Python - Calculate the variance of a column in a Pandas DataFrame

To calculate the variance of column values, use the var() method. At first, import the required Pandas library −

import pandas as pd

Create a DataFrame with two columns −

dataFrame1 = pd.DataFrame(    { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'],       "Units": [100, 150, 110, 80, 110, 90] } ) 

Finding Variance of "Units" column values using var() function −

print"Variance of Units column from DataFrame1 = ",dataFrame1['Units'].var()

In the same way, we have calculated the Variance from the 2^nd DataFrame.

Example

Following is the complete code −

import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } ) print"DataFrame1 ...\n",dataFrame1 # Finding Variance of "Units" column values print"Variance of Units column from DataFrame1 = ",dataFrame1['Units'].var() # Create DataFrame2 dataFrame2 = pd.DataFrame( { "Product": ['TV', 'PenDrive', 'HeadPhone', 'EarPhone', 'HDD', 'SSD'], "Price": [8000, 500, 3000, 1500, 3000, 4000] } ) print"\nDataFrame2 ...\n",dataFrame2 # Finding Variance of "Price" column values print"Variance of Price column from DataFrame2 = ",dataFrame2['Price'].var()

Output

This will produce the following output −

DataFrame1 ...        Car   Units 0      BMW    100 1    Lexus    150 2     Audi    110 3    Tesla     80 4  Bentley    110 5   Jaguar     90 Variance of Units column from DataFrame1 = 586.666666667 DataFrame2 ...     Price Product 0   8000 TV 1   500 PenDrive 2   3000 HeadPhone 3   1500 EarPhone 4   3000 HDD 5   4000 SSD Variance of Price column from DataFrame2 = 6766666.66667