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

To Add to the answer given by @Andy-Hayden, to do this inplace to the whole frame... not really sure why this works, but it does. There seems to be no control on the order.

    In [97]: A = pd.DataFrame(np.random.randint(0,100,(4,5)), columns=['one','two','three','four','five'])

    In [98]: A
    Out[98]: 
    one  two  three  four  five
    0   22   63     72    46    49
    1   43   30     69    33    25
    2   93   24     21    56    39
    3    3   57     52    11    74

    In [99]: A.values.sort
    Out[99]: 

    In [100]: A
    Out[100]: 
    one  two  three  four  five
    0   22   63     72    46    49
    1   43   30     69    33    25
    2   93   24     21    56    39
    3    3   57     52    11    74

    In [101]: A.values.sort()

    In [102]: A
    Out[102]: 
    one  two  three  four  five
    0   22   46     49    63    72
    1   25   30     33    43    69
    2   21   24     39    56    93
    3    3   11     52    57    74
    In [103]: A = A.iloc[:,::-1]

    In [104]: A
    Out[104]: 
    five  four  three  two  one
    0    72    63     49   46   22
    1    69    43     33   30   25
    2    93    56     39   24   21
    3    74    57     52   11    3

I hope someone can explain the why of this, just happy that it works 8)