pandas.Series.agg¶
-
Series.
agg
(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 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