Write a Python program to quantify the shape of a distribution in a dataframe

Assume, you have a dataframe and the result for quantify shape of a distribution is,

kurtosis is: Column1    -1.526243 Column2     1.948382 dtype: float64 asymmetry distribution - skewness is: Column1    -0.280389 Column2     1.309355 dtype: float64

Solution

To solve this, we will follow the steps given below −

• Define a dataframe

• Apply df.kurt(axis=0) to calculate the shape of distribution,

df.kurt(axis=0)

• Apply df.skew(axis=0) to calculate unbiased skew over axis-0 to find asymmetry distribution,

df.skew(axis=0)

Example

Let’s see the following code to get a better understanding −

import pandas as pd data = {"Column1":[12,34,56,78,90],          "Column2":[23,30,45,50,90]} df = pd.DataFrame(data) print("DataFrame is:\n",df) kurtosis = df.kurt(axis=0) print("kurtosis is:\n",kurtosis) skewness = df.skew(axis=0) print("asymmetry distribution - skewness is:\n",skewness)

Output

DataFrame is:    Column1 Column2 0    12    23 1    34    30 2    56    45 3    78    50 4    90    90 kurtosis is: Column1    -1.526243 Column2     1.948382 dtype: float64 asymmetry distribution - skewness is: Column1    -0.280389 Column2     1.309355 dtype: float64