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.

Great Thanks

ReplyDeleteThis comment has been removed by a blog administrator.

ReplyDelete