Series.std() - Pandas Series

The Series.std() function in pandas is used to compute the standard deviation of a given series. The standard deviation is a measure of the spread or variability of the data.

Syntax

The syntax for using the Series.std() function is as follows:

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

Here,

• axis: int or str, optional. Axis along which the standard deviation is computed. Default is None, which computes the standard deviation of the flattened dataset.
• skipna: bool, optional. Exclude NA/null values from the computation. Default is True.
• level: int or level name, optional. If the axis is a MultiIndex, compute the standard deviation across a particular level.
• ddof: int, optional. Degrees of freedom used in the computation. The default value is 1.
• numeric_only: bool, optional. Include only int64, float64, or boolean data. The default is None.
• **kwargs: Additional keyword arguments.

Example

Let's create a pandas series and then use the Series.std() function to compute the standard deviation.

import pandas as pd

data = pd.Series([1, 2, 3, 4, 5])

std = data.std()

print("Standard deviation:", std)

Output:

Standard deviation: 1.58113883008

In this example, we create a pandas series data with 5 integers. We then apply the Series.std() function to calculate the standard deviation of the series.

Explanation

The Series.std() function calculates the standard deviation of a given series. If the skipna option is set to True, it excludes any missing values from the computation. By default, the ddof parameter is set to 1, so the denominator in the calculation is n-1, where n is the total number of values in the series.

Use

The Series.std() function is used to calculate the standard deviation of a given series. It is useful for analyzing the variability or spread of data. It is often used in combination with other statistical functions to gain insights into the data.

Important Points

• Series.std() is used to calculate the standard deviation of a given series.
• The skipna option can be set to exclude missing values from the computation.
• The ddof parameter can be used to adjust the calculation for finite populations.

Summary

In this tutorial, we learned about the Series.std() function in pandas. We looked at its syntax, parameters, and examples of how to use it to calculate the standard deviation of a series. The standard deviation is an important statistical measure that can help us gain insights into the variability of the data.