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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

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<title>Anscombe’s Quartet — Matplotlib 2.0.2.post4416.dev0+g1df513f documentation</title>

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<h1>Anscombe’s Quartet<a class="headerlink" href="#anscombe-s-quartet" title="Permalink to this headline">¶</a></h1>

Out:

<div class="sphx-glr-script-out highlight-default"><div class="highlight"><pre>mean=7.50, std=1.94, r=0.82

mean=7.50, std=1.94, r=0.82

</pre></div>

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<div class="highlight-python"><div class="highlight"><pre>from __future__ import print_function

"""

Edward Tufte uses this example from Anscombe to show 4 datasets of x

and y that have the same mean, standard deviation, and regression

line, but which are qualitatively different.

matplotlib fun for a rainy day

"""

import matplotlib.pyplot as plt

import numpy as np

x = np.array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5])

y1 = np.array([8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68])

y2 = np.array([9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74])

y3 = np.array([7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73])

x4 = np.array([8, 8, 8, 8, 8, 8, 8, 19, 8, 8, 8])

y4 = np.array([6.58, 5.76, 7.71, 8.84, 8.47, 7.04, 5.25, 12.50, 5.56, 7.91, 6.89])

def fit(x):

return 3 + 0.5*x

xfit = np.array([np.min(x), np.max(x)])

<a href="../../api/_as_gen/matplotlib.pyplot.subplot.html#matplotlib.pyplot.subplot" title="View documentation for matplotlib.pyplot.subplot">plt.subplot</a>(221)

<a href="../../api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot">plt.plot</a>(x, y1, 'ks', xfit, fit(xfit), 'r-', lw=2)

<a href="../../api/axis_api.html#matplotlib.axis" title="View documentation for matplotlib.pyplot.axis">plt.axis</a>([2, 20, 2, 14])

<a href="../../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="View documentation for matplotlib.pyplot.setp">plt.setp</a>(<a href="../../api/_as_gen/matplotlib.pyplot.gca.html#matplotlib.pyplot.gca" title="View documentation for matplotlib.pyplot.gca">plt.gca</a>(), xticklabels=[], yticks=(4, 8, 12), xticks=(0, 10, 20))

<a href="../../api/text_api.html#matplotlib.text" title="View documentation for matplotlib.pyplot.text">plt.text</a>(3, 12, 'I', fontsize=20)

<a href="../../api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot">plt.plot</a>(x, y2, 'ks', xfit, fit(xfit), 'r-', lw=2)

<a href="../../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="View documentation for matplotlib.pyplot.setp">plt.setp</a>(<a href="../../api/_as_gen/matplotlib.pyplot.gca.html#matplotlib.pyplot.gca" title="View documentation for matplotlib.pyplot.gca">plt.gca</a>(), xticklabels=[], yticks=(4, 8, 12), yticklabels=[], xticks=(0, 10, 20))

<a href="../../api/text_api.html#matplotlib.text" title="View documentation for matplotlib.pyplot.text">plt.text</a>(3, 12, 'II', fontsize=20)

<a href="../../api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot">plt.plot</a>(x, y3, 'ks', xfit, fit(xfit), 'r-', lw=2)

<a href="../../api/text_api.html#matplotlib.text" title="View documentation for matplotlib.pyplot.text">plt.text</a>(3, 12, 'III', fontsize=20)

<a href="../../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="View documentation for matplotlib.pyplot.setp">plt.setp</a>(<a href="../../api/_as_gen/matplotlib.pyplot.gca.html#matplotlib.pyplot.gca" title="View documentation for matplotlib.pyplot.gca">plt.gca</a>(), yticks=(4, 8, 12), xticks=(0, 10, 20))

xfit = np.array([np.min(x4), np.max(x4)])

<a href="../../api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot">plt.plot</a>(x4, y4, 'ks', xfit, fit(xfit), 'r-', lw=2)

<a href="../../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="View documentation for matplotlib.pyplot.setp">plt.setp</a>(<a href="../../api/_as_gen/matplotlib.pyplot.gca.html#matplotlib.pyplot.gca" title="View documentation for matplotlib.pyplot.gca">plt.gca</a>(), yticklabels=[], yticks=(4, 8, 12), xticks=(0, 10, 20))

<a href="../../api/text_api.html#matplotlib.text" title="View documentation for matplotlib.pyplot.text">plt.text</a>(3, 12, 'IV', fontsize=20)

# verify the stats

pairs = (x, y1), (x, y2), (x, y3), (x4, y4)

for x, y in pairs:

print('mean=%1.2f, std=%1.2f, r=%1.2f' % (np.mean(y), np.std(y), np.corrcoef(x, y)[0][1]))

<a href="../../api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="View documentation for matplotlib.pyplot.show">plt.show</a>()

</pre></div>

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<a class="reference download internal" href="../../_downloads/anscombe.py" download=""><code class="xref download docutils literal">Download Python source code: anscombe.py</code></a></div>

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