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

.. only:: html

    .. meta::
        :keywords: codex

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

        :ref:`Go to the end <sphx_glr_download_plot_types_stats_ecdf.py>`
        to download the full example code.

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

.. _sphx_glr_plot_types_stats_ecdf.py:


=======
ecdf(x)
=======
Compute and plot the empirical cumulative distribution function of x.

See `~matplotlib.axes.Axes.ecdf`.

.. GENERATED FROM PYTHON SOURCE LINES 9-23



.. image-sg:: /plot_types/stats/images/sphx_glr_ecdf_001.png
   :alt: ecdf
   :srcset: /plot_types/stats/images/sphx_glr_ecdf_001.png, /plot_types/stats/images/sphx_glr_ecdf_001_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    plt.style.use('_mpl-gallery')

    # make data
    np.random.seed(1)
    x = 4 + np.random.normal(0, 1.5, 200)

    # plot:
    fig, ax = plt.subplots()
    ax.ecdf(x)
    plt.show()


.. _sphx_glr_download_plot_types_stats_ecdf.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

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

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

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: ecdf.py <ecdf.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: ecdf.zip <ecdf.zip>`


.. only:: html

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

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_
