Pandas in Action

8 Reshaping and pivoting

This chapter covers

• Comparing wide and narrow data
• Generating a pivot table from a DataFrame
• Aggregating values by sum, average, count, and more
• Stacking and unstacking DataFrame index levels
• Melting a DataFrame

A data set can arrive in a format unsuited for the analysis that we’d like to perform on it. Sometimes, issues are confined to a specific column, row, or cell. A column may have the wrong data type, a row may have missing values, or a cell may have incorrect character casing. At other times, a data set may have larger structural problems that extend beyond the data. Perhaps the data set stores its values in a format that makes it easy to extract a single row but difficult to aggregate the data.

Reshaping