ng (e.g., `large`).
rot : float, default 0
    The rotation angle of labels (in degrees)
    with respect to the screen coordinate system.
grid : bool, default True
    Setting this to True will show the grid.
figsize : A tuple (width, height) in inches
    The size of the figure to create in matplotlib.
layout : tuple (rows, columns), optional
    For example, (3, 5) will display the subplots
    using 3 rows and 5 columns, starting from the top-left.
return_type : {'axes', 'dict', 'both'} or None, default 'axes'
    The kind of object to return. The default is ``axes``.

    * 'axes' returns the matplotlib axes the boxplot is drawn on.
    * 'dict' returns a dictionary whose values are the matplotlib
      Lines of the boxplot.
    * 'both' returns a namedtuple with the axes and dict.
    * when grouping with ``by``, a Series mapping columns to
      ``return_type`` is returned.

      If ``return_type`` is `None`, a NumPy array
      of axes with the same shape as ``layout`` is returned.
%(backend)s
**kwargs
    All other plotting keyword arguments to be passed to
    :func:`matplotlib.pyplot.boxplot`.

Returns
-------
result
    See Notes.

See Also
--------
pandas.Series.plot.hist: Make a histogram.
matplotlib.pyplot.boxplot : Matplotlib equivalent plot.

Notes
-----
The return type depends on the `return_type` parameter:

* 'axes' : object of class matplotlib.axes.Axes
* 'dict' : dict of matplotlib.lines.Line2D objects
* 'both' : a namedtuple with structure (ax, lines)

For data grouped with ``by``, return a Series of the above or a numpy
array:

* :class:`~pandas.Series`
* :class:`~numpy.array` (for ``return_type = None``)

Use ``return_type='dict'`` when you want to tweak the appearance
of the lines after plotting. In this case a dict containing the Lines
making up the boxes, caps, fliers, medians, and whiskers is returned.

Examples
--------

Boxplots can be created for every column in the dataframe
by ``df.boxplot()`` or indicating the columns to be used:

.. plot::
    :context: close-figs

    >>> np.random.seed(1234)
    >>> df = pd.DataFrame(np.random.randn(10, 4),
    ...                   columns=['Col1', 'Col2', 'Col3', 'Col4'])
    >>> boxplot = df.boxplot(column=['Col1', 'Col2', 'Col3'])  # doctest: +SKIP

Boxplots of variables distributions grouped by the values of a third
variable can be created using the option ``by``. For instance:

.. plot::
    :context: close-figs

    >>> df = pd.DataFrame(np.random.randn(10, 2),
    ...                   columns=['Col1', 'Col2'])
    >>> df['X'] = pd.Series(['A', 'A', 'A', 'A', 'A',
    ...                      'B', 'B', 'B', 'B', 'B'])
    >>> boxplot = df.boxplot(by='X')

A list of strings (i.e. ``['X', 'Y']``) can be passed to boxplot
in order to group the data by combination of the variables in the x-axis:

.. plot::
    :context: close-figs

    >>> df = pd.DataFrame(np.random.randn(10, 3),
    ...                   columns=['Col1', 'Col2', 'Col3'])
    >>> df['X'] = pd.Series(['A', 'A', 'A', 'A', 'A',
    ...                      'B', 'B', 'B', 'B', 'B'])
    >>> df['Y'] = pd.Series(['A', 'B', 'A', 'B', 'A',
    ...                      'B', 'A', 'B', 'A', 'B'])
    >>> boxplot = df.boxplot(column=['Col1', 'Col2'], by=['X', 'Y'])

The layout of boxplot can be adjusted giving a tuple to ``layout``:

.. plot::
    :context: close-figs

    >>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X',
    ...                      layout=(2, 1))

Additional formatting can be done to the boxplot, like suppressing the grid
(``grid=False``), rotating the labels in the x-axis (i.e. ``rot=45``)
or changing the fontsize (i.e. ``fontsize=15``):

.. plot::
    :context: close-figs

    >>> boxplot = df.boxplot(grid=False, rot=45, fontsize=15)  # doctest: +SKIP

The parameter ``return_type`` can be used to select the type of element
returned by `boxplot`.  When ``return_type='axes'`` is selected,
the matplotlib axes on which the boxplot is drawn are returned:

    >>> boxplot = df.boxplot(column=['Col1', 'Col2'], return_type='axes')
    >>> type(boxplot)
    <class 'matplotlib.axes._subplots.AxesSubplot'>

When grouping with ``by``, a Series mapping columns to ``return_type``
is returned:

    >>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X',
    ...                      return_type='axes')
    >>> type(boxplot)
    <class 'pandas.core.series.Series'>

If ``return_type`` is `None`, a NumPy array of axes with the same shape
as ``layout`` is returned:

    >>> boxplot = df.boxplot(column=['Col1', 'Col2'], by='X',
    ...                      return_type=None)
    >>> type(boxplot)
    <class 'numpy.ndarray'>
a