>>> """
=============================================
Discrete distribution as horizontal bar chart
=============================================

Stacked bar charts can be used to visualize discrete distributions.

This example visualizes the result of a survey in which people could rate
their agreement to questions on a five-element scale.

The horizontal stacking is achieved by calling `~.Axes.barh()` for each
category and passing the starting point as the cumulative sum of the
already drawn bars via the parameter ``left``.
"""
... 
... import numpy as np
... import matplotlib.pyplot as plt
... 
... 
... category_names = ['Strongly disagree', 'Disagree',
...                   'Neither agree nor disagree', 'Agree', 'Strongly agree']
... results = {
...     'Question 1': [10, 15, 17, 32, 26],
...     'Question 2': [26, 22, 29, 10, 13],
...     'Question 3': [35, 37, 7, 2, 19],
...     'Question 4': [32, 11, 9, 15, 33],
...     'Question 5': [21, 29, 5, 5, 40],
...     'Question 6': [8, 19, 5, 30, 38]
... }
... 
... 
... def survey(results, category_names):
...     """
    Parameters
    ----------
    results : dict
        A mapping from question labels to a list of answers per category.
        It is assumed all lists contain the same number of entries and that
        it matches the length of *category_names*.
    category_names : list of str
        The category labels.
    """
...     labels = list(results.keys())
...     data = np.array(list(results.values()))
...     data_cum = data.cumsum(axis=1)
...     category_colors = plt.colormaps['RdYlGn'](
...         np.linspace(0.15, 0.85, data.shape[1]))
... 
...     fig, ax = plt.subplots(figsize=(9.2, 5))
...     ax.invert_yaxis()
...     ax.xaxis.set_visible(False)
...     ax.set_xlim(0, np.sum(data, axis=1).max())
... 
...     for i, (colname, color) in enumerate(zip(category_names, category_colors)):
...         widths = data[:, i]
...         starts = data_cum[:, i] - widths
...         rects = ax.barh(labels, widths, left=starts, height=0.5,
...                         label=colname, color=color)
... 
...         r, g, b, _ = color
...         text_color = 'white' if r * g * b < 0.5 else 'darkgrey'
...         ax.bar_label(rects, label_type='center', color=text_color)
...     ax.legend(ncol=len(category_names), bbox_to_anchor=(0, 1),
...               loc='lower left', fontsize='small')
... 
...     return fig, ax
... 
... 
... survey(results, category_names)
... plt.show()
... 
... #############################################################################
... #
... # .. admonition:: References
... #
... #    The use of the following functions, methods, classes and modules is shown
... #    in this example:
... #
... #    - `matplotlib.axes.Axes.barh` / `matplotlib.pyplot.barh`
... #    - `matplotlib.axes.Axes.bar_label` / `matplotlib.pyplot.bar_label`
... #    - `matplotlib.axes.Axes.legend` / `matplotlib.pyplot.legend`
...