parameters: (self, x=None, y=None, **kwds)
return_statement: return self(kind='bar', x=x, y=y, **kwds)
docstring: 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 : 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 : 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)
docstring_summary: Vertical bar plot.
docstring_tokens: Vertical bar plot .
function: def bar(self, x=None, y=None, **kwds):
          """
          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 : 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 : 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)
function_tokens: def bar ( self , x = None , y = None , * * kwds ) : return self ( kind = 'bar' , x = x , y = y , * * kwds )