Preserving Series with the where method

Boolean indexing necessarily filters your dataset by removing all the rows that don't match the criteria. Instead of dropping all these values, it is possible to keep them using the where method. The where method preserves the size of your Series or DataFrame and either sets the values that don't meet the criteria for missing or replaces them with something else.

Getting ready

In this recipe, we pass the where method boolean conditions to put a floor and ceiling on the minimum and maximum number of Facebook likes for actor 1 in the movie dataset.

How to do it...

1. Read the movie dataset, set the movie title as the index, and select all the values in the actor_1_facebook_likes column that are not missing:

>>> movie = pd.read_csv('data/movie.csv', index_col='movie_title')
>>> fb_likes = movie['actor_1_facebook_likes'].dropna()
>>> fb_likes.head()
movie_title
Avatar                                         1000.0
Pirates of the Caribbean...