The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) in the index and columns of the resulting DataFrame.
Parameters:
data: DataFrame
values: column to aggregate, optional
index: column, Grouper , array, or list of the previous
columns: column, Grouper, array, or list of the previousaggfunc: function, list of functions, dict, default numpy.mean
-" If list of functions passed, the resulting pivot table will have hierarchical columns whose top level are the function names.
-" If dict is passed, the key is column to aggregate and value is function or list of functionsfill_value [scalar, default None]: Value to replace missing values with
margins [boolean, default False]: Add all row / columns (eg for subtotal / grand totals)
dropna [boolean, default True]: Do not include columns whose entries are all NaN
margins_name [string, default ’All’]: Name of the row / column that will contain the totals when margins is True.
Returns:
DataFrame
Code:
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