.. only:: html
.. note::
:class: sphx-glr-download-link-note
Click :ref:`here ` to download the full example code
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_gallery_lines_bars_and_markers_horizontal_barchart_distribution.py:
=============================================
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``.
.. code-block:: default
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.get_cmap('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
ax.barh(labels, widths, left=starts, height=0.5,
label=colname, color=color)
xcenters = starts + widths / 2
r, g, b, _ = color
text_color = 'white' if r * g * b < 0.5 else 'darkgrey'
for y, (x, c) in enumerate(zip(xcenters, widths)):
ax.text(x, y, str(int(c)), ha='center', va='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()
.. image:: /gallery/lines_bars_and_markers/images/sphx_glr_horizontal_barchart_distribution_001.png
:class: sphx-glr-single-img
------------
References
""""""""""
The use of the following functions, methods, classes and modules is shown
in this example:
.. code-block:: default
import matplotlib
matplotlib.axes.Axes.barh
matplotlib.pyplot.barh
matplotlib.axes.Axes.text
matplotlib.pyplot.text
matplotlib.axes.Axes.legend
matplotlib.pyplot.legend
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
.. _sphx_glr_download_gallery_lines_bars_and_markers_horizontal_barchart_distribution.py:
.. only :: html
.. container:: sphx-glr-footer
:class: sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: horizontal_barchart_distribution.py `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: horizontal_barchart_distribution.ipynb `
.. only:: html
.. rst-class:: sphx-glr-signature
Keywords: matplotlib code example, codex, python plot, pyplot
`Gallery generated by Sphinx-Gallery
`_