DOC: update the pandas.DataFrame.plot.bar docsctring

pandas/plotting/_core.py

@@ -2835,19 +2835,86 @@ def line(self, x=None, y=None, **kwds):
 
     def bar(self, x=None, y=None, **kwds):
         """
-        Vertical bar plot
+        Vertical bar plot.
+
+        A bar plot is a plot that presents categorical data with
+        rectangular bars with lengths proportional to the values that they
+        represent. A bar plot shows comparisons among discrete categories. One
+        axis of the plot shows the specific categories being compared, and the
+        other axis represents a measured value.
 
         Parameters
         ----------
-        x, y : label or position, optional
-            Coordinates for each point.
-        `**kwds` : optional
+        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.
+        **kwds
             Additional keyword arguments are documented in
             :meth:`pandas.DataFrame.plot`.
 
         Returns
         -------
-        axes : :class:`matplotlib.axes.Axes` or numpy.ndarray of them
+        axes : matplotlib.axes.Axes or np.ndarray of them
+            An ndarray is returned with one :class:`matplotlib.axes.Axes`
+            per column when ``subplots=True``.
+
+        See Also
+        --------
+        pandas.DataFrame.plot.barh : Horizontal bar plot.
+        pandas.DataFrame.plot : Make plots of a DataFrame.
+        matplotlib.pyplot.bar : Make a bar plot with matplotlib.
+
+        Examples
+        --------
+        Basic plot.
+
+        .. plot::
+            :context: close-figs
+
+            >>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
+            >>> ax = df.plot.bar(x='lab', y='val', rot=0)
+
+        Plot a whole dataframe to a bar plot. Each column is assigned a
+        distinct color, and each row is nested in a group along the
+        horizontal axis.
+
+        .. plot::
+            :context: close-figs
+
+            >>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
+            >>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
+            >>> index = ['snail', 'pig', 'elephant',
+            ...          'rabbit', 'giraffe', 'coyote', 'horse']
+            >>> df = pd.DataFrame({'speed': speed,
+            ...                    'lifespan': lifespan}, index=index)
+            >>> ax = df.plot.bar(rot=0)
+
+        Instead of nesting, the figure can be split by column with
+        ``subplots=True``. In this case, a :class:`numpy.ndarray` of
+        :class:`matplotlib.axes.Axes` are returned.
+
+        .. plot::
+            :context: close-figs
+
+            >>> axes = df.plot.bar(rot=0, subplots=True)
+            >>> axes[1].legend(loc=2)  # doctest: +SKIP
+
+        Plot a single column.
+
+        .. plot::
+            :context: close-figs
+
+            >>> ax = df.plot.bar(y='speed', rot=0)
+
+        Plot only selected categories for the DataFrame.
+
+        .. plot::
+            :context: close-figs
+
+            >>> ax = df.plot.bar(x='lifespan', rot=0)
         """
         return self(kind='bar', x=x, y=y, **kwds)