Explore and run machine learning code with Kaggle Notebooks Using data from no data sources. Project Title: Scraping Movie Database from IMDB. Project Description: I need data from IMDB for film Name, Release Date, Genres, Language, Studio, Director, and Filming Locations. Can you scrape for films of specific countries? How much would you charge? For similar work requirements feel free to email us on info@webscrapingexpert.com.
| frombs4importBeautifulSoup |
| importrequests |
| importre |
| # Download IMDB's Top 250 data |
| url='http://www.imdb.com/chart/top' |
| response=requests.get(url) |
| soup=BeautifulSoup(response.text, 'lxml') |
| movies=soup.select('td.titleColumn') |
| links= [a.attrs.get('href') forainsoup.select('td.titleColumn a')] |
| crew= [a.attrs.get('title') forainsoup.select('td.titleColumn a')] |
| ratings= [b.attrs.get('data-value') forbinsoup.select('td.posterColumn span[name=ir]')] |
| votes= [b.attrs.get('data-value') forbinsoup.select('td.ratingColumn strong')] |
| imdb= [] |
| # Store each item into dictionary (data), then put those into a list (imdb) |
| forindexinrange(0, len(movies)): |
| # Seperate movie into: 'place', 'title', 'year' |
| movie_string=movies[index].get_text() |
| movie= (' '.join(movie_string.split()).replace('.', ')) |
| movie_title=movie[len(str(index))+1:-7] |
| year=re.search('((.*?))', movie_string).group(1) |
| place=movie[:len(str(index))-(len(movie))] |
| data= {'movie_title': movie_title, |
| 'year': year, |
| 'place': place, |
| 'star_cast': crew[index], |
| 'rating': ratings[index], |
| 'vote': votes[index], |
| 'link': links[index]} |
| imdb.append(data) |
| foriteminimdb: |
| print(item['place'], '-', item['movie_title'], '('+item['year']+') -', 'Starring:', item['star_cast']) |
commented Jan 5, 2018
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Get Estimated Price QuoteProject Title: Scrape IMDB Movie Data-set
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Project Description:
Hello Team,
We are planning to scrape information of various Films from IMDB data-set.
Web Scraping Imdb Free
Please go through each Genres of the Movies and get details for each movie available.
Web Scraping Imdb R
Extract the detail for following columns:
– Title of the Movie
– Technical aspects
– Genre
– Language
– Box office and currency
– Ratings
– Main actors
– Directors
– Writers
– Producer
– Production company
– Budget of the movie and currency
– Critics
– Advertisement
– Sequel
– Screens
Note that we need only Movies and not the TV Series.
What would be the price? Also advise, how long will it take for the completion of this task?
For similar work requirements feel free to email us on info@webscrapingexpert.com.