pandas.Series.aggregate

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

Aggregate using one or more operations over the specified axis.

New in version 0.20.0.

Parameters

funcfunction, 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:

• 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.

See also

Series.apply

Invoke function on a Series.

Series.transform

Transform function producing a Series with like indexes.

Notes

agg is an alias for aggregate. Use the alias.

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

Examples

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

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

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

pandas.Series.agg pandas.Series.align