It is possible to compare two columns from the same DataFrame to produce a boolean Series. For instance, we could determine the percentage of movies that have actor 1 with more Facebook likes than actor 2. To do this, we would select both of these columns and then drop any of the rows that had missing values for either movie. Then we would make the comparison and calculate the mean:

>>> actors = movie[['actor_1_facebook_likes', 
                    'actor_2_facebook_likes']].dropna()
>>> (actors['actor_1_facebook_likes'] > 
     actors['actor_2_facebook_likes']).mean()
.978