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Learn Calculate Variance with Python | Variance and Standard Deviation
Learning Statistics with Python
course content

Course Content

Learning Statistics with Python

Learning Statistics with Python

1. Basic Concepts
2. Mean, Median and Mode with Python
3. Variance and Standard Deviation
4. Covariance vs Correlation
5. Confidence Interval
6. Statistical Testing

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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).

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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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