Pandas Series - std() function

The Pandas Series std() function returns the sample standard deviation of the values over the specified axis. The syntax for using this function is mentioned below:

Syntax

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

Parameters

`axis`	`Optional.` Specify {0 or 'index'}. Specify axis for the function to be applied on.
`skipna`	`Optional.` Specify True to exclude NA/null values when computing the result. Default is True.
`level`	`Optional.` Specify level (int or str). If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. A str specifies the level name.
`ddof`	`Optional.` Specify Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.
`numeric_only`	`Optional.` Specify True to include only float, int or boolean data. Default: False

Return Value

Returns scalar or Series if a level is specified.

Example: using std() on a Series

In the example below, the std() function is used to get the sample standard deviation of values of a given series.

import pandas as pd
import numpy as np

idx = pd.MultiIndex.from_arrays([
    ['even', 'even', 'even', 
     'odd', 'odd', 'odd']],
    names=['DataType'])

x = pd.Series([10, 20, 30, 5, 7, 9], 
              name='Numbers', index=idx)

print("The Series contains:")
print(x)

#std of all values in the series
print("\nx.std() returns:")
print(x.std())

#std of all values within given level
print("\nx.std(level='DataType') returns:")
print(x.std(level='DataType'))
print("\nx.std(level=0) returns:")
print(x.std(level=0))

The output of the above code will be:

The Series contains:
DataType
even        10
even        20
even        30
odd          5
odd          7
odd          9
Name: Numbers, dtype: int64

x.std() returns:
9.60728889958036

x.std(level='DataType') returns:
DataType
even    10.0
odd      2.0
Name: Numbers, dtype: float64

x.std(level=0) returns:
DataType
even    10.0
odd      2.0
Name: Numbers, dtype: float64

Example: using std() on selected series in a DataFrame

Similarly, the std() function can be applied on selected series/column of a given DataFrame. Consider the following example.

import pandas as pd
import numpy as np

df = pd.DataFrame({
  "Bonus": [5, 3, 2, 4],
  "Last Salary": [58, 60, 63, 57],
  "Salary": [60, 62, 65, 59]},
  index= ["John", "Marry", "Sam", "Jo"]
)

print("The DataFrame is:")
print(df)

#std of all values of 'Salary' series
print("\ndf['Salary'].std() returns:")
print(df["Salary"].std())

The output of the above code will be:

The DataFrame is:
       Bonus  Last Salary  Salary
John       5           58      60
Marry      3           60      62
Sam        2           63      65
Jo         4           57      59

df['Salary'].std() returns:
2.6457513110645907

❮ Pandas Series - Functions