Filtering data from a dataset is one of the most common and basic operations. There are numerous ways to filter (or subset) data in pandas with boolean indexing. Boolean indexing (also known as boolean selection) can be a confusing term, but for the purposes of pandas, it refers to selecting rows by providing a boolean value (True or False) for each row. These boolean values are usually stored in a Series or NumPy ndarray and are usually created by applying a boolean condition to one or more columns in a DataFrame. We begin by creating boolean Series and calculating statistics on them and then move on to creating more complex conditionals before using boolean indexing in a wide variety of ways to filter data.