add inline comments to plotting.boxplot_frame

Author: KevsterAmp

pandas/plotting/_core.py

@@ -684,8 +684,6 @@ def boxplot(
     )
 
 
-@Substitution(data="", backend=_backend_doc)
-@Appender(_boxplot_doc)
 def boxplot_frame(
     self: DataFrame,
     column=None,
@@ -700,6 +698,176 @@ def boxplot_frame(
     backend=None,
     **kwargs,
 ):
+    """
+
+    Make a box plot from DataFrame columns.
+
+    Make a box-and-whisker plot from DataFrame columns, optionally grouped
+    by some other columns. A box plot is a method for graphically depicting
+    groups of numerical data through their quartiles.
+    The box extends from the Q1 to Q3 quartile values of the data,
+    with a line at the median (Q2). The whiskers extend from the edges
+    of box to show the range of the data. By default, they extend no more than
+    `1.5 * IQR (IQR = Q3 - Q1)` from the edges of the box, ending at the farthest
+    data point within that interval. Outliers are plotted as separate dots.
+
+    For further details see
+    Wikipedia's entry for `boxplot <https://en.wikipedia.org/wiki/Box_plot>`_.
+
+    Parameters
+    ----------
+    column : str or list of str, optional
+        Column name or list of names, or vector.
+        Can be any valid input to :meth:`pandas.DataFrame.groupby`.
+    by : str or array-like, optional
+        Column in the DataFrame to :meth:`pandas.DataFrame.groupby`.
+        One box-plot will be done per value of columns in `by`.
+    ax : object of class matplotlib.axes.Axes, optional
+        The matplotlib axes to be used by boxplot.
+    fontsize : float or str
+        Tick label font size in points or as a string (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 : 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``.
+
+    **kwargs
+        All other plotting keyword arguments to be passed to
+        :func:`matplotlib.pyplot.boxplot`.
+
+    Returns
+    -------
+    result
+        See Notes.
+
+    See Also
+    --------
+    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._axes.Axes'>
+
+    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.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'>
+    """
+
     plot_backend = _get_plot_backend(backend)
     return plot_backend.boxplot_frame(
         self,