DOC: change plot docstring to inline from @doc for SeriesGroupBy

acrossler · acrossler · commit ff32786aeb6e · 2025-11-11T16:05:33.000-08:00
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
@@ -1629,8 +1629,223 @@ def alt(obj):
         )
 
     @property
-    @doc(Series.plot.__doc__)
     def plot(self) -> GroupByPlot:
+        """
+        Make plots of Series or DataFrame.
+
+        Uses the backend specified by the
+        option ``plotting.backend``. By default, matplotlib is used.
+
+        Parameters
+        ----------
+        data : Series or DataFrame
+            The object for which the method is called.
+
+        Attributes
+        ----------
+        x : label or position, default None
+            Only used if data is a DataFrame.
+        y : label, position or list of label, positions, default None
+            Allows plotting of one column versus another. Only used if data is a
+            DataFrame.
+        kind : str
+            The kind of plot to produce:
+
+            - 'line' : line plot (default)
+            - 'bar' : vertical bar plot
+            - 'barh' : horizontal bar plot
+            - 'hist' : histogram
+            - 'box' : boxplot
+            - 'kde' : Kernel Density Estimation plot
+            - 'density' : same as 'kde'
+            - 'area' : area plot
+            - 'pie' : pie plot
+            - 'scatter' : scatter plot (DataFrame only)
+            - 'hexbin' : hexbin plot (DataFrame only)
+        ax : matplotlib axes object, default None
+            An axes of the current figure.
+        subplots : bool or sequence of iterables, default False
+            Whether to group columns into subplots:
+
+            - ``False`` : No subplots will be used
+            - ``True`` : Make separate subplots for each column.
+            - sequence of iterables of column labels: Create a subplot for each
+            group of columns. For example `[('a', 'c'), ('b', 'd')]` will
+            create 2 subplots: one with columns 'a' and 'c', and one
+            with columns 'b' and 'd'. Remaining columns that aren't specified
+            will be plotted in additional subplots (one per column).
+
+            .. versionadded:: 1.5.0
+
+        sharex : bool, default True if ax is None else False
+            In case ``subplots=True``, share x axis and set some x axis labels
+            to invisible; defaults to True if ax is None otherwise False if
+            an ax is passed in; Be aware, that passing in both an ax and
+            ``sharex=True`` will alter all x axis labels for all axis in a figure.
+        sharey : bool, default False
+            In case ``subplots=True``, share y axis and set some y axis labels to invisible.
+        layout : tuple, optional
+            (rows, columns) for the layout of subplots.
+        figsize : a tuple (width, height) in inches
+            Size of a figure object.
+        use_index : bool, default True
+            Use index as ticks for x axis.
+        title : str or list
+            Title to use for the plot. If a string is passed, print the string
+            at the top of the figure. If a list is passed and `subplots` is
+            True, print each item in the list above the corresponding subplot.
+        grid : bool, default None (matlab style default)
+            Axis grid lines.
+        legend : bool or {'reverse'}
+            Place legend on axis subplots.
+        style : list or dict
+            The matplotlib line style per column.
+        logx : bool or 'sym', default False
+            Use log scaling or symlog scaling on x axis.
+
+        logy : bool or 'sym' default False
+            Use log scaling or symlog scaling on y axis.
+
+        loglog : bool or 'sym', default False
+            Use log scaling or symlog scaling on both x and y axes.
+
+        xticks : sequence
+            Values to use for the xticks.
+        yticks : sequence
+            Values to use for the yticks.
+        xlim : 2-tuple/list
+            Set the x limits of the current axes.
+        ylim : 2-tuple/list
+            Set the y limits of the current axes.
+        xlabel : label, optional
+            Name to use for the xlabel on x-axis. Default uses index name as xlabel, or the
+            x-column name for planar plots.
+
+            .. versionchanged:: 2.0.0
+
+                Now applicable to histograms.
+
+        ylabel : label, optional
+            Name to use for the ylabel on y-axis. Default will show no ylabel, or the
+            y-column name for planar plots.
+
+            .. versionchanged:: 2.0.0
+
+                Now applicable to histograms.
+
+        rot : float, default None
+            Rotation for ticks (xticks for vertical, yticks for horizontal
+            plots).
+        fontsize : float, default None
+            Font size for xticks and yticks.
+        colormap : str or matplotlib colormap object, default None
+            Colormap to select colors from. If string, load colormap with that
+            name from matplotlib.
+        colorbar : bool, optional
+            If True, plot colorbar (only relevant for 'scatter' and 'hexbin'
+            plots).
+        position : float
+            Specify relative alignments for bar plot layout.
+            From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5
+            (center).
+        table : bool, Series or DataFrame, default False
+            If True, draw a table using the data in the DataFrame and the data
+            will be transposed to meet matplotlib's default layout.
+            If a Series or DataFrame is passed, use passed data to draw a
+            table.
+        yerr : DataFrame, Series, array-like, dict and str
+            See :ref:`Plotting with Error Bars <visualization.errorbars>` for
+            detail.
+        xerr : DataFrame, Series, array-like, dict and str
+            Equivalent to yerr.
+        stacked : bool, default False in line and bar plots, and True in area plot
+            If True, create stacked plot.
+        secondary_y : bool or sequence, default False
+            Whether to plot on the secondary y-axis if a list/tuple, which
+            columns to plot on secondary y-axis.
+        mark_right : bool, default True
+            When using a secondary_y axis, automatically mark the column
+            labels with "(right)" in the legend.
+        include_bool : bool, default is False
+            If True, boolean values can be plotted.
+        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
+            Options to pass to matplotlib plotting method.
+
+        Returns
+        -------
+        :class:`matplotlib.axes.Axes` or numpy.ndarray of them
+            If the backend is not the default matplotlib one, the return value
+            will be the object returned by the backend.
+
+        See Also
+        --------
+        matplotlib.pyplot.plot : Plot y versus x as lines and/or markers.
+        DataFrame.hist : Make a histogram.
+        DataFrame.boxplot : Make a box plot.
+        DataFrame.plot.scatter : Make a scatter plot with varying marker
+            point size and color.
+        DataFrame.plot.hexbin : Make a hexagonal binning plot of
+            two variables.
+        DataFrame.plot.kde : Make Kernel Density Estimate plot using
+            Gaussian kernels.
+        DataFrame.plot.area : Make a stacked area plot.
+        DataFrame.plot.bar : Make a bar plot.
+        DataFrame.plot.barh : Make a horizontal bar plot.
+
+        Notes
+        -----
+        - See matplotlib documentation online for more on this subject
+        - If `kind` = 'bar' or 'barh', you can specify relative alignments
+        for bar plot layout by `position` keyword.
+        From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5
+        (center)
+
+        Examples
+        --------
+        For Series:
+
+        .. plot::
+            :context: close-figs
+
+            >>> ser = pd.Series([1, 2, 3, 3])
+            >>> plot = ser.plot(kind="hist", title="My plot")
+
+        For DataFrame:
+
+        .. plot::
+            :context: close-figs
+
+            >>> df = pd.DataFrame(
+            ...     {
+            ...         "length": [1.5, 0.5, 1.2, 0.9, 3],
+            ...         "width": [0.7, 0.2, 0.15, 0.2, 1.1],
+            ...     },
+            ...     index=["pig", "rabbit", "duck", "chicken", "horse"],
+            ... )
+            >>> plot = df.plot(title="DataFrame Plot")
+
+        For SeriesGroupBy:
+
+        .. plot::
+            :context: close-figs
+
+            >>> lst = [-1, -2, -3, 1, 2, 3]
+            >>> ser = pd.Series([1, 2, 2, 4, 6, 6], index=lst)
+            >>> plot = ser.groupby(lambda x: x > 0).plot(title="SeriesGroupBy Plot")
+
+        For DataFrameGroupBy:
+
+        .. plot::
+            :context: close-figs
+
+            >>> df = pd.DataFrame({"col1": [1, 2, 3, 4], "col2": ["A", "B", "A", "B"]})
+            >>> plot = df.groupby("col2").plot(kind="bar", title="DataFrameGroupBy Plot")
+        """
         result = GroupByPlot(self)
         return result
 
