SeriesGroupBy.resample.html)
    * [ pandas.core.groupby.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.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.SeriesGroupBy.hist  #

SeriesGroupBy.  hist  (  _ by  =  None  _ , _ ax  =  None  _ , _ grid  =  True
_ , _ xlabelsize  =  None  _ , _ xrot  =  None  _ , _ ylabelsize  =  None  _ ,
_ yrot  =  None  _ , _ figsize  =  None  _ , _ bins  =  10  _ , _ backend  =
None  _ , _ legend  =  False  _ , _ **  kwargs  _ )  [ [source]
](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/groupby/generic.py#L1247-L1278) #

    

Draw histogram of the input series using matplotlib.

Parameters  :

    

**by** object, optional

    

If passed, then used to form histograms for separate groups.

**ax** matplotlib axis object

    

If not passed, uses gca().

**grid** bool, default True

    

Whether to show axis grid lines.

**xlabelsize** int, default None

    

If specified changes the x-axis label size.

**xrot** float, default None

    

Rotation of x axis labels.

**ylabelsize** int, default None

    

If specified changes the y-axis label size.

**yrot** float, default None

    

Rotation of y axis labels.

**figsize** tuple, default None

    

Figure size in inches by default.

**bins** int or sequence, default 10

    

Number of histogram bins to be used. If an integer is given, bins + 1 bin
edges are calculated and returned. If bins is a sequence, gives bin edges,
including left edge of first bin and right edge of last bin. In this case,
bins is returned unmodified.

**backend** str, default None

    

Backend to use instead of the backend specified in the option `
plotting.backend  ` . For instance, âmatplotlibâ. Alternatively, to
specify the ` plotting.backend  ` for the whole session, set `
pd.options.plotting.backend  ` .

**legend** bool, default False

    

Whether to show the legend.

****kwargs**

    

To be passed to the actual plotting function.

Returns  :

    

matplotlib.AxesSubplot

    

A histogram plot.

See also

[ ` matplotlib.axes.Axes.hist  `
](https://matplotlib.org/stable/api/_as_gen/matplotl