Fastest way to sort each row in a pandas dataframe

Question

I need to find the quickest way to sort each row in a dataframe with millions of rows and around a hundred columns.

So something like this:

A   B   C         


        

Answer 1

One could try this approach to preserve the integrity of the df:

import pandas as pd 
import numpy as np

A = pd.DataFrame(np.random.randint(0,100,(4,5)), columns=['one','two','three','four','five']) 
print (A) 
print(type(A))

   one  two  three  four  five
0   85   27     64    50    55
1    3   90     65    22     8
2    0    7     64    66    82
3   58   21     42    27    30

B = A.apply(lambda x: np.sort(x), axis=1, raw=True) 
print(B) 
print(type(B))

   one  two  three  four  five
0   27   50     55    64    85
1    3    8     22    65    90
2    0    7     64    66    82
3   21   27     30    42    58