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I have a data frame of this kind:

d = pd.DataFrame({'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

smci
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Ronit Shetty
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  • Please clarify and provide a sample of your expected output. – richardec Mar 10 '22 at 23:29
  • To be clear, you don't want to permute the entire dataframe rows? only the list/Series in the 'Jon' column `['A', 'B', 'C', 'D', 'E']`? So this is just a question about permutations in Python, not permuting rows in pandas? Your title seems to disagree with the question body. – smci Mar 11 '22 at 00:05

1 Answers1

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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
richardec
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