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getGenres([$lang]) getMoviesByGenre($id, [$page], [$lang]) Movies & TV Series getTopRated([$page], [$type], [$lang]) getPopular([$page], [$type], [$lang]) Movies searchMovie($query, [$page], [$adult], [$lang]) getMovie($id, [$lang]) getMovieCast($id) getMovieImage...
Before we can make a request using the API, the very first thing we have to do is to register and get our API Key from themoviedb.org. The Movie Database (TMDb API) We will build a great movie app. Here are the main features of the app that we will build: List of movies by ...
hk created branch 9-tmdbservice-findbyimdbid-always-uses-movieresults to address this issue 3 months ago hk mentioned in commit f90501e8 3 months ago Please register or sign in to reply0 Assignees None Labels Bug Milestone 2.3 Due
#credits,movies两个表中都有字段id,title,检查两个字段是否相同(movies['title']==credits['title']).describe()#删除重复字段 del movies['title']#合并两张表,参数代表合并方式 df=credits.merge(right=movies,how='inner',left_on='movie_id',right_on='id')#删除分析不需要的字段 ...
#credits,movies两个表中都有字段id,title,检查两个字段是否相同(movies['title']==credits['title']).describe()#删除重复字段 del movies['title']#合并两张表,参数代表合并方式 df=credits.merge(right=movies,how='inner',left_on='movie_id',right_on='id')#删除分析不需要的字段 ...
Get a movie $item=newItem($tmdb);$movie=$item->getMovie($movie_id);echo$movie->getTitle(); The getter returns aMovieobject. See demo TV Show Search a TV Show $search=newSearch($tmdb);$responses=$search->tvshow('game of thrones'); ...
__get_tmdb_movie_detail(tmdbid) if tmdb_info: tmdb_info['media_type'] = MediaType.MOVIE else: if mtype == MediaType.MOVIE: tmdb_info = self.__get_tmdb_movie_detail(tmdbid) if tmdb_info: tmdb_info['media_type'] = MediaType.MOVIE else: tmdb_info = self.__get_tmdb_tv_detail(...
movie_id: 电影标识号 title: 电影名称 cast: 演员列表 crew: 全体工作人员 import pandas as pd import numpy as np import os import matplotlib.pyplot as plt %matplotlib inline import seaborn as sns import json plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['font.family']='sans-...
本报告的数据来源于Kaggle平台上的项目TMDB(The Movie Database),共计4803部电影,主要为美国地区一百年间(1916-2017)的电影作品。 通过对电影数据的分析,利用数据可视化的方法,发现流行趋势,找到投资方向,为本行业新入局者提供一定参考建议。 本文重点在于数据可视化方法,未能面面俱到敬请谅解。