pandas.DataFrame.aggregate — pandas 0.25.3 documentation (original) (raw)

DataFrame. aggregate(self, func, axis=0, *args, **kwargs)[source]¶

Aggregate using one or more operations over the specified axis.

New in version 0.20.0.

Parameters:	func : function, str, list or dict Function to use for aggregating the data. If a function, must either work when passed a DataFrame or when passed to DataFrame.apply. Accepted combinations are: function string function name list of functions and/or function names, e.g. [np.sum, 'mean'] dict of axis labels -> functions, function names or list of such. axis : {0 or ‘index’, 1 or ‘columns’}, default 0 If 0 or ‘index’: apply function to each column. If 1 or ‘columns’: apply function to each row. args Positional arguments to pass to func. *kwargs Keyword arguments to pass to func.
Returns:	scalar, Series or DataFrame The return can be: scalar : when Series.agg is called with single function Series : when DataFrame.agg is called with a single function DataFrame : when DataFrame.agg is called with several functions Return scalar, Series or DataFrame. The aggregation operations are always performed over an axis, either the index (default) or the column axis. This behavior is different from numpy aggregation functions (mean, median, prod, sum, std, var), where the default is to compute the aggregation of the flattened array, e.g., numpy.mean(arr_2d) as opposed to numpy.mean(arr_2d, axis=0). agg is an alias for aggregate. Use the alias.

Parameters:

func : function, str, list or dict Function to use for aggregating the data. If a function, must either work when passed a DataFrame or when passed to DataFrame.apply. Accepted combinations are: function string function name list of functions and/or function names, e.g. [np.sum, 'mean'] dict of axis labels -> functions, function names or list of such. axis : {0 or ‘index’, 1 or ‘columns’}, default 0 If 0 or ‘index’: apply function to each column. If 1 or ‘columns’: apply function to each row. *args Positional arguments to pass to func. **kwargs Keyword arguments to pass to func.

Returns:

scalar, Series or DataFrame The return can be: scalar : when Series.agg is called with single function Series : when DataFrame.agg is called with a single function DataFrame : when DataFrame.agg is called with several functions Return scalar, Series or DataFrame. The aggregation operations are always performed over an axis, either the index (default) or the column axis. This behavior is different from numpy aggregation functions (mean, median, prod, sum, std, var), where the default is to compute the aggregation of the flattened array, e.g., numpy.mean(arr_2d) as opposed to numpy.mean(arr_2d, axis=0). agg is an alias for aggregate. Use the alias.