Course Content
Learning Statistics with Python
Learning Statistics with Python
2. Mean, Median and Mode with Python
4. Covariance vs Correlation
Calculate Variance with Python
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).
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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SectionΒ 3. ChapterΒ 3