how to compute descriptive statistics; Skewness and Kurtosis for slected feature from dataset?

Question

I need to find skewness and kurtosis for a selected feature from the data frame correctly in python.

the target( y ) feature is a selected feature i need.

import pandas as pd
import numpy.random as rd
data = pd.read_csv('data4filter2.csv')
columns = ['Development Platform','Language Type','Adjusted Function Points','Resource Level']
y = data['Normalised Work Effort'].values
X = data[list(columns)].values

Answer 1

I guess the normalized data is the 'Normalised Work Effort' column (just because the name? - yes, without further information and to answer the question)

from scipy.stats import skew
from scipy.stats import kurtosis

print(skew(y))
1.4698391946407465
print(kurtosis(y))
0.5414032993205269