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