SeriesGroupBy.resample.html)
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  * [ __ ](../../index.html)
  * [ API reference ](../index.html)
  * [ GroupBy ](../groupby.html)
  * pandas.core.... 

#  pandas.core.groupby.SeriesGroupBy.tail  #

SeriesGroupBy.  tail  (  _ n  =  5  _ )  [ [source]
](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/groupby/groupby.py#L5499-L5540) #

    

Return last n rows of each group.

Similar to ` .apply(lambda  x:  x.tail(n))  ` , but it returns a subset of
rows from the original DataFrame with original index and order preserved ( `
as_index  ` flag is ignored).

Parameters  :

    

**n** int

    

If positive: number of entries to include from end of each group. If negative:
number of entries to exclude from start of each group.

Returns  :

    

Series or DataFrame

    

Subset of original Series or DataFrame as determined by n.

See also

` Series.groupby  `

    

Apply a function groupby to a Series.

` DataFrame.groupby  `

    

Apply a function groupby to each row or column of a DataFrame.

Examples

    
    
    >>> df = pd.DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
    ...                   columns=['A', 'B'])
    >>> df.groupby('A').tail(1)
       A  B
    1  a  2
    3  b  2
    >>> df.groupby('A').tail(-1)
       A  B
    1  a  2
    3  b  2
    

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  * ` SeriesGroupBy.tail()  `

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