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