Numerical Computing with Python

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: At World's End      40000.0
Spectre                                       11000.0
The Dark Knight Rises                         27000.0
Star Wars: Episode VII - The Force Awakens      131.0
Name: actor_1_facebook_likes, dtype: float64

2. Let's use the describe method to get a sense of the distribution:

>>> fb_likes.describe(percentiles=[.1, .25, .5, .75, .9]) \            .astype(int)count 4909 mean 6494 std 15106 min 0 10% 240 25% 607 50% 982 75% 11000 90% 18000 max 640000 ...