.. _pylab_examples-anscombe: pylab_examples example code: anscombe.py ======================================== .. plot:: /home/tcaswell/other_source/matplotlib/doc/mpl_examples/pylab_examples/anscombe.py :: #!/usr/bin/env python 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 """ from pylab import * x = array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5]) y1 = array([8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68]) y2 = array([9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74]) y3 = array([7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73]) x4 = array([8,8,8,8,8,8,8,19,8,8,8]) y4 = 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 = array( [amin(x), amax(x) ] ) subplot(221) plot(x,y1,'ks', xfit, fit(xfit), 'r-', lw=2) axis([2,20,2,14]) setp(gca(), xticklabels=[], yticks=(4,8,12), xticks=(0,10,20)) text(3,12, 'I', fontsize=20) subplot(222) plot(x,y2,'ks', xfit, fit(xfit), 'r-', lw=2) axis([2,20,2,14]) setp(gca(), xticklabels=[], yticks=(4,8,12), yticklabels=[], xticks=(0,10,20)) text(3,12, 'II', fontsize=20) subplot(223) plot(x,y3,'ks', xfit, fit(xfit), 'r-', lw=2) axis([2,20,2,14]) text(3,12, 'III', fontsize=20) setp(gca(), yticks=(4,8,12), xticks=(0,10,20)) subplot(224) xfit = array([amin(x4),amax(x4)]) plot(x4,y4,'ks', xfit, fit(xfit), 'r-', lw=2) axis([2,20,2,14]) setp(gca(), yticklabels=[], yticks=(4,8,12), xticks=(0,10,20)) text(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'%(mean(y), std(y), corrcoef(x,y)[0][1])) show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)