Constructing multiple boolean conditions

In Python, boolean expressions use the built-in logical operators and, or, and not. These keywords do not work with boolean indexing in pandas and are respectively replaced with &, |, and ~. Additionally, each expression must be wrapped in parentheses or an error will be raised.

Getting ready

Constructing a precise filter for your dataset might have you combining multiple boolean expressions together to extract an exact subset. In this recipe, we construct multiple boolean expressions before combining them together to find all the movies that have an imdb_score greater than 8, a content_rating of PG-13, and a title_year either before 2000 or after 2009.

 

How to do it...

1. Load in the movie dataset and set the index as the title:

>>> movie = pd.read_csv('data/movie.csv', index_col='movie_title')

2. Create a variable to hold each set of criteria independently as a boolean Series:

>>> criteria1 = movie.imdb_score > 8
>>> criteria2...