aggregate(self, func=None, axis=0, *args, **kwargs)

Notes

:None:None:`agg` is an alias for aggregate . Use the alias.

Functions that mutate the passed object can produce unexpected behavior or errors and are not supported. See gotchas.udf-mutation for more details.

A passed user-defined-function will be passed a Series for evaluation.

Parameters

func : function, str, list or dict

Function to use for aggregating the data. If a function, must either work when passed a Series or when passed to Series.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'}

Parameter needed for compatibility with DataFrame.

*args :

Positional arguments to pass to func .

**kwargs :

Keyword arguments to pass to func .

Returns

scalar, Series or DataFrame

The return can be:

Aggregate using one or more operations over the specified axis.

See Also

Series.apply

Invoke function on a Series.

Series.transform

Transform function producing a Series with like indexes.

Examples

This example is valid syntax, but we were not able to check execution

>>> s = pd.Series([1, 2, 3, 4])
... s
0    1
1    2
2    3
3    4
dtype: int64

This example is valid syntax, but we were not able to check execution

>>> s.agg('min')
1

This example is valid syntax, but we were not able to check execution

>>> s.agg(['min', 'max'])
min   1
max   4
dtype: int64

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.window.expanding.Expanding.aggregate pandas.core.series.Series.aggregate pandas.core.series.Series.apply pandas.core.series.Series.transform pandas.core.window.rolling.Window.aggregate

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