parameters: (
      grouped,
      subplots=True,
      column=None,
      fontsize=None,
      rot=0,
      grid=True,
      ax=None,
      figsize=None,
      layout=None,
      sharex=False,
      sharey=True,
      backend=None,
      **kwargs,
  )
return_statement: return plot_backend.boxplot_frame_groupby(
          grouped,
          subplots=subplots,
          column=column,
          fontsize=fontsize,
          rot=rot,
          grid=grid,
          ax=ax,
          figsize=figsize,
          layout=layout,
          sharex=sharex,
          sharey=sharey,
          **kwargs,
      )
docstring: 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 str
      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)
          The layout of the plot: (rows, columns).
      sharex : bool, default False
          Whether x-axes will be shared among subplots.
  
          .. versionadded:: 0.23.1
      sharey : bool, default True
          Whether y-axes will be shared among subplots.
  
          .. versionadded:: 0.23.1
      backend : str, default None
          Backend to use instead of the backend specified in the option
          ``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
          specify the ``plotting.backend`` for the whole session, set
          ``pd.options.plotting.backend``.
  
          .. versionadded:: 1.0.0
  
      **kwargs
          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)
docstring_summary: Make box plots from DataFrameGroupBy data.
docstring_tokens: Make box plots from DataFrameGroupBy data .
function: def boxplot_frame_groupby(
      grouped,
      subplots=True,
      column=None,
      fontsize=None,
      rot=0,
      grid=True,
      ax=None,
      figsize=None,
      layout=None,
      sharex=False,
      sharey=True,
      backend=None,
      **kwargs,
  ):
      """
      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 str
      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)
          The layout of the plot: (rows, columns).
      sharex : bool, default False
          Whether x-axes will be shared among subplots.
  
          .. versionadded:: 0.23.1
      sharey : bool, default True
          Whether y-axes will be shared among subplots.
  
          .. versionadded:: 0.23.1
      backend : str, default None
          Backend to use instead of the backend specified in the option
          ``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
          specify the ``plotting.backend`` for the whole session, set
          ``pd.options.plotting.backend``.
  
          .. versionadded:: 1.0.0
  
      **kwargs
          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)
      """
      plot_backend = _get_plot_backend(backend)
      return plot_backend.boxplot_frame_groupby(
          grouped,
          subplots=subplots,
          column=column,
          fontsize=fontsize,
          rot=rot,
          grid=grid,
          ax=ax,
          figsize=figsize,
          layout=layout,
          sharex=sharex,
          sharey=sharey,
          **kwargs,
      )
function_tokens: def boxplot_frame_groupby ( grouped , subplots = True , column = None , fontsize = None , rot = 0 , grid = True , ax = None , figsize = None , layout = None , sharex = False , sharey = True , backend = None , * * kwargs , ) : plot_backend = _get_plot_backend ( backend ) return plot_backend . boxplot_frame_groupby ( grouped , subplots = subplots , column = column , fontsize = fontsize , rot = rot , grid = grid , ax = ax , figsize = figsize , layout = layout , sharex = sharex , sharey = sharey , * * kwargs , )