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pythonpandaspermutation

Permutation of a number of rows of a dataframe using pandas

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

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