Import kendal method from scipy.stats.

  Load the sample data set.

  Pass the arguments x and y to the kendal().

#import pandas library

import pandas as pd

#import kendal method from scipy.stats

from scipy.stats import kendalltau

#load sample data

data={‘salary’:[1000,200,300,400

,50,400,300,2000,100,50],

‘age’:[25,26,25,23,30,29,23,23,25,25],

‘rating’:[4,3.24,2.5,2.25,2,2.25,2.5,2.75,

3.2,4.2], ‘bonus’:[2500,1200,900,3000,

1800,1400,850,250,750,1000]}

#create and store the data into a data frame

df=pd.DataFrame(data)

print(“Actual Data frame\n”,df)

#pass the arguments to kendal()

p=kendalltau(df[‘salary’],df[‘age’])

q=kendalltau(df[‘rating’],df[‘bonus’])

#print the results

print(p)

print(q)