oupby.SeriesGroupBy.rolling ](pandas.core.groupby.SeriesGroupBy.rolling.html)
    * [ pandas.core.groupby.SeriesGroupBy.sample ](pandas.core.groupby.SeriesGroupBy.sample.html)
    * [ pandas.core.groupby.SeriesGroupBy.sem ](pandas.core.groupby.SeriesGroupBy.sem.html)
    * [ pandas.core.groupby.SeriesGroupBy.shift ](pandas.core.groupby.SeriesGroupBy.shift.html)
    * [ pandas.core.groupby.SeriesGroupBy.size ](pandas.core.groupby.SeriesGroupBy.size.html)
    * [ pandas.core.groupby.SeriesGroupBy.skew ](pandas.core.groupby.SeriesGroupBy.skew.html)
    * [ pandas.core.groupby.SeriesGroupBy.std ](pandas.core.groupby.SeriesGroupBy.std.html)
    * [ pandas.core.groupby.SeriesGroupBy.sum ](pandas.core.groupby.SeriesGroupBy.sum.html)
    * [ pandas.core.groupby.SeriesGroupBy.var ](pandas.core.groupby.SeriesGroupBy.var.html)
    * [ pandas.core.groupby.SeriesGroupBy.tail ](pandas.core.groupby.SeriesGroupBy.tail.html)
    * [ pandas.core.groupby.SeriesGroupBy.take ](pandas.core.groupby.SeriesGroupBy.take.html)
    * [ pandas.core.groupby.SeriesGroupBy.value_counts ](pandas.core.groupby.SeriesGroupBy.value_counts.html)
    * [ pandas.core.groupby.DataFrameGroupBy.boxplot ](pandas.core.groupby.DataFrameGroupBy.boxplot.html)
    * [ pandas.core.groupby.DataFrameGroupBy.hist ](pandas.core.groupby.DataFrameGroupBy.hist.html)
    * [ pandas.core.groupby.SeriesGroupBy.hist ](pandas.core.groupby.SeriesGroupBy.hist.html)
    * [ pandas.core.groupby.DataFrameGroupBy.plot ](pandas.core.groupby.DataFrameGroupBy.plot.html)
    * [ pandas.core.groupby.SeriesGroupBy.plot ](pandas.core.groupby.SeriesGroupBy.plot.html)
  * [ Resampling ](../resampling.html)
  * [ Style ](../style.html)
  * [ Plotting ](../plotting.html)
  * [ Options and settings ](../options.html)
  * [ Extensions ](../extensions.html)
  * [ Testing ](../testing.html)
  * [ Missing values ](../missing_value.html)

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

#  pandas.core.groupby.DataFrameGroupBy.tail  #

DataFrameGroupBy.  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
    

[ __ previous  pandas.core.groupby.DataFrameGroupBy.var
](pandas.core.groupby.DataFrameGroupBy.var.html "previous page") [ next
pandas.core.groupby.DataFrameGroupBy.take  __
](pandas.core.groupby.DataFrameGroupBy.take.html "next page")

__ On this page

  * ` DataFrameGroupBy.tail()  `

[ __ Show Source
](../../_sources/reference/api/pandas.core.groupby.DataFrameGroupBy.tail.rst.txt)

© 2024, pandas via [ NumFOCUS, Inc. ](https://numfocus.org) Hosted by [
OVHcloud ](https://www.ovhcloud.com) .

Created using [ Sphinx ](https://www.sphinx-doc.org/) 7.2.6.  

Built with the [ PyData Sphinx Theme ](https://pydata-sphinx-
theme.readthedocs.io/en/stable/index.html) 0.14.4.