Permutation of a number of rows of a dataframe using pandas

March 11, 2022

I have a data frame of this kind

d = {'Job': ['A', 'B', 'C', 'D', 'E'], 'Machine1': [1,3,2,4,3],'Machine2': [2,0,5,1,2]}

For the index 'Job', I need to find all permutations of length 5, basically (5 factorial) permutations. The length of the index may change for a different scenario, so I am not looking for a code specific to 5 jobs only.

Expected output – A,B,C,D,E; A,C,D,E,B; E,D,C,B,A and so on up to 120 such ways. In basic math, it is a permutation expressed as 5P5

>Solution :

I think you’re looking for the built-in function itertools.permutations():

import itertools as it
permutations = list(it.permutations(d['Job']))

Output:

>>> permutations
[('A', 'B', 'C', 'D', 'E'),
 ('A', 'B', 'C', 'E', 'D'),
 ('A', 'B', 'D', 'C', 'E'),
 ('A', 'B', 'D', 'E', 'C'),
 ('A', 'B', 'E', 'C', 'D'),
...

>>> len(permutations)
120