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pandas.Series.aggregate

Series.aggregate(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 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:

DataFrame, Series or scalar

if DataFrame.agg is called with a single function, returns a Series if DataFrame.agg is called with several functions, returns a DataFrame if Series.agg is called with single function, returns a scalar if Series.agg is called with several functions, returns a Series

See also

pandas.Series.apply
Invoke function on a Series.
pandas.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
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