Way to expand rows for range of cell value in Python?

Question

I have a dataset that looks like this.

    data = {'doc_ID':['Monday', 'Tuesday', 'Wednesday'], 'attachmentCount':[3,0,2], 'open':['TRUE','TRUE','FALSE']}
    df = pd.DataFrame(data)
    df

        doc_ID  attachmentCount open
    0   Monday      3           TRUE
    1   Tuesday     0           TRUE
    2   Wednesday   2           FALSE

I want to expand the dataset by inserting a row for every integer between 1 and the max of "attachmentCount". So, it should look something like this:

        doc_ID  attachmentCount   open
   0    Monday         1          TRUE
   1    Monday         2          TRUE
   2    Monday         3          TRUE
   3    Tuesday        0          TRUE
   4    Wednesday      1          FALSE
   5    Wednesday      2          FALSE

I've tried a couple different things that are so wildly incorrect, that they are not worth posting here. Anyone have any suggestions? Thank you.

Answer 1

I don't know pandas, but in pure python, the following code gives the output you need.

a = [[0, 'Monday', 3, True], [1, 'Tuesday', 0, True], [2, 'Wednesday', 2, False]]
[[[x[0],x[1],y,x[3]] for y in set(range(1,x[2]+1)+[x[2]])] for x in a]

Explaining the code:

a is the dataset.

x is each row of the dataset.

Therefore, in the inner List Comprehension , range(1,x[2]+1)+[x[2]]) , is the all the integers from 1 to the attachmentCount and whatever the attachmentCount is. This is needed as the attachmentCount can be lesser than 1, like 0 in your case. This is converted to a set to remove duplicates.

The innermost part merely substitutes the attachmentCount with each element of the newly created set of values.