I have the following Dataframe, which contains, among others, UserID and rank_group as attribute: UserID Col2 Col3 rank_group 0 1 2 3 1 1 1 5 6 1 ... 20 1 8 9 2 21 1 11 12 2 ... 45 1 14 15 3 46 1 17 18 3 47 2 2 3 1 48 2 5 6 1 ... 60 2 8 9 2 61 2 11 12 2 ... 70 2 14 15 3 71 2 17 18 3 The dataframe has got an UserID, and for each user, it has rows with rank_group 1 on the top, followed by the rows with rank_group 2, etc. In other words, rank_group follows a specific progressive order, 1,2,3,4,etc I would like to shuffle the order of the Dataframe's rows such that rank_group follow a random one. For example, if we compute the rank_group from 1 to n for each user, we should obtain after shuffling, the dataset reflecting any permutation from 1 to n. I tried df.sample(frac=1) but it does not take into account the rank_group block but it mixes any row with any row. It is not what I am looking for. In my case, it has to maintain the same order within a fixed rank_group. Also, looked into the np.random.permutation, same issue here. Any help? Continue reading...
