.. 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 .. note:: :class: sphx-glr-download-link-note Click :ref:here  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:: 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 .. 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 :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:Download Python source code: anscombe.py  .. container:: sphx-glr-download sphx-glr-download-jupyter :download:Download Jupyter notebook: anscombe.ipynb  .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery `_