.. only:: html

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

        Click :ref:`here <sphx_glr_download_gallery_specialty_plots_anscombe.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_gallery_specialty_plots_anscombe.py:


==================
Anscombe's quartet
==================

`Anscombe's quartet`_ is a group of datasets (x, y) that have the same mean,
standard deviation, and regression line, but which are qualitatively different.

It is often used to illustrate the importance of looking at a set of data
graphically and not only relying on basic statistic properties.

.. _Anscombe's quartet: https://en.wikipedia.org/wiki/Anscombe%27s_quartet


.. code-block:: default


    import matplotlib.pyplot as plt
    import numpy as np

    x = [10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5]
    y1 = [8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68]
    y2 = [9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74]
    y3 = [7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73]
    x4 = [8, 8, 8, 8, 8, 8, 8, 19, 8, 8, 8]
    y4 = [6.58, 5.76, 7.71, 8.84, 8.47, 7.04, 5.25, 12.50, 5.56, 7.91, 6.89]

    datasets = {
        'I': (x, y1),
        'II': (x, y2),
        'III': (x, y3),
        'IV': (x4, y4)
    }

    fig, axs = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(6, 6),
                            gridspec_kw={'wspace': 0.08, 'hspace': 0.08})
    axs[0, 0].set(xlim=(0, 20), ylim=(2, 14))
    axs[0, 0].set(xticks=(0, 10, 20), yticks=(4, 8, 12))

    for ax, (label, (x, y)) in zip(axs.flat, datasets.items()):
        ax.text(0.1, 0.9, label, fontsize=20, transform=ax.transAxes, va='top')
        ax.tick_params(direction='in', top=True, right=True)
        ax.plot(x, y, 'o')

        # linear regression
        p1, p0 = np.polyfit(x, y, deg=1)  # slope, intercept
        ax.axline(xy1=(0, p0), slope=p1, color='r', lw=2)

        # add text box for the statistics
        stats = (f'$\\mu$ = {np.mean(y):.2f}\n'
                 f'$\\sigma$ = {np.std(y):.2f}\n'
                 f'$r$ = {np.corrcoef(x, y)[0][1]:.2f}')
        bbox = dict(boxstyle='round', fc='blanchedalmond', ec='orange', alpha=0.5)
        ax.text(0.95, 0.07, stats, fontsize=9, bbox=bbox,
                transform=ax.transAxes, horizontalalignment='right')

    plt.show()




.. image:: /gallery/specialty_plots/images/sphx_glr_anscombe_001.png
    :alt: anscombe
    :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.axline
    matplotlib.axes.Axes.text
    matplotlib.axes.Axes.tick_params




.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none


    <function _AxesBase.tick_params at 0x7f5f32c96280>




.. _sphx_glr_download_gallery_specialty_plots_anscombe.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: anscombe.py <anscombe.py>`



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

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