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API-development.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "00rbAxorEVOV"
},
"source": [
"# Intro to Python API Requests Development\n",
"<b>Objectives</b>\n",
"* Learn how to use the Python `Requests` module.\n",
"* Learn how to connect to API web data resources to extract data using HTTP methods.\n",
"* Learn how to read and manipulate API JSON response data.\n",
"* Learn how to deal with pagination in APIs (looping through pages to gather data).\n",
"* Best practices for writing API code that helps with troubleshooting and debugging.\n",
"\n",
"<b>TMDB Background Info</b> \n",
"The Movie Database (TMDB) is a popular, community-built database for movies and TV shows. All the content has been added and updated by users dating back to the year 2008. TMDB has a strong focus on collecting data from around the globe, and covers a wide range of data. They created a free API which allows users to extract a wide range of data from their database, which makes it a perfect environment to learn basic API development skills. \n",
"\n",
"<b>TMDB Rules and Limitations</b> \n",
"The API limits requests to 500 pages and 20 records per page\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "y4V1z_8vEVOf"
},
"source": [
"# 1.0 Import libraries, modules, and create variables for your API \n",
"* We'll be using the Python Requests module to manage our API connection along with other common libraries for API connection and data management."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "6XecbEZiEVOg"
},
"outputs": [],
"source": [
"import json\n",
"import requests\n",
"import pandas as pd\n",
"import re\n",
"from pprint import pprint\n",
"from pandas import json_normalize\n",
"from dateutil.parser import parse\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ghNRj-f2EVOh"
},
"outputs": [],
"source": [
"# Establishing variable for the API connection\n",
"api_key = ('460f7b576a1b5c789d7d574f7fcc4f5f')\n",
"language = ('en-US')\n",
"url = ('https://api.themoviedb.org/3/')\n",
"popular_movie_endpoint =(r'movie/popular')\n",
"params={'api_key':api_key,'language':language}\n",
"headers = {'accept':'application/json'}"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Hh_ZrR7wEVOj"
},
"source": [
"# 2.0 Basic API Connection Check \n",
"* It's good practice to test your API connection before writing your code. This gives you the opportunity to check the connection and to get an initial look at the JSON data.\n",
"* The objective is to get a response code of 200 and a JSON output.\n",
"* Using pretty print `pprint()` helps to improve the readability of JSON data.\n",
"\n",
"<b>Note:</b> The JSON output has 4 main keys, `page`, `results`, `total_pages`, and `total_results`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "x0NWTRuNEVOj",
"outputId": "9418f456-7f0b-44c6-e09a-cfab4472bfec",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Response Code: 200\n",
"URL Link: https://api.themoviedb.org/3/movie/popular?api_key=460f7b576a1b5c789d7d574f7fcc4f5f&language=en-US \n",
"\n",
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]
}
],
"source": [
"# Quick API connection check\n",
"response = requests.get(\"https://api.themoviedb.org/3/movie/popular\", headers=headers, params={'api_key':api_key,'language':language})\n",
"\n",
"# Printing the response code and url\n",
"print('Response Code: ' + str(response.status_code))\n",
"print('URL Link: ' + response.url, '\\n')\n",
"\n",
"# Formtting the JSON response to print using the pretty print module, which helps with readability of JSON files\n",
"pprint(response.json())"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FrVJ1WpsEVOl"
},
"source": [
"# 3.0 Build a function to pull data from the TMDB API \n",
"* The main objective is to get data from the popular movies endpoint. \n",
"* Use try/exeption blocks to capture error handling. \n",
"* Assign the function to a variable called `popular_movies_data`. This is good practice when reusing or calling functions later in the code.\n",
"\n",
"<b>Note:</b> Try using `pprint(json_file)` to see the difference between the two outputs.\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0Y5u_DalEVOl"
},
"outputs": [],
"source": [
"def get_popular_movie_data():\n",
" try:\n",
" response = requests.get(url + popular_movie_endpoint, headers=headers, params=params, verify=True)\n",
" print('Response Code: ' + str(response.status_code))\n",
" print('URL Link: ' + response.url, '\\n')\n",
" json_file = response.json()\n",
" except Exception as e:\n",
" print(f'Failed to connect with URL: {url}')\n",
" print(e)\n",
" raise SystemExit\n",
" return json_file\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "9Mu6u8X0EVOm",
"outputId": "5ba71a48-c13d-4b83-8d6e-2c3cc3801f95",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Response Code: 200\n",
"URL Link: https://api.themoviedb.org/3/movie/popular?api_key=460f7b576a1b5c789d7d574f7fcc4f5f&language=en-US \n",
"\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'page': 1,\n",
" 'results': [{'adult': False,\n",
" 'backdrop_path': '/xg27NrXi7VXCGUr7MG75UqLl6Vg.jpg',\n",
" 'genre_ids': [16, 10751, 12, 35],\n",
" 'id': 1022789,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Inside Out 2',\n",
" 'overview': \"Teenager Riley's mind headquarters is undergoing a sudden demolition to make room for something entirely unexpected: new Emotions! Joy, Sadness, Anger, Fear and Disgust, who’ve long been running a successful operation by all accounts, aren’t sure how to feel when Anxiety shows up. And it looks like she’s not alone.\",\n",
" 'popularity': 5389.964,\n",
" 'poster_path': '/vpnVM9B6NMmQpWeZvzLvDESb2QY.jpg',\n",
" 'release_date': '2024-06-11',\n",
" 'title': 'Inside Out 2',\n",
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" 'vote_count': 1868},\n",
" {'adult': False,\n",
" 'backdrop_path': '/fDmci71SMkfZM8RnCuXJVDPaSdE.jpg',\n",
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" 'id': 519182,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Despicable Me 4',\n",
" 'overview': 'Gru and Lucy and their girls — Margo, Edith and Agnes — welcome a new member to the Gru family, Gru Jr., who is intent on tormenting his dad. Meanwhile, Gru faces a new nemesis in Maxime Le Mal and his femme fatale girlfriend Valentina, forcing the family to go on the run.',\n",
" 'popularity': 4182.19,\n",
" 'poster_path': '/3w84hCFJATpiCO5g8hpdWVPBbmq.jpg',\n",
" 'release_date': '2024-06-20',\n",
" 'title': 'Despicable Me 4',\n",
" 'video': False,\n",
" 'vote_average': 7.5,\n",
" 'vote_count': 301},\n",
" {'adult': False,\n",
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" 'id': 748783,\n",
" 'original_language': 'en',\n",
" 'original_title': 'The Garfield Movie',\n",
" 'overview': 'Garfield, the world-famous, Monday-hating, lasagna-loving indoor cat, is about to have a wild outdoor adventure! After an unexpected reunion with his long-lost father – scruffy street cat Vic – Garfield and his canine friend Odie are forced from their perfectly pampered life into joining Vic in a hilarious, high-stakes heist.',\n",
" 'popularity': 2209.679,\n",
" 'poster_path': '/p6AbOJvMQhBmffd0PIv0u8ghWeY.jpg',\n",
" 'release_date': '2024-04-30',\n",
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" 'video': False,\n",
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" 'vote_count': 451},\n",
" {'adult': False,\n",
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" 'genre_ids': [28, 12, 878],\n",
" 'id': 786892,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Furiosa: A Mad Max Saga',\n",
" 'overview': 'As the world fell, young Furiosa is snatched from the Green Place of Many Mothers and falls into the hands of a great Biker Horde led by the Warlord Dementus. Sweeping through the Wasteland they come across the Citadel presided over by The Immortan Joe. While the two Tyrants war for dominance, Furiosa must survive many trials as she puts together the means to find her way home.',\n",
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" 'release_date': '2024-05-22',\n",
" 'title': 'Furiosa: A Mad Max Saga',\n",
" 'video': False,\n",
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" {'adult': False,\n",
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" 'genre_ids': [878, 12, 28],\n",
" 'id': 653346,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Kingdom of the Planet of the Apes',\n",
" 'overview': \"Several generations following Caesar's reign, apes – now the dominant species – live harmoniously while humans have been reduced to living in the shadows. As a new tyrannical ape leader builds his empire, one young ape undertakes a harrowing journey that will cause him to question all he's known about the past and to make choices that will define a future for apes and humans alike.\",\n",
" 'popularity': 1685.471,\n",
" 'poster_path': '/gKkl37BQuKTanygYQG1pyYgLVgf.jpg',\n",
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" 'vote_count': 1893},\n",
" {'adult': False,\n",
" 'backdrop_path': '/dn3gbDpXPSwC6saMJOHkCiFA9jn.jpg',\n",
" 'genre_ids': [14, 12, 10751, 35],\n",
" 'id': 974262,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Descendants: The Rise of Red',\n",
" 'overview': \"After the Queen of Hearts incites a coup on Auradon, her rebellious daughter Red and Cinderella's perfectionist daughter Chloe join forces and travel back in time to try to undo the traumatic event that set Red's mother down her villainous path.\",\n",
" 'popularity': 1277.167,\n",
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" 'video': False,\n",
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" 'vote_count': 132},\n",
" {'adult': False,\n",
" 'backdrop_path': '/gRApXuxWmO2forYTuTmcz5RaNUV.jpg',\n",
" 'genre_ids': [28, 80, 53, 35],\n",
" 'id': 573435,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Bad Boys: Ride or Die',\n",
" 'overview': 'After their late former Captain is framed, Lowrey and Burnett try to clear his name, only to end up on the run themselves.',\n",
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" 'poster_path': '/nP6RliHjxsz4irTKsxe8FRhKZYl.jpg',\n",
" 'release_date': '2024-06-05',\n",
" 'title': 'Bad Boys: Ride or Die',\n",
" 'video': False,\n",
" 'vote_average': 7.11,\n",
" 'vote_count': 568},\n",
" {'adult': False,\n",
" 'backdrop_path': '/rrwt0u1rW685u9bJ9ougg5HJEHC.jpg',\n",
" 'genre_ids': [28, 35, 80],\n",
" 'id': 280180,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Beverly Hills Cop: Axel F',\n",
" 'overview': 'Forty years after his unforgettable first case in Beverly Hills, Detroit cop Axel Foley returns to do what he does best: solve crimes and cause chaos.',\n",
" 'popularity': 1237.903,\n",
" 'poster_path': '/zszRKfzjM5jltiq8rk6rasKVpUv.jpg',\n",
" 'release_date': '2024-06-20',\n",
" 'title': 'Beverly Hills Cop: Axel F',\n",
" 'video': False,\n",
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" 'vote_count': 591},\n",
" {'adult': False,\n",
" 'backdrop_path': '/lA6KdSkCTxwzvqzPqxch997RabQ.jpg',\n",
" 'genre_ids': [28, 53],\n",
" 'id': 560016,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Monkey Man',\n",
" 'overview': 'Kid is an anonymous young man who ekes out a meager living in an underground fight club where, night after night, wearing a gorilla mask, he is beaten bloody by more popular fighters for cash. After years of suppressed rage, Kid discovers a way to infiltrate the enclave of the city’s sinister elite. As his childhood trauma boils over, his mysteriously scarred hands unleash an explosive campaign of retribution to settle the score with the men who took everything from him.',\n",
" 'popularity': 1148.565,\n",
" 'poster_path': '/4lhR4L2vzzjl68P1zJyCH755Oz4.jpg',\n",
" 'release_date': '2024-04-03',\n",
" 'title': 'Monkey Man',\n",
" 'video': False,\n",
" 'vote_average': 7.1,\n",
" 'vote_count': 600},\n",
" {'adult': False,\n",
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" 'genre_ids': [27, 53],\n",
" 'id': 646683,\n",
" 'original_language': 'en',\n",
" 'original_title': 'The Exorcism',\n",
" 'overview': \"A troubled actor begins to unravel while shooting a supernatural horror film, leading his estranged daughter to wonder if he's slipping back into his past addictions or if there's something more sinister at play.\",\n",
" 'popularity': 1119.067,\n",
" 'poster_path': '/ar2h87jlTfMlrDZefR3VFz1SfgH.jpg',\n",
" 'release_date': '2024-05-30',\n",
" 'title': 'The Exorcism',\n",
" 'video': False,\n",
" 'vote_average': 4.3,\n",
" 'vote_count': 67},\n",
" {'adult': False,\n",
" 'backdrop_path': '/lLh39Th5plbrQgbQ4zyIULsd0Pp.jpg',\n",
" 'genre_ids': [878, 28, 12],\n",
" 'id': 823464,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Godzilla x Kong: The New Empire',\n",
" 'overview': 'Following their explosive showdown, Godzilla and Kong must reunite against a colossal undiscovered threat hidden within our world, challenging their very existence – and our own.',\n",
" 'popularity': 998.116,\n",
" 'poster_path': '/z1p34vh7dEOnLDmyCrlUVLuoDzd.jpg',\n",
" 'release_date': '2024-03-27',\n",
" 'title': 'Godzilla x Kong: The New Empire',\n",
" 'video': False,\n",
" 'vote_average': 7.202,\n",
" 'vote_count': 3196},\n",
" {'adult': False,\n",
" 'backdrop_path': '/oSJV6nAfHzyE9v6oEAXmDjbko00.jpg',\n",
" 'genre_ids': [14, 12],\n",
" 'id': 943344,\n",
" 'original_language': 'zh',\n",
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" 'vote_count': 5},\n",
" {'adult': False,\n",
" 'backdrop_path': '/dbtGinhWWKgQLQ0hjZHMFWxBJcJ.jpg',\n",
" 'genre_ids': [28, 878, 27, 53],\n",
" 'id': 1159518,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Black Noise',\n",
" 'overview': 'Members of an elite security team deployed to rescue a VIP on an exclusive island.The rescue mission becomes a desperate attempt to survive, escape the island and elude the sinister presence that seeks to harm them.',\n",
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" 'poster_path': '/snKpXexv5dtWqEKEmXrJtp8QGQC.jpg',\n",
" 'release_date': '2023-11-03',\n",
" 'title': 'Black Noise',\n",
" 'video': False,\n",
" 'vote_average': 5.313,\n",
" 'vote_count': 16},\n",
" {'adult': False,\n",
" 'backdrop_path': '/uNTciMXpCQDg7gvgMsPCdnxo6Re.jpg',\n",
" 'genre_ids': [28, 53],\n",
" 'id': 1114738,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Boneyard',\n",
" 'overview': 'After Police Chief Carter discovers the remains of eleven women, FBI Special Agent Petrovick is recruited to profile the serial killer responsible for the infamous \"boneyard\" killings. As the police force, narcotics agency, and FBI lock horns, a tangled web of intrigue turns everyone into a suspect.',\n",
" 'popularity': 768.042,\n",
" 'poster_path': '/xkNK36hQv8SWiwiQoE7naRfP0zL.jpg',\n",
" 'release_date': '2024-07-05',\n",
" 'title': 'Boneyard',\n",
" 'video': False,\n",
" 'vote_average': 5.788,\n",
" 'vote_count': 40},\n",
" {'adult': False,\n",
" 'backdrop_path': '/adAJDB2Au3x5ve2YyWaEYy4EUw.jpg',\n",
" 'genre_ids': [18, 10749, 35],\n",
" 'id': 1191610,\n",
" 'original_language': 'es',\n",
" 'original_title': 'Goyo',\n",
" 'overview': 'A young autistic museum guide lives by a strict routine — until he falls in love with his coworker and must confront a whirlwind of new, intense emotions.',\n",
" 'popularity': 735.939,\n",
" 'poster_path': '/fCjC1RRbEJUpDjM55RNUMXQen0b.jpg',\n",
" 'release_date': '2024-06-27',\n",
" 'title': 'Goyo',\n",
" 'video': False,\n",
" 'vote_average': 6.788,\n",
" 'vote_count': 26},\n",
" {'adult': False,\n",
" 'backdrop_path': '/dvBCdCohwWbsP5qAaglOXagDMtk.jpg',\n",
" 'genre_ids': [878, 28, 35],\n",
" 'id': 533535,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Deadpool & Wolverine',\n",
" 'overview': 'A listless Wade Wilson toils away in civilian life with his days as the morally flexible mercenary, Deadpool, behind him. But when his homeworld faces an existential threat, Wade must reluctantly suit-up again with an even more reluctant Wolverine.',\n",
" 'popularity': 712.349,\n",
" 'poster_path': '/jbwYaoYWZwxtPP76AZnfYKQjCEB.jpg',\n",
" 'release_date': '2024-07-24',\n",
" 'title': 'Deadpool & Wolverine',\n",
" 'video': False,\n",
" 'vote_average': 0.0,\n",
" 'vote_count': 0},\n",
" {'adult': False,\n",
" 'backdrop_path': '/a4IWRYNMNMszIkRbEIiNsRg6cvt.jpg',\n",
" 'genre_ids': [10752, 28, 18],\n",
" 'id': 929590,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Civil War',\n",
" 'overview': 'In the near future, a group of war journalists attempt to survive while reporting the truth as the United States stands on the brink of civil war.',\n",
" 'popularity': 708.024,\n",
" 'poster_path': '/sh7Rg8Er3tFcN9BpKIPOMvALgZd.jpg',\n",
" 'release_date': '2024-04-10',\n",
" 'title': 'Civil War',\n",
" 'video': False,\n",
" 'vote_average': 6.988,\n",
" 'vote_count': 1907},\n",
" {'adult': False,\n",
" 'backdrop_path': '/iTWrsOVsUqcwYSxrpINNs3hG2nC.jpg',\n",
" 'genre_ids': [53, 27, 28, 9648],\n",
" 'id': 1001311,\n",
" 'original_language': 'fr',\n",
" 'original_title': 'Sous la Seine',\n",
" 'overview': 'In order to save Paris from an international bloodbath, a grieving scientist is forced to face her tragic past when a giant shark appears in the Seine.',\n",
" 'popularity': 706.026,\n",
" 'poster_path': '/qZPLK5ktRKa3CL4sKRZtj8UlPYc.jpg',\n",
" 'release_date': '2024-06-04',\n",
" 'title': 'Under Paris',\n",
" 'video': False,\n",
" 'vote_average': 6.093,\n",
" 'vote_count': 910},\n",
" {'adult': False,\n",
" 'backdrop_path': '/j29ekbcLpBvxnGk6LjdTc2EI5SA.jpg',\n",
" 'genre_ids': [16, 10751, 12, 18, 35],\n",
" 'id': 150540,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Inside Out',\n",
" 'overview': 'When 11-year-old Riley moves to a new city, her Emotions team up to help her through the transition. Joy, Fear, Anger, Disgust and Sadness work together, but when Joy and Sadness get lost, they must journey through unfamiliar places to get back home.',\n",
" 'popularity': 680.264,\n",
" 'poster_path': '/2H1TmgdfNtsKlU9jKdeNyYL5y8T.jpg',\n",
" 'release_date': '2015-06-17',\n",
" 'title': 'Inside Out',\n",
" 'video': False,\n",
" 'vote_average': 7.916,\n",
" 'vote_count': 21227},\n",
" {'adult': False,\n",
" 'backdrop_path': '/aATi2PtaOQCVAquCym6OU0Z4FjY.jpg',\n",
" 'genre_ids': [28, 80, 53],\n",
" 'id': 704673,\n",
" 'original_language': 'en',\n",
" 'original_title': 'Trigger Warning',\n",
" 'overview': \"A Special Forces commando uncovers a dangerous conspiracy when she returns to her hometown looking for answers into her beloved father's death.\",\n",
" 'popularity': 642.399,\n",
" 'poster_path': '/lJN24nn28s5afC1UnLPYRgYOp1K.jpg',\n",
" 'release_date': '2024-06-20',\n",
" 'title': 'Trigger Warning',\n",
" 'video': False,\n",
" 'vote_average': 5.9,\n",
" 'vote_count': 322}],\n",
" 'total_pages': 45146,\n",
" 'total_results': 902905}"
]
},
"metadata": {},
"execution_count": 6
}
],
"source": [
"popular_movies_data = get_popular_movie_data()\n",
"popular_movies_data"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "IWZC9BkJEVOm"
},
"source": [
"# 4.0 Converting JSON Data to a Pandas DataFrame \n",
"* Create a function to convert the JSON data from `popular_movies_data` to a Pandas DataFrame. \n",
"* Assign the dataframe to a variable called `popular_movies`. \n",
"\n",
"<b>Note:</b> The API call only provided the first page of data which contains only 20 records. You have to loop through all pages to get the full list. Our API code did not include a pagination or looping feature so it only gave us the 20 records on the first page."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "jl4lxAj-EVOn",
"outputId": "bf0ffef4-e76d-4258-8306-396e950c66e8",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Converting JSON data to Pandas Dataframe\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
" adult backdrop_path genre_ids id \\\n",
"0 False /xg27NrXi7VXCGUr7MG75UqLl6Vg.jpg [16, 10751, 12, 35] 1022789 \n",
"1 False /fDmci71SMkfZM8RnCuXJVDPaSdE.jpg [16, 10751, 35, 28] 519182 \n",
"2 False /Akv9GlCCMrzcDkVz4ad8MdLl9DK.jpg [16, 35, 10751, 12] 748783 \n",
"3 False /wNAhuOZ3Zf84jCIlrcI6JhgmY5q.jpg [28, 12, 878] 786892 \n",
"4 False /fqv8v6AycXKsivp1T5yKtLbGXce.jpg [878, 12, 28] 653346 \n",
"5 False /dn3gbDpXPSwC6saMJOHkCiFA9jn.jpg [14, 12, 10751, 35] 974262 \n",
"6 False /gRApXuxWmO2forYTuTmcz5RaNUV.jpg [28, 80, 53, 35] 573435 \n",
"7 False /rrwt0u1rW685u9bJ9ougg5HJEHC.jpg [28, 35, 80] 280180 \n",
"8 False /lA6KdSkCTxwzvqzPqxch997RabQ.jpg [28, 53] 560016 \n",
"9 False /8fNBsXpgMvqk75SPsZzTmIqSRxY.jpg [27, 53] 646683 \n",
"10 False /lLh39Th5plbrQgbQ4zyIULsd0Pp.jpg [878, 28, 12] 823464 \n",
"11 False /oSJV6nAfHzyE9v6oEAXmDjbko00.jpg [14, 12] 943344 \n",
"12 False /dbtGinhWWKgQLQ0hjZHMFWxBJcJ.jpg [28, 878, 27, 53] 1159518 \n",
"13 False /uNTciMXpCQDg7gvgMsPCdnxo6Re.jpg [28, 53] 1114738 \n",
"14 False /adAJDB2Au3x5ve2YyWaEYy4EUw.jpg [18, 10749, 35] 1191610 \n",
"15 False /dvBCdCohwWbsP5qAaglOXagDMtk.jpg [878, 28, 35] 533535 \n",
"16 False /a4IWRYNMNMszIkRbEIiNsRg6cvt.jpg [10752, 28, 18] 929590 \n",
"17 False /iTWrsOVsUqcwYSxrpINNs3hG2nC.jpg [53, 27, 28, 9648] 1001311 \n",
"18 False /j29ekbcLpBvxnGk6LjdTc2EI5SA.jpg [16, 10751, 12, 18, 35] 150540 \n",
"19 False /aATi2PtaOQCVAquCym6OU0Z4FjY.jpg [28, 80, 53] 704673 \n",
"\n",
" original_language original_title \\\n",
"0 en Inside Out 2 \n",
"1 en Despicable Me 4 \n",
"2 en The Garfield Movie \n",
"3 en Furiosa: A Mad Max Saga \n",
"4 en Kingdom of the Planet of the Apes \n",
"5 en Descendants: The Rise of Red \n",
"6 en Bad Boys: Ride or Die \n",
"7 en Beverly Hills Cop: Axel F \n",
"8 en Monkey Man \n",
"9 en The Exorcism \n",
"10 en Godzilla x Kong: The New Empire \n",
"11 zh 地底怪物 \n",
"12 en Black Noise \n",
"13 en Boneyard \n",
"14 es Goyo \n",
"15 en Deadpool & Wolverine \n",
"16 en Civil War \n",
"17 fr Sous la Seine \n",
"18 en Inside Out \n",
"19 en Trigger Warning \n",
"\n",
" overview popularity \\\n",
"0 Teenager Riley's mind headquarters is undergoi... 5389.964 \n",
"1 Gru and Lucy and their girls — Margo, Edith an... 4182.190 \n",
"2 Garfield, the world-famous, Monday-hating, las... 2209.679 \n",
"3 As the world fell, young Furiosa is snatched f... 1802.966 \n",
"4 Several generations following Caesar's reign, ... 1685.471 \n",
"5 After the Queen of Hearts incites a coup on Au... 1277.167 \n",
"6 After their late former Captain is framed, Low... 1263.839 \n",
"7 Forty years after his unforgettable first case... 1237.903 \n",
"8 Kid is an anonymous young man who ekes out a m... 1148.565 \n",
"9 A troubled actor begins to unravel while shoot... 1119.067 \n",
"10 Following their explosive showdown, Godzilla a... 998.116 \n",
"11 978.450 \n",
"12 Members of an elite security team deployed to ... 772.167 \n",
"13 After Police Chief Carter discovers the remain... 768.042 \n",
"14 A young autistic museum guide lives by a stric... 735.939 \n",
"15 A listless Wade Wilson toils away in civilian ... 712.349 \n",
"16 In the near future, a group of war journalists... 708.024 \n",
"17 In order to save Paris from an international b... 706.026 \n",
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"\n",
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" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
"\n",
"\n",
"<div id=\"df-279d0d70-b32e-4ad1-a152-22c0edbebdfe\">\n",
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-279d0d70-b32e-4ad1-a152-22c0edbebdfe')\"\n",
" title=\"Suggest charts\"\n",
" style=\"display:none;\">\n",
"\n",
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" width=\"24px\">\n",
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" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
" --disabled-bg-color: #3B4455;\n",
" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-279d0d70-b32e-4ad1-a152-22c0edbebdfe button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
"\n",
" <div id=\"id_ee0854c9-e900-441d-b3d9-b3607052896e\">\n",
" <style>\n",
" .colab-df-generate {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-generate:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
" <button class=\"colab-df-generate\" onclick=\"generateWithVariable('popular_movies')\"\n",
" title=\"Generate code using this dataframe.\"\n",
" style=\"display:none;\">\n",
"\n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
" </svg>\n",
" </button>\n",
" <script>\n",
" (() => {\n",
" const buttonEl =\n",
" document.querySelector('#id_ee0854c9-e900-441d-b3d9-b3607052896e button.colab-df-generate');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" buttonEl.onclick = () => {\n",
" google.colab.notebook.generateWithVariable('popular_movies');\n",
" }\n",
" })();\n",
" </script>\n",
" </div>\n",
"\n",
" </div>\n",
" </div>\n"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "popular_movies",
"summary": "{\n \"name\": \"popular_movies\",\n \"rows\": 20,\n \"fields\": [\n {\n \"column\": \"adult\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"backdrop_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 20,\n \"samples\": [\n \"/xg27NrXi7VXCGUr7MG75UqLl6Vg.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"genre_ids\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 283263,\n \"min\": 150540,\n \"max\": 1191610,\n \"num_unique_values\": 20,\n \"samples\": [\n 1022789\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_language\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 4,\n \"samples\": [\n \"zh\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 20,\n \"samples\": [\n \"Inside Out 2\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"overview\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 20,\n \"samples\": [\n \"Teenager Riley's mind headquarters is undergoing a sudden demolition to make room for something entirely unexpected: new Emotions! Joy, Sadness, Anger, Fear and Disgust, who\\u2019ve long been running a successful operation by all accounts, aren\\u2019t sure how to feel when Anxiety shows up. And it looks like she\\u2019s not alone.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"popularity\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1231.3670315166958,\n \"min\": 642.399,\n \"max\": 5389.964,\n \"num_unique_values\": 20,\n \"samples\": [\n 5389.964\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"poster_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 20,\n \"samples\": [\n \"/vpnVM9B6NMmQpWeZvzLvDESb2QY.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"release_date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 18,\n \"samples\": [\n \"2024-06-11\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 20,\n \"samples\": [\n \"Inside Out 2\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"video\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_average\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.8469903050211458,\n \"min\": 0.0,\n \"max\": 7.916,\n \"num_unique_values\": 20,\n \"samples\": [\n 7.699\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_count\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 4660,\n \"min\": 0,\n \"max\": 21227,\n \"num_unique_values\": 20,\n \"samples\": [\n 1868\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 7
}
],
"source": [
"def convertJsonToDataFrame():\n",
" print('Converting JSON data to Pandas Dataframe')\n",
" popular_movies_df = pd.json_normalize(popular_movies_data, 'results')\n",
" return popular_movies_df\n",
"\n",
"popular_movies = convertJsonToDataFrame()\n",
"popular_movies"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "uDy0kCNWEVOo"
},
"source": [
"# 5.0 Pagination - Looping APIs with a Specified Range of Pages (for loop) \n",
"* Create a function that pulls data from the popular movies endpoint with filters for English movies only from 2024. \n",
"* Include a looping feature to loop through each page within the specified range and automatically stops when the last record is retrieved. \n",
"* Include a feature that calculates the total number pages that the API call retrieved data from and the total number of records that were retrieved.\n",
"* Include try/exception blocks to handle errors that could arise.\n",
"\n",
"<b>NOTE:</b> This function uses a range of pages for the loop. This is useful when you want to pull data from a specified range of pages."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "eGkvUSjOEVOo",
"outputId": "c8ee731b-5227-4da4-9be6-43c6caa85722",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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]
}
],
"source": [
"# Establishing global variables for the API\n",
"api_key = '460f7b576a1b5c789d7d574f7fcc4f5f'\n",
"language = 'en-US'\n",
"url = 'https://api.themoviedb.org/3/'\n",
"popular_movie_endpoint = 'movie/popular'\n",
"params = {'api_key': api_key, 'language': language, 'year': 2024}\n",
"headers = {'accept': 'application/json'}\n",
"\n",
"def get_2024_popular_movie_data():\n",
" # Initialize an empty list to store the data from all of the pages in the API\n",
" all_pages_data = []\n",
"\n",
" total_pages = 0\n",
"\n",
" # Iterate through pages 1 to 600 to fetch data\n",
" for page in range(1, 601):\n",
" try:\n",
" # Update the 'page' parameter in the API request to keep count of which page you are on within the loop\n",
" params['page'] = page\n",
"\n",
" # Make the API request to fetch the movie data\n",
" response = requests.get(url + popular_movie_endpoint, headers=headers, params=params)\n",
" print(f'Response Code for page {page}: {response.status_code}')\n",
"\n",
"\n",
" # Parse the JSON response and assign it to a variable\n",
" json_file = response.json()\n",
"\n",
" # Filter the results to include only movies released in 2024 and in English\n",
" filtered_results = [movie for movie in json_file.get('results', []) if movie.get('release_date', '').startswith('2024') and movie.get('original_language') == 'en']\n",
"\n",
" # Append the filtered results to the all_pages_data list and print the number of rows retrieved for the page\n",
" all_pages_data.extend(filtered_results)\n",
" print('Rows of data retrieved: '+str(len(all_pages_data)), '\\n')\n",
"\n",
" # If there are no more results in the JSON response, the script will print the statement and terminate\n",
" if json_file.get('results',[]) == []:\n",
" print('There are no more records to retrieve.', '\\n')\n",
" break\n",
"\n",
" total_pages += 1\n",
"\n",
" # Handle exceptions related to the API request call\n",
" except requests.exceptions.RequestException as e:\n",
" print(f'Error connecting to the API: {e}')\n",
" raise SystemExit\n",
"\n",
" # Handle exceptions related to processing the API response\n",
" except KeyError as e:\n",
" print(f'Error processing the API response: {e}')\n",
" raise SystemExit\n",
"\n",
" # Print the total number of pages processed\n",
" print(f'Total pages processed: {total_pages}', '\\n')\n",
"\n",
" print('Total rows of data retrieved: ' + str(len(all_pages_data)), '\\n')\n",
"\n",
" # Return the list of all retrieved movie data\n",
" return all_pages_data\n",
"\n",
"# Assign the 'get_2024_popular_movie_data' function to a variable\n",
"popular_movies_data_2024 = get_2024_popular_movie_data()\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "HmxM-YZZEVOp"
},
"source": [
"# 5.1 Convert JSON Data To a Pandas Dataframe \n",
"* Create a function to convert the `filtered_popular_movies_data` JSON file to a Pandas dataframe.\n",
"* Add a Doc string to the function to document the details of the function. \n",
"\n",
"<b>Note:</b> Take note of the difference between this function and the last JSON --> Pandas DF conversion function that we created in 4.0. This function uses an argumet variable called `json_data` while the previous one did not.\n",
"\n",
"<b>Note:</b> Doc strings are used to explain how a function works. It's good practice to include doc strings for each function."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "wzXwmx7wEVOq",
"outputId": "265c1f43-97e2-4714-b22e-65b978086f09",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Converting JSON data to Pandas Dataframe \n",
"\n"
]
},
{
"output_type": "execute_result",
"data": {
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"0 False /xg27NrXi7VXCGUr7MG75UqLl6Vg.jpg [16, 10751, 12, 35] 1022789 \n",
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" original_language original_title \\\n",
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"\n",
" overview popularity \\\n",
"0 Teenager Riley's mind headquarters is undergoi... 5389.964 \n",
"1 Gru and Lucy and their girls — Margo, Edith an... 4182.190 \n",
"2 Garfield, the world-famous, Monday-hating, las... 2209.679 \n",
"3 As the world fell, young Furiosa is snatched f... 1802.966 \n",
"4 Several generations following Caesar's reign, ... 1685.471 \n",
".. ... ... \n",
"295 The life of a young glassblower in training an... 21.098 \n",
"296 Madonna celebrates her four-decade career in a... 14.855 \n",
"297 Genius artist Cesar Catilina seeks to leap the... 28.421 \n",
"298 20.712 \n",
"299 From Rickrolling to viral conspiracy theories,... 20.709 \n",
"\n",
" poster_path release_date \\\n",
"0 /vpnVM9B6NMmQpWeZvzLvDESb2QY.jpg 2024-06-11 \n",
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"4 /gKkl37BQuKTanygYQG1pyYgLVgf.jpg 2024-05-08 \n",
".. ... ... \n",
"295 /pznTVwDl2qEVwHT1TEVd7AnVC7H.jpg 2024-07-26 \n",
"296 /7PvmeXZpneJJOHU5A95ShAywaoB.jpg 2024-05-04 \n",
"297 /m0BJiPZs5iWzbJWe2uRNotZpKOk.jpg 2024-09-25 \n",
"298 /x3NJ5w7n7msDZFKoiDwoLlbKh0s.jpg 2024-07-19 \n",
"299 /AlJKsIzkSU629hEhbRzRb1cSxA1.jpg 2024-03-10 \n",
"\n",
" title video vote_average vote_count \n",
"0 Inside Out 2 False 7.699 1868 \n",
"1 Despicable Me 4 False 7.500 301 \n",
"2 The Garfield Movie False 7.274 451 \n",
"3 Furiosa: A Mad Max Saga False 7.600 2170 \n",
"4 Kingdom of the Planet of the Apes False 7.131 1893 \n",
".. ... ... ... ... \n",
"295 The Glassworker False 0.000 0 \n",
"296 Madonna: The Celebration Tour in Rio False 8.900 9 \n",
"297 Megalopolis False 0.000 0 \n",
"298 Swahi False 0.000 0 \n",
"299 The Antisocial Network: Memes to Mayhem False 6.450 20 \n",
"\n",
"[300 rows x 14 columns]"
],
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" <td>/gKkl37BQuKTanygYQG1pyYgLVgf.jpg</td>\n",
" <td>2024-05-08</td>\n",
" <td>Kingdom of the Planet of the Apes</td>\n",
" <td>False</td>\n",
" <td>7.131</td>\n",
" <td>1893</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",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>False</td>\n",
" <td>/aqvGE8cMM5zta73xlNEtWlLqpWx.jpg</td>\n",
" <td>[16]</td>\n",
" <td>629078</td>\n",
" <td>en</td>\n",
" <td>The Glassworker</td>\n",
" <td>The life of a young glassblower in training an...</td>\n",
" <td>21.098</td>\n",
" <td>/pznTVwDl2qEVwHT1TEVd7AnVC7H.jpg</td>\n",
" <td>2024-07-26</td>\n",
" <td>The Glassworker</td>\n",
" <td>False</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>296</th>\n",
" <td>False</td>\n",
" <td>/jWrJjlBeFuOLZHETn85lZ0vHPUK.jpg</td>\n",
" <td>[10402, 99]</td>\n",
" <td>1280042</td>\n",
" <td>en</td>\n",
" <td>Madonna: The Celebration Tour in Rio</td>\n",
" <td>Madonna celebrates her four-decade career in a...</td>\n",
" <td>14.855</td>\n",
" <td>/7PvmeXZpneJJOHU5A95ShAywaoB.jpg</td>\n",
" <td>2024-05-04</td>\n",
" <td>Madonna: The Celebration Tour in Rio</td>\n",
" <td>False</td>\n",
" <td>8.900</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>297</th>\n",
" <td>False</td>\n",
" <td>/v7bGLVacGLXop3hp5wTDY6HsB1i.jpg</td>\n",
" <td>[18, 878]</td>\n",
" <td>592831</td>\n",
" <td>en</td>\n",
" <td>Megalopolis</td>\n",
" <td>Genius artist Cesar Catilina seeks to leap the...</td>\n",
" <td>28.421</td>\n",
" <td>/m0BJiPZs5iWzbJWe2uRNotZpKOk.jpg</td>\n",
" <td>2024-09-25</td>\n",
" <td>Megalopolis</td>\n",
" <td>False</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>298</th>\n",
" <td>False</td>\n",
" <td>None</td>\n",
" <td>[]</td>\n",
" <td>1301417</td>\n",
" <td>en</td>\n",
" <td>Swahi</td>\n",
" <td></td>\n",
" <td>20.712</td>\n",
" <td>/x3NJ5w7n7msDZFKoiDwoLlbKh0s.jpg</td>\n",
" <td>2024-07-19</td>\n",
" <td>Swahi</td>\n",
" <td>False</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299</th>\n",
" <td>False</td>\n",
" <td>/ngrJjNw3hJRXwMfGLIhchEaBobW.jpg</td>\n",
" <td>[99]</td>\n",
" <td>1242384</td>\n",
" <td>en</td>\n",
" <td>The Antisocial Network: Memes to Mayhem</td>\n",
" <td>From Rickrolling to viral conspiracy theories,...</td>\n",
" <td>20.709</td>\n",
" <td>/AlJKsIzkSU629hEhbRzRb1cSxA1.jpg</td>\n",
" <td>2024-03-10</td>\n",
" <td>The Antisocial Network: Memes to Mayhem</td>\n",
" <td>False</td>\n",
" <td>6.450</td>\n",
" <td>20</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>300 rows × 14 columns</p>\n",
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" <script>\n",
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" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
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"\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "popular_movies_2024_df",
"summary": "{\n \"name\": \"popular_movies_2024_df\",\n \"rows\": 300,\n \"fields\": [\n {\n \"column\": \"adult\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"backdrop_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 227,\n \"samples\": [\n \"/8fNBsXpgMvqk75SPsZzTmIqSRxY.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"genre_ids\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 214023,\n \"min\": 280180,\n \"max\": 1310259,\n \"num_unique_values\": 235,\n \"samples\": [\n 821499\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_language\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"en\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 235,\n \"samples\": [\n \"The Inheritance\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"overview\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 236,\n \"samples\": [\n \"Billionaire Charles Abernathy, on the eve of his 75th birthday, invites his four estranged children back home out of fear that tonight someone \\u2013 or something \\u2013 is coming to kill him. To ensure his family will help protect him from whatever\\u2019s coming, Abernathy puts each of their inheritances on the line \\u2013 they\\u2019ll get nothing if he\\u2019s found dead by dawn.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"popularity\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 464.32203460842084,\n \"min\": 13.865,\n \"max\": 5389.964,\n \"num_unique_values\": 235,\n \"samples\": [\n 166.209\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"poster_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 233,\n \"samples\": [\n \"/8aF0iAKH9MJMYAZdi0Slg77RYa2.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"release_date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 129,\n \"samples\": [\n \"2024-02-01\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 235,\n \"samples\": [\n \"The Inheritance\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"video\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_average\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2.8867801696225075,\n \"min\": 0.0,\n \"max\": 10.0,\n \"num_unique_values\": 133,\n \"samples\": [\n 6.5\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_count\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 538,\n \"min\": 0,\n \"max\": 4849,\n \"num_unique_values\": 138,\n \"samples\": [\n 78\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 12
}
],
"source": [
"def convertJsonToDataFrame(json_data):\n",
" \"\"\"\n",
" Converts JSON data into a Pandas Dataframe\n",
"\n",
" Args:\n",
" Date Type - JSON: This function accepts any JSON data file as the argument for conversion.\n",
"\n",
" Returns:\n",
" Pandas Dataframe and print statement\n",
" \"\"\"\n",
" print('Converting JSON data to Pandas Dataframe \\n')\n",
" popular_movies_df = pd.json_normalize(json_data)\n",
" return popular_movies_df\n",
"\n",
"\n",
"# Assigning the Pandas Dataframe to a variable - \"popular_movies_df\"\n",
"popular_movies_2024_df = convertJsonToDataFrame(popular_movies_data_2024)\n",
"popular_movies_2024_df"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ikZuZjomEVOq"
},
"source": [
"# 6.0 Pagination - Looping APIs with While Loops \n",
"* Create a function that pulls data from the popular movies endpoint with filters for English movies released in 2023. \n",
"* This function includes a while loop that iterates through each page and automatically stops when the last record is retrieved. \n",
"* Include a feature that calculates the total number pages that the API call retrieved data from and the total number of records that were retrieved.\n",
"* Use try/exception blocks to handle errors that could arise.\n",
"\n",
"<b>NOTE:</b> This function uses a while loop to iterate through each page to retreive data specified in the filter. This is useful when you want to pull data from an API source where the quantity of pages are unkown."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "SE7fbrT0EVOq",
"outputId": "d0222016-f4a4-493e-9bdc-2d56152452ee",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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"\n",
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"\n",
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"\n",
"Response Code for page 501: 400\n",
"Rows of data retrieved: 420 \n",
"\n",
"There are no more records to retrieve. \n",
"\n",
"Total pages processed: 501 \n",
"\n",
"Total rows of data retrieved: 420 \n",
"\n",
"Converting JSON data to Pandas Dataframe \n",
"\n"
]
},
{
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" adult backdrop_path genre_ids \\\n",
"0 False /dbtGinhWWKgQLQ0hjZHMFWxBJcJ.jpg [28, 878, 27, 53] \n",
"1 False /wPNI1fd18z5TKBOK9Mv9Rfjb0j0.jpg [53, 18, 28, 80] \n",
"2 False /2KGxQFV9Wp1MshPBf8BuqWUgVAz.jpg [16, 28, 12, 35, 10751] \n",
"3 False /nb3xI8XI3w4pMVZ38VijbsyBqP4.jpg [18, 36] \n",
"4 False /yyFc8Iclt2jxPmLztbP617xXllT.jpg [35, 10751, 14] \n",
".. ... ... ... \n",
"415 False /d14tpaz2DlQBRXDk94M4pU2gXvj.jpg [99] \n",
"416 False /1Z8PEjwJduCWLA40HxlmvuoCGI8.jpg [16, 12, 35] \n",
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"419 False /zgeoMjGEKStumT0tcY4atSPw2Mv.jpg [99] \n",
"\n",
" id original_language original_title \\\n",
"0 1159518 en Black Noise \n",
"1 729165 en Out of Exile \n",
"2 940551 en Migration \n",
"3 872585 en Oppenheimer \n",
"4 787699 en Wonka \n",
".. ... ... ... \n",
"415 1015356 en To Kill a Tiger \n",
"416 1054972 en Rock Dog 3: Battle the Beat \n",
"417 996727 en The Price We Pay \n",
"418 828899 en Metalocalypse: Army of the Doomstar \n",
"419 1180248 en Bye Bye Barry \n",
"\n",
" overview popularity \\\n",
"0 Members of an elite security team deployed to ... 772.167 \n",
"1 Recently paroled thief Gabriel Russell tries t... 538.114 \n",
"2 After a migrating duck family alights on their... 363.551 \n",
"3 The story of J. Robert Oppenheimer's role in t... 327.033 \n",
"4 Willy Wonka – chock-full of ideas and determin... 308.373 \n",
".. ... ... \n",
"415 Ranjit, a farmer in India, takes on the fight ... 12.703 \n",
"416 After touring the world, Bodi takes some time ... 15.406 \n",
"417 After a pawn shop robbery goes askew, two crim... 23.843 \n",
"418 After the heroic rescue of Toki Wartooth, DETH... 20.244 \n",
"419 When NFL superstar Barry Sanders vanished at t... 16.820 \n",
"\n",
" poster_path release_date \\\n",
"0 /snKpXexv5dtWqEKEmXrJtp8QGQC.jpg 2023-11-03 \n",
"1 /jgF5XaXnJmOgMxulhy2k1f9LNNc.jpg 2023-01-20 \n",
"2 /ldfCF9RhR40mppkzmftxapaHeTo.jpg 2023-12-06 \n",
"3 /8Gxv8gSFCU0XGDykEGv7zR1n2ua.jpg 2023-07-19 \n",
"4 /qhb1qOilapbapxWQn9jtRCMwXJF.jpg 2023-12-06 \n",
".. ... ... \n",
"415 /qxzaYYRAH6gZoyJlnajCvYeL6Ms.jpg 2023-10-20 \n",
"416 /39Hr1FKfqqvx0umS60PCCWtBOKd.jpg 2023-02-02 \n",
"417 /1zjrFPZNGAJnJoqR7PxvsxRtsTt.jpg 2023-01-13 \n",
"418 /fGc9HKeGKebC1RD7WPt0NYDONTo.jpg 2023-08-22 \n",
"419 /bAS05MBhwnkNZi2ksMK6oZhWU6p.jpg 2023-11-20 \n",
"\n",
" title video vote_average vote_count \n",
"0 Black Noise False 5.313 16 \n",
"1 Out of Exile False 6.281 16 \n",
"2 Migration False 7.466 1547 \n",
"3 Oppenheimer False 8.094 8550 \n",
"4 Wonka False 7.200 3182 \n",
".. ... ... ... ... \n",
"415 To Kill a Tiger False 7.407 27 \n",
"416 Rock Dog 3: Battle the Beat False 6.148 27 \n",
"417 The Price We Pay False 5.900 154 \n",
"418 Metalocalypse: Army of the Doomstar False 6.815 46 \n",
"419 Bye Bye Barry False 8.000 15 \n",
"\n",
"[420 rows x 14 columns]"
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>adult</th>\n",
" <th>backdrop_path</th>\n",
" <th>genre_ids</th>\n",
" <th>id</th>\n",
" <th>original_language</th>\n",
" <th>original_title</th>\n",
" <th>overview</th>\n",
" <th>popularity</th>\n",
" <th>poster_path</th>\n",
" <th>release_date</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>0</th>\n",
" <td>False</td>\n",
" <td>/dbtGinhWWKgQLQ0hjZHMFWxBJcJ.jpg</td>\n",
" <td>[28, 878, 27, 53]</td>\n",
" <td>1159518</td>\n",
" <td>en</td>\n",
" <td>Black Noise</td>\n",
" <td>Members of an elite security team deployed to ...</td>\n",
" <td>772.167</td>\n",
" <td>/snKpXexv5dtWqEKEmXrJtp8QGQC.jpg</td>\n",
" <td>2023-11-03</td>\n",
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" <td>5.313</td>\n",
" <td>16</td>\n",
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" <tr>\n",
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" <td>False</td>\n",
" <td>/wPNI1fd18z5TKBOK9Mv9Rfjb0j0.jpg</td>\n",
" <td>[53, 18, 28, 80]</td>\n",
" <td>729165</td>\n",
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" <td>/jgF5XaXnJmOgMxulhy2k1f9LNNc.jpg</td>\n",
" <td>2023-01-20</td>\n",
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" <td>16</td>\n",
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" <tr>\n",
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" <td>False</td>\n",
" <td>/2KGxQFV9Wp1MshPBf8BuqWUgVAz.jpg</td>\n",
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" <td>940551</td>\n",
" <td>en</td>\n",
" <td>Migration</td>\n",
" <td>After a migrating duck family alights on their...</td>\n",
" <td>363.551</td>\n",
" <td>/ldfCF9RhR40mppkzmftxapaHeTo.jpg</td>\n",
" <td>2023-12-06</td>\n",
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" <td>7.466</td>\n",
" <td>1547</td>\n",
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" <td>2023-07-19</td>\n",
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" <td>8.094</td>\n",
" <td>8550</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>False</td>\n",
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" <td>[35, 10751, 14]</td>\n",
" <td>787699</td>\n",
" <td>en</td>\n",
" <td>Wonka</td>\n",
" <td>Willy Wonka – chock-full of ideas and determin...</td>\n",
" <td>308.373</td>\n",
" <td>/qhb1qOilapbapxWQn9jtRCMwXJF.jpg</td>\n",
" <td>2023-12-06</td>\n",
" <td>Wonka</td>\n",
" <td>False</td>\n",
" <td>7.200</td>\n",
" <td>3182</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",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>False</td>\n",
" <td>/d14tpaz2DlQBRXDk94M4pU2gXvj.jpg</td>\n",
" <td>[99]</td>\n",
" <td>1015356</td>\n",
" <td>en</td>\n",
" <td>To Kill a Tiger</td>\n",
" <td>Ranjit, a farmer in India, takes on the fight ...</td>\n",
" <td>12.703</td>\n",
" <td>/qxzaYYRAH6gZoyJlnajCvYeL6Ms.jpg</td>\n",
" <td>2023-10-20</td>\n",
" <td>To Kill a Tiger</td>\n",
" <td>False</td>\n",
" <td>7.407</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>416</th>\n",
" <td>False</td>\n",
" <td>/1Z8PEjwJduCWLA40HxlmvuoCGI8.jpg</td>\n",
" <td>[16, 12, 35]</td>\n",
" <td>1054972</td>\n",
" <td>en</td>\n",
" <td>Rock Dog 3: Battle the Beat</td>\n",
" <td>After touring the world, Bodi takes some time ...</td>\n",
" <td>15.406</td>\n",
" <td>/39Hr1FKfqqvx0umS60PCCWtBOKd.jpg</td>\n",
" <td>2023-02-02</td>\n",
" <td>Rock Dog 3: Battle the Beat</td>\n",
" <td>False</td>\n",
" <td>6.148</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>417</th>\n",
" <td>False</td>\n",
" <td>/f9PSbuMeBS5CuHEOVyymg5lcq8J.jpg</td>\n",
" <td>[28, 53, 9648, 80, 27]</td>\n",
" <td>996727</td>\n",
" <td>en</td>\n",
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" <td>23.843</td>\n",
" <td>/1zjrFPZNGAJnJoqR7PxvsxRtsTt.jpg</td>\n",
" <td>2023-01-13</td>\n",
" <td>The Price We Pay</td>\n",
" <td>False</td>\n",
" <td>5.900</td>\n",
" <td>154</td>\n",
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" <td>After the heroic rescue of Toki Wartooth, DETH...</td>\n",
" <td>20.244</td>\n",
" <td>/fGc9HKeGKebC1RD7WPt0NYDONTo.jpg</td>\n",
" <td>2023-08-22</td>\n",
" <td>Metalocalypse: Army of the Doomstar</td>\n",
" <td>False</td>\n",
" <td>6.815</td>\n",
" <td>46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>419</th>\n",
" <td>False</td>\n",
" <td>/zgeoMjGEKStumT0tcY4atSPw2Mv.jpg</td>\n",
" <td>[99]</td>\n",
" <td>1180248</td>\n",
" <td>en</td>\n",
" <td>Bye Bye Barry</td>\n",
" <td>When NFL superstar Barry Sanders vanished at t...</td>\n",
" <td>16.820</td>\n",
" <td>/bAS05MBhwnkNZi2ksMK6oZhWU6p.jpg</td>\n",
" <td>2023-11-20</td>\n",
" <td>Bye Bye Barry</td>\n",
" <td>False</td>\n",
" <td>8.000</td>\n",
" <td>15</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>420 rows × 14 columns</p>\n",
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"type": "dataframe",
"variable_name": "popular_movies_2023",
"summary": "{\n \"name\": \"popular_movies_2023\",\n \"rows\": 420,\n \"fields\": [\n {\n \"column\": \"adult\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"backdrop_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 315,\n \"samples\": [\n \"/xCXMHUMQJess3GACbR2PQI7sjeH.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"genre_ids\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 193902,\n \"min\": 296271,\n \"max\": 1211483,\n \"num_unique_values\": 315,\n \"samples\": [\n 1072371\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_language\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"en\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"original_title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 315,\n \"samples\": [\n \"Jules\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"overview\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 315,\n \"samples\": [\n \"A flying saucer lands in the backyard of an elderly suburbanite with memory problems, who forms a bond with the scared alien inside.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"popularity\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 66.49378683492255,\n \"min\": 12.703,\n \"max\": 772.167,\n \"num_unique_values\": 314,\n \"samples\": [\n 44.013\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"poster_path\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 315,\n \"samples\": [\n \"/yMOWu8rpZPiBI0j8MInBTtNO0vU.jpg\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"release_date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 172,\n \"samples\": [\n \"2023-11-21\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"title\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 315,\n \"samples\": [\n \"Jules\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"video\",\n \"properties\": {\n \"dtype\": \"boolean\",\n \"num_unique_values\": 1,\n \"samples\": [\n false\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_average\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.8689994407479383,\n \"min\": 0.0,\n \"max\": 8.433,\n \"num_unique_values\": 235,\n \"samples\": [\n 6.676\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"vote_count\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1184,\n \"min\": 0,\n \"max\": 8656,\n \"num_unique_values\": 239,\n \"samples\": [\n 81\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 13
}
],
"source": [
"# Establishing variables for the API\n",
"api_key = '460f7b576a1b5c789d7d574f7fcc4f5f'\n",
"language = 'en-US'\n",
"url = 'https://api.themoviedb.org'\n",
"popular_movie_endpoint = '/3/movie/popular'\n",
"params = {'api_key': api_key, 'language': language, 'year': 2023}\n",
"headers = {'accept': 'application/json'}\n",
"\n",
"def get_2023_popular_movie_data():\n",
" \"\"\"\n",
" This function fetches data from the popular movie endpoint, TMDB API.\n",
"\n",
" Raises:\n",
" SystemExit: Handles exceptions related to the API request call\n",
" SystemExit: Handle KeyError exceptions related to processing the API response\n",
"\n",
" Returns:\n",
" JSON: List of filtered JSON data extracted from the API request call\n",
" \"\"\"\n",
" all_pages_data = []\n",
" page = 1\n",
" while True:\n",
" try:\n",
" params['page'] = page\n",
" response = requests.get(url + popular_movie_endpoint, headers=headers, params=params)\n",
" print(f'Response Code for page {page}: {response.status_code}')\n",
" json_file = response.json()\n",
" filtered_results = [movie for movie in json_file.get('results', []) if movie.get('release_date', '').startswith('2023') and movie.get('original_language') == 'en']\n",
" all_pages_data.extend(filtered_results)\n",
" print('Rows of data retrieved: '+str(len(all_pages_data)), '\\n')\n",
"\n",
"\n",
" # If there are no more results in the JSON response, the script will print the statement and terminate\n",
" if json_file.get('results',[]) == []:\n",
" print('There are no more records to retrieve.', '\\n')\n",
" break\n",
" page += 1\n",
"\n",
" # Handle exceptions related to the API request call\n",
" except requests.exceptions.RequestException as e:\n",
" print(f'Error connecting to the API: {e}')\n",
" raise SystemExit\n",
"\n",
" # Handle exceptions related to processing the API response\n",
" except KeyError as e:\n",
" print(f'Error processing the API response: {e}')\n",
" raise SystemExit\n",
"\n",
" # Print the total number of pages processed\n",
" print(f'Total pages processed: {page}', '\\n')\n",
"\n",
" print('Total rows of data retrieved: ' + str(len(all_pages_data)), '\\n')\n",
" return all_pages_data\n",
"\n",
"\n",
"popular_movies_data_2023 = get_2023_popular_movie_data()\n",
"popular_movies_2023 = convertJsonToDataFrame(popular_movies_data_2023)\n",
"popular_movies_2023"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6l3p3zBCEVOr"
},
"source": [
"# 7.0 Create your own API script\n",
"### Objective: Get movie data from the TMDB API from both 2023 and 2024 that have Spanish as their original language. Ensure that you loop through each page in the API to gather data up to the maximum limit.\n",
"* url = ('https://api.themoviedb.org')\n",
"* endpoint = ('/3/discover/movie')\n",
"* language = ('es-ES')\n",
"* api_key = {your api key value}\n",
"* params = {'api_key': api_key, 'language': language, 'with_original_language':'es', 'release_date_gte': '2023-1-1'}\n",
"* headers = {'accept': 'application/json'}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Vi5DgIUEEVOs"
},
"outputs": [],
"source": [
"# Enter your API code here"
]
},
{
"cell_type": "code",
"source": [
"# Enter your API code here"
],
"metadata": {
"id": "w0qjAXaBKutF"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "73nFMJviEVOs"
},
"outputs": [],
"source": [
"# Enter your API code here"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "AlyINU-sEVOt"
},
"source": [
"# NOAA Weather API Example\n",
"This API takes latitude and longitude data points as parameters to get weather data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ficcAlTpEVOt",
"outputId": "0d870041-56b1-43ff-fa7f-529b7d4b2d06"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Response Code: 200\n",
"URL Link: https://api.weather.gov/points/25.7617,-80.1918 \n",
"\n",
"{'@context': ['https://geojson.org/geojson-ld/geojson-context.jsonld',\n",
" {'@version': '1.1',\n",
" '@vocab': 'https://api.weather.gov/ontology#',\n",
" 'bearing': {'@type': 's:QuantitativeValue'},\n",
" 'city': 's:addressLocality',\n",
" 'county': {'@type': '@id'},\n",
" 'distance': {'@id': 's:Distance',\n",
" '@type': 's:QuantitativeValue'},\n",
" 'forecastGridData': {'@type': '@id'},\n",
" 'forecastOffice': {'@type': '@id'},\n",
" 'geo': 'http://www.opengis.net/ont/geosparql#',\n",
" 'geometry': {'@id': 's:GeoCoordinates',\n",
" '@type': 'geo:wktLiteral'},\n",
" 'publicZone': {'@type': '@id'},\n",
" 's': 'https://schema.org/',\n",
" 'state': 's:addressRegion',\n",
" 'unit': 'http://codes.wmo.int/common/unit/',\n",
" 'unitCode': {'@id': 's:unitCode', '@type': '@id'},\n",
" 'value': {'@id': 's:value'},\n",
" 'wx': 'https://api.weather.gov/ontology#'}],\n",
" 'geometry': {'coordinates': [-80.1918, 25.7617], 'type': 'Point'},\n",
" 'id': 'https://api.weather.gov/points/25.7617,-80.1918',\n",
" 'properties': {'@id': 'https://api.weather.gov/points/25.7617,-80.1918',\n",
" '@type': 'wx:Point',\n",
" 'county': 'https://api.weather.gov/zones/county/FLC086',\n",
" 'cwa': 'MFL',\n",
" 'fireWeatherZone': 'https://api.weather.gov/zones/fire/FLZ173',\n",
" 'forecast': 'https://api.weather.gov/gridpoints/MFL/110,50/forecast',\n",
" 'forecastGridData': 'https://api.weather.gov/gridpoints/MFL/110,50',\n",
" 'forecastHourly': 'https://api.weather.gov/gridpoints/MFL/110,50/forecast/hourly',\n",
" 'forecastOffice': 'https://api.weather.gov/offices/MFL',\n",
" 'forecastZone': 'https://api.weather.gov/zones/forecast/FLZ173',\n",
" 'gridId': 'MFL',\n",
" 'gridX': 110,\n",
" 'gridY': 50,\n",
" 'observationStations': 'https://api.weather.gov/gridpoints/MFL/110,50/stations',\n",
" 'radarStation': 'KAMX',\n",
" 'relativeLocation': {'geometry': {'coordinates': [-80.208615,\n",
" 25.775163],\n",
" 'type': 'Point'},\n",
" 'properties': {'bearing': {'unitCode': 'wmoUnit:degree_(angle)',\n",
" 'value': 131},\n",
" 'city': 'Miami',\n",
" 'distance': {'unitCode': 'wmoUnit:m',\n",
" 'value': 2253.0645399099},\n",
" 'state': 'FL'},\n",
" 'type': 'Feature'},\n",
" 'timeZone': 'America/New_York'},\n",
" 'type': 'Feature'}\n"
]
}
],
"source": [
"# Weather API Example from NOAA - https://www.weather.gov/documentation/services-web-api#/default/zone_stations\n",
"\n",
"wx_response = requests.get(\"https://api.weather.gov/points/25.761681,-80.191788\", headers={'Accept': 'application/geo+json', 'User-Agent':'Panamax007'})\n",
"print('Response Code: ' + str(wx_response.status_code))\n",
"print('URL Link: ' + wx_response.url, '\\n')\n",
"pprint(wx_response.json())\n"
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "prb2G5-9JLDp"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "fba9POZLEVOt"
},
"source": [
"# OAuth2 Token Example - World Health Organization (WHO) Example\n",
"This is just a code example. It needs a client id and client secret from the WHO to work"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "1DjW18t6EVOu"
},
"outputs": [],
"source": [
"\n",
"token_endpoint = 'https://icdaccessmanagement.who.int/connect/token'\n",
"client_id = '...'\n",
"client_secret = '...'\n",
"scope = 'icdapi_access'\n",
"grant_type = 'client_credentials'\n",
"\n",
"\n",
"# get the OAUTH2 token\n",
"\n",
"# set data to post\n",
"payload = {'client_id': client_id,\n",
"\t \t 'client_secret': client_secret,\n",
" 'scope': scope,\n",
" 'grant_type': grant_type}\n",
"\n",
"# make request\n",
"r = requests.post(token_endpoint, data=payload, verify=False).json()\n",
"token = r['access_token']\n",
"\n",
"\n",
"# access ICD API\n",
"\n",
"uri = 'https://id.who.int/icd/entity'\n",
"\n",
"# HTTP header fields to set\n",
"headers = {'Authorization': 'Bearer '+token,\n",
" 'Accept': 'application/json',\n",
" 'Accept-Language': 'en',\n",
"\t 'API-Version': 'v2'}\n",
"\n",
"# make request\n",
"r = requests.get(uri, headers=headers, verify=False)\n",
"\n",
"# print the result\n",
"print (r.text)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
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"colab": {
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"collapsed_sections": [
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"nbformat": 4,
"nbformat_minor": 0
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