# Kurtosis Function In Pandas

## Overview:

• Kurtosis is one of the two measures that quantify shape of of a distribution. The another measure is skewness.
• Kurtosis describes the peakedness of the distribution.
• If the distribution is tall and thin it is called a leptokurtic distribution. Values in a leptokurtic distribution are near the mean or at the extremes.
• A flat distribution where the values are moderately spread out (i.e., unlike leptokurtic) is called platykurtic distribution.
• A distribution whose shape is in between a leptokurtic distribution and a platykurtic distribution is called a mesokurtic distribution. A mesokurtic distribution looks more close to a normal distribution.

## Kurtosis function in pandas:

• The pandas DataFrame has a computing method kurtosis() which computes the kurtosis for a set of values across a specific axis (i.e., a row or a column).
• The pandas library function kurtosis() computes the Fisher's Kurtosis which is obtained by subtracting the Pearson's Kurtosis by three. With Fisher's Kurtosis, definition a normal distribution has a kurtosis of 0.

## Example:

 import pandas as pd import numpy as np   dataMatrix = [(65,75,74,73,95,76,62,100),               (101,102,103,107,157,160,191,192)];         dataFrame = pd.DataFrame(data=dataMatrix); kurt = dataFrame.kurt(axis=1); print("Data:"); print(dataFrame); print("Kurtosis:"); print(kurt);   dataMatrix = [(70,90,90,100,120,120,100,121,125,115,112),               (58.22,39.33,-30.44,36.77,20.80,-73.95,-39.99,91.03,-138.01,-20,None)];               dataFrame = pd.DataFrame(data=dataMatrix); kurt = dataFrame.kurt(axis=1); print("Data:"); print(dataFrame); print("Kurtosis:"); print(kurt);

## Output:

 Data:      0    1    2    3    4    5    6    7 0   65   75   74   73   95   76   62  100 1  101  102  103  107  157  160  191  192 Kurtosis: 0   -0.246357 1   -2.044655 dtype: float64 Data:       0      1      2       3      4       5       6       7       8    9      10 0  70.00  90.00  90.00  100.00  120.0  120.00  100.00  121.00  125.00  115  112.0 1  58.22  39.33 -30.44   36.77   20.8  -73.95  -39.99   91.03 -138.01  -20    NaN Kurtosis: 0    0.057451 1    0.067184 dtype: float64