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 2nd 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