I have a pandas dataframe column that contains a different numbers and each number has a different frequencies. there are 532 to unique value in column. and totally 59000 value are there.
0 135715
1 138775
2 134915
3 134335
4 134555
5 144995
6 136515
7 135185
8 145555
9 135245
...
How can i replace these values somehow corresponding to values in column that starts from 1 to 532. something like this.
0 1
1 2
2 3
3 4
4 5
5 5
6 5
7 6
8 7
9 1
10 1
11 4
...
I tried np.where() with np.arange() but it raise error.
