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  * [ Missing values ](../missing_value.html)

  * [ __ ](../../index.html)
  * [ API reference ](../index.html)
  * [ GroupBy ](../groupby.html)
  * pandas.NamedAgg 

#  pandas.NamedAgg  #

_ class  _ pandas.  NamedAgg  (  _ column  _ , _ aggfunc  _ )  [ [source]
](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/groupby/generic.py#L124-L151) #

    

Helper for column specific aggregation with control over output column names.

Subclass of typing.NamedTuple.

Parameters  :

    

**column** Hashable

    

Column label in the DataFrame to apply aggfunc.

**aggfunc** function or str

    

Function to apply to the provided column. If string, the name of a built-in
pandas function.

Examples

    
    
    >>> df = pd.DataFrame({"key": [1, 1, 2], "a": [-1, 0, 1], 1: [10, 11, 12]})
    >>> agg_a = pd.NamedAgg(column="a", aggfunc="min")
    >>> agg_1 = pd.NamedAgg(column=1, aggfunc=lambda x: np.mean(x))
    >>> df.groupby("key").agg(result_a=agg_a, result_1=agg_1)
         result_a  result_1
    key
    1          -1      10.5
    2           1      12.0
    

Attributes

` aggfunc  ` |  Alias for field number 1   
---|---  
` column  ` |  Alias for field number 0   
  
Methods

` count  ` (value,Â /)  |  Return number of occurrences of value.   
---|---  
` index  ` (value[,Â start,Â stop])  |  Return first index of value.   
  
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__ On this page

  * ` NamedAgg  `

[ __ Show Source ](../../_sources/reference/api/pandas.NamedAgg.rst.txt)

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