Merge pull request #368 from digitaltxtlab/04-comp-stat-solution

Generate Composite Statistics - solution

Author: valentina-s

_episodes/04-files.md

@@ -148,4 +148,40 @@ where the maxima are a bit less regular, but the minima are consistently zero.
 >
 > Then use pyplot to generate average, max, and min for all patients.
 >
+> > ## Solution
+> > ~~~
+> > import glob
+> > import numpy
+> > import matplotlib.pyplot
+> >
+> > filenames = glob.glob('data/inflammation*.csv')
+> > composite_data = numpy.zeros((60,40))
+> >
+> > for f in filenames:
+> >     data = numpy.loadtxt(fname = f, delimiter=',')
+> >     composite_data += data
+> >
+> > composite_data/=len(filenames)
+> >
+> > fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0))
+> >
+> > axes1 = fig.add_subplot(1, 3, 1)
+> > axes2 = fig.add_subplot(1, 3, 2)
+> > axes3 = fig.add_subplot(1, 3, 3)
+> >
+> > axes1.set_ylabel('average')
+> > axes1.plot(numpy.mean(composite_data, axis=0))
+> >
+> > axes2.set_ylabel('max')
+> > axes2.plot(numpy.max(composite_data, axis=0))
+> >
+> > axes3.set_ylabel('min')
+> > axes3.plot(numpy.min(composite_data, axis=0))
+> >
+> > fig.tight_layout()
+> >
+> > matplotlib.pyplot.show()
+> > ~~~
+> > {: .python}
+>{: .solution}
 {: .challenge}