Selecting with booleans, integer location, and labels

Chapter 10, Selecting Subsets of Data, covered a wide range of recipes on selecting different subsets of data through the .iloc and .loc indexers. Both these indexers select rows and columns simultaneously by either integer location or label. Both these indexers can also do data selection through boolean indexing, even though booleans are not integers and not labels.

Getting ready

In this recipe, we will filter both rows and columns with boolean indexing for both the .iloc and .loc indexers.

How to do it...

1. Read in the movie dataset, set the index as the title, and then create a boolean Series matching all movies with a content rating of G and an IMDB score less than 4:

>>> movie = pd.read_csv('data/movie.csv', index_col='movie_title')
>>> c1 = movie['content_rating'] == 'G'
>>> c2 = movie['imdb_score'] < 4
>>> criteria = c1 & c2

2. Let's first pass these criteria to the .loc indexer to filter the rows...