numpy version

[biopzhang]

I found the code useful. I rewrote the function using 2D numpy array as input in my use case. I'm posting it here if it's of any help to others or as an addition to your code.

import numpy as np
import pandas as pd

def qnorm_np(arr):
    sorted_arr = arr.astype(float)
    sorted_arr.sort(axis=0)
    rank = sorted_arr.mean(axis=1)
    for col in range(arr.shape[1]):
        t = np.searchsorted(np.sort(arr[:, col]), arr[:,col])
        sorted_arr[:,col] = rank[t]
    return sorted_arr

#Test
df_input =  pd.DataFrame({'C1': {'A': 5, 'B': 2, 'C': 3, 'D': 4},
                   'C2': {'A': 4, 'B': 1, 'C': 4, 'D': 2},
                   'C3': {'A': 3, 'B': 4, 'C': 6, 'D': 8}})
arr_norm = qnorm_np(df_input.values)

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