Print the standard deviation of Pandas series

In this program, we will find the standard deviation of a Pandas series. Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance.

Syntax

Series.std(axis=None, skipna=True, level=None, ddof=1, numeric_only=None)

Parameters

The std() method accepts several parameters:

• ddof ? Delta Degrees of Freedom (default is 1)
• skipna ? Exclude NaN values (default is True)
• axis ? Not applicable for Series

Example

Let's calculate the standard deviation of a Pandas series using the std() function:

import pandas as pd

series = pd.Series([10, 20, 30, 40, 50])
print("Series:")
print(series)

series_std = series.std()
print("\nStandard Deviation of the series:", series_std)

Series:
0    10
1    20
2    30
3    40
4    50
dtype: int64

Standard Deviation of the series: 15.811388300841896

Working with Missing Values

By default, std() excludes NaN values. Here's how it handles missing data:

import pandas as pd
import numpy as np

series_with_nan = pd.Series([10, 20, np.nan, 40, 50])
print("Series with NaN:")
print(series_with_nan)

std_skip_nan = series_with_nan.std()
std_include_nan = series_with_nan.std(skipna=False)

print(f"\nStandard deviation (skip NaN): {std_skip_nan}")
print(f"Standard deviation (include NaN): {std_include_nan}")

Series with NaN:
0    10.0
1    20.0
2     NaN
3    40.0
4    50.0
dtype: float64

Standard deviation (skip NaN): 18.257418583505537
Standard deviation (include NaN): nan

Comparison with Different ddof Values

The ddof parameter affects the calculation by changing the denominator:

import pandas as pd

data = pd.Series([2, 4, 6, 8, 10])

std_ddof_0 = data.std(ddof=0)  # Population standard deviation
std_ddof_1 = data.std(ddof=1)  # Sample standard deviation (default)

print(f"Data: {data.tolist()}")
print(f"Standard deviation (ddof=0): {std_ddof_0}")
print(f"Standard deviation (ddof=1): {std_ddof_1}")

Data: [2, 4, 6, 8, 10]
Standard deviation (ddof=0): 2.8284271247461903
Standard deviation (ddof=1): 3.1622776601683795

Conclusion

The std() function in Pandas provides an easy way to calculate standard deviation. Use ddof=0 for population standard deviation and ddof=1 (default) for sample standard deviation.