from scipy.io import loadmat NYCdiseases = loadmat('NYCDiseases.mat') # loading a matlab file chickenpox = np.sum(NYCdiseases['chickenPox'],axis=0) mumps = np.sum(NYCdiseases['mumps'],axis=0) measles = np.sum(NYCdiseases['measles'],axis=0)In the snippet above we read the data from a Matlab file and summed the number of cases for each month. We are now ready to visualize our values using the function

*stackplot*:

import matplotlib.patches as mpatches import matplotlib.pyplot as plt plt.stackplot(arange(12)+1, [chickenpox, mumps, measles], colors=['#377EB8','#55BA87','#7E1137']) plt.xlim(1,12) # creating the legend manually plt.legend([mpatches.Patch(color='#377EB8'), mpatches.Patch(color='#55BA87'), mpatches.Patch(color='#7E1137')], ['chickenpox','mumps','measles']) plt.show()The result is as follows:

We note that the highest number of cases happens between January and Jul, also we see that measles cases are more common than mumps and chicken pox cases.