This is the process when you find yourself in a situation when there are overlapping categories per row and still one to categorize by single category... This will help to do just that and is so simple.

categorize_multiple.py

# Create a unique set, so it becomes clear 
genres = set()
for gen in df.Genre:
    for single_gen in map(str.strip, gen.split(",")):
        genres.add(single_gen)
        
# Create dict to store ids of that category
genre_ids = dict()
for gen in genres:
    genre_ids[gen] = []
    
# Then iterate over 'mixed' category column and save id there
for movie in df.iterrows():
    for gen in genre_ids.keys():
        if gen in movie[1]['Genre']:
            genre_ids[gen].append(movie[0])
            
# -- That's all! Now on top of that we can build more --

There is one more version for the same (from the Pandas Notebook) check it out here in this gist:
https://gist.github.com/AayushSameerShah/23b145fe9e3f56acc28fbdaf51186902