.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/specialty_plots/anscombe.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_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

.. GENERATED FROM PYTHON SOURCE LINES 14-56

.. code-block:: Python


    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-sg:: /gallery/specialty_plots/images/sphx_glr_anscombe_001.png
   :alt: anscombe
   :srcset: /gallery/specialty_plots/images/sphx_glr_anscombe_001.png, /gallery/specialty_plots/images/sphx_glr_anscombe_001_2_00x.png 2.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 57-65

.. admonition:: References

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

   - `matplotlib.axes.Axes.axline` / `matplotlib.pyplot.axline`
   - `matplotlib.axes.Axes.text` / `matplotlib.pyplot.text`
   - `matplotlib.axes.Axes.tick_params` / matplotlib.pyplot.tick_params`


.. _sphx_glr_download_gallery_specialty_plots_anscombe.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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