#https://datatofish.com/covariance-matrix-python/
import numpy as np
import seaborn as sn
import matplotlib.pyplot as plt

A = [45,37,42,35,39]
B = [38,31,26,28,33]
C = [10,15,17,21,12]

data = np.array([A,B,C])

covMatrix = np.cov(data,bias=False)
print (covMatrix)

sn.heatmap(covMatrix, annot=True, fmt='g')
plt.show()


## Pandas only version
#import pandas as pd
#data = {'A': [45,37,42,35,39],
#        'B': [38,31,26,28,33],
#        'C': [10,15,17,21,12]
#        }
#df = pd.DataFrame(data,columns=['A','B','C'])
#covMatrix = pd.DataFrame.cov(df)
#print (covMatrix)