How to calculate Rankits with Python?

Question

How can I calculate Rankits with Python?

https://en.wikipedia.org/wiki/Rankit

In particular I want to reproduce the example on Wikipedia: So I search for a function which takes a list [16, 22, 40, 43, 65, 75] and then returns the corresponding rankits: [−1.2672, −0.6418, −0.2016, 0.2016, 0.6418, 1.2672]

Answer 1

observation = [16, 22, 40, 43, 65, 75]
import numpy as np
import scipy.stats
def Q_Q_Prob(data):
    n = len(data)
    prob_level = []
    
    for i in range(1,n+1):
        prob_level.append(np.round((i-0.5)/n,5))
    Standard_normal_quantiles = scipy.stats.norm.ppf(prob_level)
    return Standard_normal_quantiles

print(Q_Q_Prob(observation))

This gives exact result for the example in book name : Applied Multivariate Statistical Analysis (RICHARD A. JOHNSON), However not giving exact values for the mentioned example. Sharing this because this might give you a idea.