.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/lines_bars_and_markers/stackplot_demo.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_gallery_lines_bars_and_markers_stackplot_demo.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gallery_lines_bars_and_markers_stackplot_demo.py:


===========================
Stackplots and streamgraphs
===========================

.. GENERATED FROM PYTHON SOURCE LINES 8-14

Stackplots
----------

Stackplots draw multiple datasets as vertically stacked areas. This is
useful when the individual data values and additionally their cumulative
value are of interest.

.. GENERATED FROM PYTHON SOURCE LINES 14-40

.. code-block:: default



    import numpy as np
    import matplotlib.pyplot as plt

    # data from United Nations World Population Prospects (Revision 2019)
    # https://population.un.org/wpp/, license: CC BY 3.0 IGO
    year = [1950, 1960, 1970, 1980, 1990, 2000, 2010, 2018]
    population_by_continent = {
        'africa': [228, 284, 365, 477, 631, 814, 1044, 1275],
        'americas': [340, 425, 519, 619, 727, 840, 943, 1006],
        'asia': [1394, 1686, 2120, 2625, 3202, 3714, 4169, 4560],
        'europe': [220, 253, 276, 295, 310, 303, 294, 293],
        'oceania': [12, 15, 19, 22, 26, 31, 36, 39],
    }

    fig, ax = plt.subplots()
    ax.stackplot(year, population_by_continent.values(),
                 labels=population_by_continent.keys())
    ax.legend(loc='upper left')
    ax.set_title('World population')
    ax.set_xlabel('Year')
    ax.set_ylabel('Number of people (millions)')

    plt.show()




.. image:: /gallery/lines_bars_and_markers/images/sphx_glr_stackplot_demo_001.png
    :alt: World population
    :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 41-46

Streamgraphs
------------

Using the *baseline* parameter, you can turn an ordinary stacked area plot
with baseline 0 into a stream graph.

.. GENERATED FROM PYTHON SOURCE LINES 46-72

.. code-block:: default



    # Fixing random state for reproducibility
    np.random.seed(19680801)


    def gaussian_mixture(x, n=5):
        """Return a random mixture of *n* Gaussians, evaluated at positions *x*."""
        def add_random_gaussian(a):
            amplitude = 1 / (.1 + np.random.random())
            dx = x[-1] - x[0]
            x0 = (2 * np.random.random() - .5) * dx
            z = 10 / (.1 + np.random.random()) / dx
            a += amplitude * np.exp(-(z * (x - x0))**2)
        a = np.zeros_like(x)
        for j in range(n):
            add_random_gaussian(a)
        return a


    x = np.linspace(0, 100, 101)
    ys = [gaussian_mixture(x) for _ in range(3)]

    fig, ax = plt.subplots()
    ax.stackplot(x, ys, baseline='wiggle')
    plt.show()



.. image:: /gallery/lines_bars_and_markers/images/sphx_glr_stackplot_demo_002.png
    :alt: stackplot demo
    :class: sphx-glr-single-img






.. _sphx_glr_download_gallery_lines_bars_and_markers_stackplot_demo.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: stackplot_demo.py <stackplot_demo.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: stackplot_demo.ipynb <stackplot_demo.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    Keywords: matplotlib code example, codex, python plot, pyplot
    `Gallery generated by Sphinx-Gallery
    <https://sphinx-gallery.readthedocs.io>`_