Python ProgrammingPython Programming

How to measure Variance and Standard Deviation for DataFrame columns in Pandas?

Measure Variance and Standard Deviation:

import pandas as pd

df = pd.DataFrame([[10, 20, 30, 40], [7, 14, 21, 28], [55, 15, 8, 12],
                   [15, 14, 1, 8], [7, 1, 1, 8], [5, 4, 9, 2]],
                  columns=['Apple', 'Orange', 'Banana', 'Pear'],
                  index=['Basket1', 'Basket2', 'Basket3', 'Basket4',
                         'Basket5', 'Basket6'])

print("\n----------- Calculate Mean -----------\n")
print(df.mean())

print("\n----------- Calculate Median -----------\n")
print(df.median())

print("\n----------- Calculate Mode -----------\n")
print(df.mode())


C:\pandas>python example.py
 
----------- Measure Variance -----------
 
Apple     367.900000
Orange     52.666667
Banana    134.266667
Pear      211.866667
dtype: float64
 
----------- Standard Deviation -----------
 
Apple     19.180719
Orange     7.257180
Banana    11.587349
Pear      14.555640
dtype: float64
 
C:\pandas>