Learn Calculate Variance with Python | Variance and Standard Deviation

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Calculating Variance with NumPy

In numpy, pass the sequence of values (such as a column from the dataset) into the np.var() function, for example: np.var(df['work_year']).

Calculating Variance with pandas

In pandas, apply the .var() method directly to the column, like this: df['work_year'].var().

Both methods produce similar results, with slight differences due to the use of different denominators: N in numpy (population variance) and N-1 in pandas (sample variance).


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import pandas as pd
import numpy as np

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a849660e-ddfa-4033-80a6-94a1b7772e23/update/ds_salaries_statistics', index_col = 0)

# Calculate the variance using the function from the NumPy library
var_1 = np.var(df['salary_in_usd'])
# Calculate the variance using the function from the pandas library
var_2 = df['salary_in_usd'].var()

print('The variace using NumPy library is', var_1)
print('The variace using pandas library is', var_2)

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