Pandas in Action

5 Filtering a DataFrame

This chapter covers

• Reducing a DataFrame’s memory use
• Extracting DataFrame rows by one or more conditions
• Filtering a DataFrame for rows that include or exclude null values
• Selecting column values that fall between a range
• Removing duplicate and null values from a DataFrame

In chapter 4, we learned how to extract rows, columns, and cell values from a DataFrame by using the loc and iloc accessors. These accessors work well when we know the index labels and positions of the rows/columns we want to target. Sometimes, we may want to target rows not by an identifier but by a condition or a criterion. We may want to extract a subset of rows in which a column holds a specific value, for example.

In this chapter, we’ll learn ...