pandas.core.groupby.DataFrameGroupBy.boxplot

DataFrameGroupBy.boxplot(grouped, subplots=True, column=None, fontsize=None, rot=0, grid=True, ax=None, figsize=None, layout=None, sharex=False, sharey=True, **kwds) [source]

Make box plots from DataFrameGroupBy data.

Parameters:

grouped : Grouped DataFrame subplots : bool False - no subplots will be used True - create a subplot for each group column : column name or list of names, or vector Can be any valid input to groupby fontsize : int or string rot : label rotation angle grid : Setting this to True will show the grid ax : Matplotlib axis object, default None figsize : A tuple (width, height) in inches layout : tuple (optional) (rows, columns) for the layout of the plot sharex : bool, default False Whether x-axes will be shared among subplots New in version 0.23.1. sharey : bool, default True Whether y-axes will be shared among subplots New in version 0.23.1. `**kwds` : Keyword Arguments All other plotting keyword arguments to be passed to matplotlib’s boxplot function

Returns:

dict of key/value = group key/DataFrame.boxplot return value or DataFrame.boxplot return value in case subplots=figures=False

Examples

>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)