1313
+ "execution_count": 30,
1314
+ "id": "174f33cc-34dd-4c8d-86c8-ed7e9a7a01c7",
1315
+ "metadata": {},
1316
+ "outputs": [
1317
+ {
1318
+ "name": "stdout",
1319
+ "output_type": "stream",
1320
+ "text": [
1321
+ "['000' '007' '10' ... 'zone' 'zoo' 'zooeydeschanel']\n"
1322
+ ]
1323
+ }
1324
+ ],
1325
+ "source": [
1326
+ "print(cv.get_feature_names_out())"
1327
+ ]
1328
+ },
1329
+ {
1330
+ "cell_type": "code",
1331
+ "execution_count": 31,
1332
+ "id": "10a5bb71-f03c-4b16-ab13-f7c70b8d7dc7",
1333
+ "metadata": {},
1334
+ "outputs": [],
1335
+ "source": [
1336
+ "from sklearn.metrics.pairwise import cosine_similarity"
1337
+ ]
1338
+ },
1339
+ {
1340
+ "cell_type": "code",
1341
+ "execution_count": 32,
1342
+ "id": "b693799b-7b86-41cf-8299-3e109dd2cc48",
1343
+ "metadata": {},
1344
+ "outputs": [
1345
+ {
1346
+ "data": {
1347
+ "text/plain": [
1348
+ "array([[1. , 0.08964215, 0.05976143, ..., 0.02519763, 0.02817181,\n",
1349
+ " 0. ],\n",
1350
+ " [0.08964215, 1. , 0.0625 , ..., 0.02635231, 0. ,\n",
1351
+ " 0. ],\n",
1352
+ " [0.05976143, 0.0625 , 1. , ..., 0.02635231, 0. ,\n",
1353
+ " 0. ],\n",
1354
+ " ...,\n",
1355
+ " [0.02519763, 0.02635231, 0.02635231, ..., 1. , 0.0745356 ,\n",
1356
+ " 0.04836508],\n",
1357
+ " [0.02817181, 0. , 0. , ..., 0.0745356 , 1. ,\n",
1358
+ " 0.05407381],\n",
1359
+ " [0. , 0. , 0. , ..., 0.04836508, 0.05407381,\n",
1360
+ " 1. ]])"
1361
+ ]
1362
+ },
1363
+ "execution_count": 32,
1364
+ "metadata": {},
1365
+ "output_type": "execute_result"
1366
+ }
1367
+ ],
1368
+ "source": [
1369
+ "movies_cos_sim = cosine_similarity(vectors)\n",
1370
+ "movies_cos_sim"
1371
+ ]
1372
+ },
1373
+ {
1374
+ "cell_type": "code",
1375
+ "execution_count": 33,
1376
+ "id": "f2b04fdc-7764-4fe7-a401-63833468fd85",
1377
+ "metadata": {},
1378
+ "outputs": [
1379
+ {
1380
+ "data": {
1381
+ "text/plain": [
1382
+ "(4806, 4806)"
1383
+ ]
1384
+ },
1385
+ "execution_count": 33,
1386
+ "metadata": {},
1387
+ "output_type": "execute_result"
1388
+ }
1389
+ ],
1390
+ "source": [
1391
+ "movies_cos_sim.shape"
1392
+ ]
1393
+ },
1394
+ {
1395
+ "cell_type": "code",
1396
+ "execution_count": 101,
1397
+ "id": "21306d5b-1bce-4508-a8ed-85e41be6af95",
1398
+ "metadata": {},
1399
+ "outputs": [],
1400
+ "source": [
1401
+ "def recommend(movie):\n",
1402
+ " if movie in movies['title'].tolist():\n",
1403
+ " index = movies[movies['title']==movie].index[0]\n",
1404
+ " ascending_indices = movies_cos_sim[index].argsort()\n",
1405
+ " descending_indices = ascending_indices[::-1]\n",
1406
+ " return movies.iloc[descending_indices[1:21]]['title'].tolist()\n",
1407
+ " else:\n",
1408
+ " return 'movie not found in dataset'"
1409
+ ]
1410
+ },
1411
+ {
1412
+ "cell_type": "code",
1413
+ "execution_count": 133,
1414
+ "id": "be12e60c-1a10-4cb3-a9cd-b3fe1174f91b",
1415
+ "metadata": {},
1416
+ "outputs": [
1417
+ {
1418
+ "name": "stdin",
1419
+ "output_type": "stream",
1420
+ "text": [
1421
+ "movie : My Fault\n"
1422
+ ]
1423
+ },
1424
+ {
1425
+ "name": "stdout",
1426
+ "output_type": "stream",
1427
+ "text": [
1428
+ "m\n",
1429
+ "o\n",
1430
+ "v\n",
1431
+ "i\n",
1432
+ "e\n",
1433
+ " \n",
1434
+ "n\n",
1435
+ "o\n",
1436
+ "t\n",
1437
+ " \n",
1438
+ "f\n",
1439
+ "o\n",
1440
+ "u\n",
1441
+ "n\n",
1442
+ "d\n",
1443
+ " \n",
1444
+ "i\n",
1445
+ "n\n",
1446
+ " \n",
1447
+ "d\n",
1448
+ "a\n",
1449
+ "t\n",
1450
+ "a\n",
1451
+ "s\n",
1452
+ "e\n",
1453
+ "t\n",
1454
+ "----------------------------------------------------------------------------------------------\n"
1455
+ ]
1456
+ },
1457
+ {
1458
+ "name": "stdin",
1459
+ "output_type": "stream",
1460
+ "text": [
1461
+ "movie : God Father\n"
1462
+ ]
1463
+ },
1464
+ {
1465
+ "name": "stdout",
1466
+ "output_type": "stream",
1467
+ "text": [
1468
+ "m\n",
1469
+ "o\n",
1470
+ "v\n",
1471
+ "i\n",
1472
+ "e\n",
1473
+ " \n",
1474
+ "n\n",
1475
+ "o\n",
1476
+ "t\n",
1477
+ " \n",
1478
+ "f\n",
1479
+ "o\n",
1480
+ "u\n",
1481
+ "n\n",
1482
+ "d\n",
1483
+ " \n",
1484
+ "i\n",
1485
+ "n\n",
1486
+ " \n",
1487
+ "d\n",
1488
+ "a\n",
1489
+ "t\n",
1490
+ "a\n",
1491
+ "s\n",
1492
+ "e\n",
1493
+ "t\n",
1494
+ "----------------------------------------------------------------------------------------------\n"
1495
+ ]
1496
+ },
1497
+ {
1498
+ "name": "stdin",
1499
+ "output_type": "stream",
1500
+ "text": [
1501
+ "movie : Godfather\n"
1502
+ ]
1503
+ },
1504
+ {
1505
+ "name": "stdout",
1506
+ "output_type": "stream",
1507
+ "text": [
1508
+ "m\n",
1509
+ "o\n",
1510
+ "v\n",
1511
+ "i\n",
1512
+ "e\n",
1513
+ " \n",
1514
+ "n\n",
1515
+ "o\n",
1516
+ "t\n",
1517
+ " \n",
1518
+ "f\n",
1519
+ "o\n",
1520
+ "u\n",
1521
+ "n\n",
1522
+ "d\n",
1523
+ " \n",
1524
+ "i\n",
1525
+ "n\n",
1526
+ " \n",
1527
+ "d\n",
1528
+ "a\n",
1529
+ "t\n",
1530
+ "a\n",
1531
+ "s\n",
1532
+ "e\n",
1533
+ "t\n",
1534
+ "----------------------------------------------------------------------------------------------\n"
1535
+ ]
1536
+ },
1537
+ {
1538
+ "name": "stdin",
1539
+ "output_type": "stream",
1540
+ "text": [
1541
+ "movie : The Godfather\n"
1542
+ ]
1543
+ },
1544
+ {
1545
+ "name": "stdout",
1546
+ "output_type": "stream",
1547
+ "text": [
1548
+ "Desert Dancer\n",
1549
+ "Take the Lead\n",
1550
+ "Step Up 2: The Streets\n",
1551
+ "Center Stage\n",
1552
+ "Step Up\n",
1553
+ "Footloose\n",
1554
+ "ABCD (Any Body Can Dance)\n",
1555
+ "Step Up Revolution\n",
1556
+ "Tango\n",
1557
+ "Dancin' It's On\n",
1558
+ "Love Me Tender\n",
1559
+ "Sweet Charity\n",
1560
+ "Black Swan\n",
1561
+ "Sunday School Musical\n",
1562
+ "Peaceful Warrior\n",
1563
+ "Mao's Last Dancer\n",
1564
+ "Mr. Holland's Opus\n",
1565
+ "Yentl\n",
1566
+ "Honey\n",
1567
+ "Rize\n",
1568
+ "----------------------------------------------------------------------------------------------\n"
1569
+ ]
1570
+ },
1571
+ {
1572
+ "name": "stdin",
1573
+ "output_type": "stream",
1574
+ "text": [
1575
+ "movie : The Fault in Our Stars\n"
1576
+ ]
1577
+ },
1578
+ {
1579
+ "name": "stdout",
1580
+ "output_type": "stream",
1581
+ "text": [
1582
+ "Easy Money\n",
1583
+ "The Slaughter Rule\n",
1584
+ "Blood Ties\n",
1585
+ "Runner Runner\n",
1586
+ "The Gambler\n",
1587
+ "Hardball\n",
1588
+ "Gridiron Gang\n",
1589
+ "The Rainmaker\n",
1590
+ "Amidst the Devil's Wings\n",
1591
+ "Nine Queens\n",
1592
+ "Casino\n",
1593
+ "The Legend of Bagger Vance\n",
1594
+ "My Big Fat Greek Wedding\n",
1595
+ "Mi America\n",
1596
+ "Blue Like Jazz\n",
1597
+ "Ong Bak 2\n",
1598
+ "Auto Focus\n",
1599
+ "Stonewall\n",
1600
+ "Killer Joe\n",
1601
+ "Jesus' Son\n",
1602
+ "----------------------------------------------------------------------------------------------\n"
1603
+ ]
1604
+ },
1605
+ {
1606
+ "name": "stdin",
1607
+ "output_type": "stream",
1608
+ "text": [
1609
+ "movie : \n"
1610
+ ]
1611
+ },
1612
+ {
1613
+ "name": "stdout",
1614
+ "output_type": "stream",
1615
+ "text": [
1616
+ "function ended\n"
1617
+ ]
1618
+ }
1619
+ ],
1620
+ "source": [
1621
+ "while(True):\n",
1622
+ " movie = input('movie : ')\n",
1623
+ " if movie:\n",
1624
+ " for i in recommend(movie):\n",
1625
+ " print(i)\n",
1626
+ " print('----------------------------------------------------------------------------------------------')\n",
1627
+ " else:\n",
1628
+ " print('function ended')\n",
1629
+ " break"
1630
+ ]
1631
+ },
1632
+ {
1633
+ "cell_type": "code",
1634
+ "execution_count": 136,
1635
+ "id": "afc6fb23-bdc3-47df-9c22-18d303d97d81",
1636
+ "metadata": {},
1637
+ "outputs": [],
1638
+ "source": [
1639
+ "import pickle\n",
1640
+ "\n",
1641
+ "pickle.dump(movies.to_dict(), open('movies_dict.pkl', 'wb'))"
1642
+ ]
1643
+ },
1644
+ {
1645
+ "cell_type": "code",
1646
+ "execution_count": 144,
1647
+ "id": "d5d7a4a7-df6e-4ed6-a04b-5a4b8ba08550",
1648
+ "metadata": {},
1649
+ "outputs": [],
1650
+ "source": [
1651
+ "pickle.dump(movies_cos_sim, open('movies_cos_sim.pkl', 'wb'))\n",
1652
+ "x = pickle.load(open('movies_cos_sim.pkl', 'rb'))\n",
1653
+ "x"
1654
+ ]
1655
+ },
1656
+ {
1657
+ "cell_type": "code",
1658
+ "execution_count": 145,
1659
+ "id": "738cd08d-2232-4008-84c8-9e90f9320698",
1660
+ "metadata": {},
1661
+ "outputs": [
1662
+ {
1663
+ "data": {
1664
+ "text/plain": [
1665
+ "array([[1. , 0.08964215, 0.05976143, ..., 0.02519763, 0.02817181,\n",
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+ " 0. ],\n",
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+ " [0.05976143, 0.0625 , 1. , ..., 0.02635231, 0. ,\n",
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+ " 0. ],\n",
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+ " ...,\n",
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+ " [0.02519763, 0.02635231, 0.02635231, ..., 1. , 0.0745356 ,\n",
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+ " 0.04836508],\n",
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+ " [0.02817181, 0. , 0. , ..., 0.0745356 , 1. ,\n",
1675
+ " 0.05407381],\n",
1676
+ " [0. , 0. , 0. , ..., 0.04836508, 0.05407381,\n",
1677
+ " 1. ]])"
1678
+ ]
1679
+ },
1680
+ "execution_count": 145,
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+ "metadata": {},
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+ }
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+ ],
1685
+ "source": []
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "id": "1c150443-6419-4b0a-ab1a-92a3952c1bab",
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+ "source": []
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+ }
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+ ],
1696
+ "metadata": {
1697
+ "kernelspec": {
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+ "display_name": "Python 3 (ipykernel)",
1699
+ "language": "python",
1700
+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.12.4"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 5
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+ }