On this short piece, I take advantage of public Wikipedia data, Python programming, and network evaluation to extract and draw up a network of Oscar-winning actors and actresses.
All images were created by the writer.
Wikipedia, as the most important free, crowdsourced online encyclopedia, serves as a tremendously wealthy data source on various public domains. Lots of these domains, from film to politics, involve various layers of networks underneath, expressing different forms of social phenomena equivalent to collaboration. As a result of the approaching Academy Awards Ceremony, here I show the instance of Oscar-winning actors and actresses on how we are able to use easy Pythonic methods to show Wiki sites into networks.
First, let’s take a take a look at how, as an example, the Wiki list of all Oscar-winning actors is structured:
This subpage nicely shows all of the individuals who have ever received an Oscar and have been granted a Wiki profile (most probably, no actors and actresses were missed by the fans). In this text, I give attention to acting, which could be present in the next 4 subpages — including foremost and supporting actors and actresses:
urls = { 'actor' :'https://en.wikipedia.org/wiki/Category:Best_Actor_Academy_Award_winners',
'actress' : 'https://en.wikipedia.org/wiki/Category:Best_Actress_Academy_Award_winners',
'supporting_actor' : 'https://en.wikipedia.org/wiki/Category:Best_Supporting_Actor_Academy_Award_winners',
'supporting_actress' : 'https://en.wikipedia.org/wiki/Category:Best_Supporting_Actress_Academy_Award_winners'}
Now let’s write an easy block of code that checks each of those 4 listings, and using the packages urllib and beautifulsoup, extracts the name of all artists:
from urllib.request import urlopen
import bs4 as bs
import re# Iterate across the 4 categories
people_data = []
for category, url in urls.items():
# Query the name listing page and…
