Pandas How To Uncategorized How to calculate kurtosis in Pandas

How to calculate kurtosis in Pandas

Here’s how to calculate kurtosis in Pandas.
how to calculate kurtosis in Pandas.

How to calculate kurtosis in Pandas

To calculate a Kurtosis in Pandas just use a Kurt method which Pandas is offering to you.

import pandas as pd

my_df = pd.DataFrame({"my_column1": ['9', '2', '3', '5'],
                    "my_column2": ['3', '7', '6', '4'],
                    "my_column3": ['4', '8', '8', '8']})

print(f'The kurtosis of columns:\n{my_df.kurtosis()}')

The kurtosis of columns:
my_column1    0.757656
my_column2   -3.300000
my_column3    4.000000
dtype: float64

The kurtosis method calculates the excess kurtosis, which is the kurtosis of a dataset minus the kurtosis of a normal distribution. A positive value of kurtosis indicates that the data has heavier tails than a normal distribution, while a negative value indicates lighter tails.

For more details see the documentation of kurt function.

Tags:

Leave a Reply

Your email address will not be published. Required fields are marked *

Related Post