https://www.imdb.com/title/tt5348176/

import scrapy

class ImdbSpider(scrapy.Spider):
    '''Crawls an IMDB page for a given movie or show and 
        yields its actors and related works'''
    name = 'imdb_spider'
    
    start_urls = ['https://www.imdb.com/title/tt16290412/']

    def parse(self, response):
        '''navigates to credits page from a given IMDB show/film page'''
                
        for url in self.start_urls:
            credURL = url + 'fullcredits/'
            yield scrapy.Request(url=credURL, callback=self.parse_full_credits)

    def parse_full_credits(self, response):
        '''parses credits page and navigates to actor 
           pages for each actor in the credits page '''
        
        # Get list of URLs for actor pages
        actor_urls = [a.attrib["href"] for a in response.css("td.primary_photo a")]
        for url in actor_urls:
            #href only contains ID, not full link
            actorURL = 'https://www.imdb.com' + url
            yield scrapy.Request(url=actorURL, callback=self.parse_actor_page) 

    def parse_actor_page(self, response):
        '''parses actor page for each credited actor.  
           yields actor and film/show names as a  
           key-value pair for each project the actor has acted in'''
        
        # Every title is written as 'actor name - IMDB'
        # We can extract just the name using string indexing
        title = response.css('title::text').getall()[0]
        name = title[:len(title) - 7]

        # From div.filmo-rows, we filter out film/tv IDs 
        # that are not acting credits 
        credIDs = response.css('div.filmo-row::attr(id)').getall()
        projects = [l[6:] for l in credIDs if 'actor' in l]

        # Then, find the film/tv show name under the correct link
        titleFunc = lambda p: response.css('div.filmo-row a[href*="' + p + '"]::text').get()
        actedList = [titleFunc(p) for p in projects]

        for acted in actedList:
            yield {'actor' : name, 'movie_or_TV_name' : acted}

import pandas as pd
import matplotlib.pyplot as plt

# Ensures that all rows all displayed
pd.set_option('display.max_rows', None)

df = pd.read_csv('results.csv')

df[df.actor == "Bill Hader"].head()

df.groupby('movie_or_TV_name').count().sort_values(by='actor',ascending=False)