Mapping out the connections of Oscar Winners | by Milan Janosov | Feb, 2024

On this quick piece, I take advantage of public Wikipedia information, Python programming, and community evaluation to extract and draw up a community of Oscar-winning actors and actresses.

All pictures had been created by the writer.

Wikipedia, as the biggest free, crowdsourced on-line encyclopedia, serves as a tremendously wealthy information supply on numerous public domains. Many of those domains, from movie to politics, contain numerous layers of networks beneath, expressing differing types of social phenomena similar to collaboration. As a result of approaching Academy Awards Ceremony, right here I present the instance of Oscar-winning actors and actresses on how we are able to use easy Pythonic strategies to show Wiki websites into networks.

First, let’s check out how, for example, the Wiki record of all Oscar-winning actors is structured:

This subpage properly exhibits all of the individuals who have ever acquired an Oscar and have been granted a Wiki profile (more than likely, no actors and actresses had been missed by the followers). On this article, I deal with appearing, which will be discovered within the following 4 subpages — together with principal and supporting actors and actresses:

urls = { ‘actor’ :’https://en.wikipedia.org/wiki/Class:Best_Actor_Academy_Award_winners’,’actress’ : ‘https://en.wikipedia.org/wiki/Class:Best_Actress_Academy_Award_winners’,’supporting_actor’ : ‘https://en.wikipedia.org/wiki/Class:Best_Supporting_Actor_Academy_Award_winners’,’supporting_actress’ : ‘https://en.wikipedia.org/wiki/Class:Best_Supporting_Actress_Academy_Award_winners’}

Now let’s write a easy block of code that checks every of those 4 listings, and utilizing the packages urllib and beautifulsoup, extracts the title of all artists:

from urllib.request import urlopenimport bs4 as bsimport re

# Iterate throughout the 4 categoriespeople_data = []

for class, url in urls.gadgets():

# Question the title itemizing web page and…