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 ...

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