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

.. only:: html

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

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

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

.. _sphx_glr_gallery_statistics_histogram_features.py:


==============================================
Some features of the histogram (hist) function
==============================================

In addition to the basic histogram, this demo shows a few optional features:

* Setting the number of data bins.
* The *density* parameter, which normalizes bin heights so that the integral of
  the histogram is 1. The resulting histogram is an approximation of the
  probability density function.

Selecting different bin counts and sizes can significantly affect the shape
of a histogram. The Astropy docs have a great section_ on how to select these
parameters.

.. _section: http://docs.astropy.org/en/stable/visualization/histogram.html

.. GENERATED FROM PYTHON SOURCE LINES 19-49

.. code-block:: default


    import numpy as np
    import matplotlib.pyplot as plt

    np.random.seed(19680801)

    # example data
    mu = 100  # mean of distribution
    sigma = 15  # standard deviation of distribution
    x = mu + sigma * np.random.randn(437)

    num_bins = 50

    fig, ax = plt.subplots()

    # the histogram of the data
    n, bins, patches = ax.hist(x, num_bins, density=True)

    # add a 'best fit' line
    y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *
         np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
    ax.plot(bins, y, '--')
    ax.set_xlabel('Smarts')
    ax.set_ylabel('Probability density')
    ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')

    # Tweak spacing to prevent clipping of ylabel
    fig.tight_layout()
    plt.show()




.. image:: /gallery/statistics/images/sphx_glr_histogram_features_001.png
    :alt: Histogram of IQ: $\mu=100$, $\sigma=15$
    :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 50-59

.. admonition:: References

   The use of the following functions, methods, classes and modules is shown
   in this example:

   - `matplotlib.axes.Axes.hist` / `matplotlib.pyplot.hist`
   - `matplotlib.axes.Axes.set_title`
   - `matplotlib.axes.Axes.set_xlabel`
   - `matplotlib.axes.Axes.set_ylabel`


.. _sphx_glr_download_gallery_statistics_histogram_features.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: histogram_features.py <histogram_features.py>`



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

     :download:`Download Jupyter notebook: histogram_features.ipynb <histogram_features.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>`_