Numerical Computing with Python

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It is possible to apply our customized function to multiple aggregating columns. We simply add more column names to the indexing operator. The max_deviation function only works with numeric columns:

>>> college.groupby('STABBR')['UGDS', 'SATVRMID', 'SATMTMID'] \           .agg(max_deviation).round(1).head()

You can also use your customized aggregation function along with the prebuilt functions. The following does this and groups by state and religious affiliation:

>>> college.groupby(['STABBR', 'RELAFFIL']) \            ['UGDS', 'SATVRMID', 'SATMTMID'] \           .agg([max_deviation, 'mean', 'std']).round(1).head()

Notice that pandas uses the name of the ...