Python Pandas Series kurt() Function

Pandas Series kurt() Function:

Pandas kurtosis: The kurt() method of the Pandas Series gets the unbiased kurtosis over the given axis.

Syntax:

Series.kurt(axis=None, skipna=None, level=None, numeric_only=None)

Parameters

axis: This is optional. It indicates 0 or ‘index’. This is the axis on which the function will be applied.

skipna: This is optional. When computing the result, specify True to exclude NA/null values. The default value is True.

level: This is optional. It indicates the level (int or str). If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. The level name is specified by str.

numeric_only: This is optional. Pass True to include just float, int, or boolean data. False by default

Return Value:

If a level is given, it returns a scalar or a series. The unbiased kurtosis over the given axis is returned by this kurt() method of the Pandas Series.

Pandas Series kurt() Function in Python

Example1

Approach:

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Import numpy module using the import keyword.
import numpy as np

idx = pd.MultiIndex.from_arrays([
    ['rand', 'rand', 'rand', 'rand', 
     'randn', 'randn', 'randn', 'randn']],
    names=['DataType'])

x = pd.Series(np.append(np.random.rand(4),
              np.random.randn(4)), index=idx)

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

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

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

Output:

Example2

Approach:

Import pandas module using the import keyword.
Pass some random key-value pair(dictionary), index list as arguments to the DataFrame() function of the pandas module to create a dataframe.
Store it in a variable.
Print the given dataframe.
Apply kurt() function on the student_marks column of the dataframe to get the kurtosis of all the elements of the student_marks column and print the result.
The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random key-value pair(dictionary), index list as arguments to the 
# DataFrame() function of the pandas module to create a dataframe
# Store it in a variable.
data_frme = pd.DataFrame({
  "student_rollno": [1, 2, 3, 4],
  "student_marks": [80, 35, 25, 90]},
  index= ["virat", "nick" , "jessy", "sindhu"]
)
# Print the given dataframe
print("The given Dataframe:")
print(data_frme)
print()
# Apply kurt() function on the student_marks column of the dataframe to
# get the kurtosis of all the elements of the student_marks column
# and print the result.
print("The kurtosis of all the elements of student_marks column of a dataframe:")
print(data_frme["student_marks"].kurt())

Output:

The given Dataframe:
        student_rollno  student_marks
virat                1             80
nick                 2             35
jessy                3             25
sindhu               4             90

The kurtosis of all the elements of student_marks column of a dataframe:
-5.07072

Pandas Series kurt() Function in Python

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