remove unused docstring vars that was previously used for @appender and @substition

Author: KevsterAmp

pandas/plotting/_core.py

@@ -271,220 +271,6 @@ def hist_frame(
     )
 
 
-_boxplot_doc = """
-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
-----------
-%(data)s\
-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)s\
-
-**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'>
-"""
-
-_backend_doc = """\
-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``.
-"""
-
-
-_bar_or_line_doc = """
-        Parameters
-        ----------
-        x : label or position, optional
-            Allows plotting of one column versus another. If not specified,
-            the index of the DataFrame is used.
-        y : label or position, optional
-            Allows plotting of one column versus another. If not specified,
-            all numerical columns are used.
-        color : str, array-like, or dict, optional
-            The color for each of the DataFrame's columns. Possible values are:
-
-            - A single color string referred to by name, RGB or RGBA code,
-                for instance 'red' or '#a98d19'.
-
-            - A sequence of color strings referred to by name, RGB or RGBA
-                code, which will be used for each column recursively. For
-                instance ['green','yellow'] each column's %(kind)s will be filled in
-                green or yellow, alternatively. If there is only a single column to
-                be plotted, then only the first color from the color list will be
-                used.
-
-            - A dict of the form {column name : color}, so that each column will be
-                colored accordingly. For example, if your columns are called `a` and
-                `b`, then passing {'a': 'green', 'b': 'red'} will color %(kind)ss for
-                column `a` in green and %(kind)ss for column `b` in red.
-
-        **kwargs
-            Additional keyword arguments are documented in
-            :meth:`DataFrame.plot`.
-
-        Returns
-        -------
-        matplotlib.axes.Axes or np.ndarray of them
-            An ndarray is returned with one :class:`matplotlib.axes.Axes`
-            per column when ``subplots=True``.
-"""
-
-
 def boxplot(
     data: DataFrame,
     column: str | list[str] | None = None,