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# pandas.Series.hist

Series.hist(by=None, ax=None, grid=True, xlabelsize=None, xrot=None, ylabelsize=None, yrot=None, figsize=None, bins=10, backend=None, legend=False, **kwargs)

  Draw histogram of the input series using matplotlib.

  The histogram is computed over the fixed or variable width bins, and drawn using the matplotlib library. This is useful for visualizing the distribution of the data.

  Parameters:
    by object, optional

      If passed, then used to form histograms for separate groups.

    ax matplotlib axis object

      If not passed, uses gca().

    grid bool, default True

      Whether to show axis grid lines.

    xlabelsize int, default None

      If specified changes the x-axis label size.

    xrot float, default None

      Rotation of x axis labels.

    ylabelsize int, default None

      If specified changes the y-axis label size.

    yrot float, default None

      Rotation of y axis labels.

    figsize tuple, default None

      Figure size in inches by default.

    bins int or sequence, default 10

      Number of histogram bins to be used. If an integer is given, bins + 1 bin edges are calculated and returned. If bins is a sequence, gives bin edges, including left edge of first bin and right edge of last bin. In this case, bins is returned unmodified.

    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`.

    legend bool, default False

      Whether to show the legend.

    **kwargs

      To be passed to the actual plotting function.

  Returns:
    matplotlib.axes.Axes

      A histogram plot.

  See also

  `matplotlib.axes.Axes.hist`

    Plot a histogram using matplotlib.

  Examples

  For Series:

      >>> lst = ["a", "a", "a", "b", "b", "b"]
      >>> ser = pd.Series([1, 2, 2, 4, 6, 6], index=lst)
      >>> hist = ser.hist()

  For Groupby:

      >>> lst = ["a", "a", "a", "b", "b", "b"]
      >>> ser = pd.Series([1, 2, 2, 4, 6, 6], index=lst)
      >>> hist = ser.groupby(level=0).hist()