Pandas DataFrame column value remapping

Question

Assuming the following DataFrame:

df = pd.DataFrame({'id': [8,16,23,8,23], 'count': [5,8,7,1,2]}, columns=['id', 'count'])

   id  count
0   8      5
1  16      8
2  23      7
3   8      1
4  23      2

...is there some Pandas magic that allows me to remap the ids so that the ids become sequential? Looking for a result like:

   id  count
0   0      5
1   1      8
2   2      7
3   0      1
4   2      2

where the original ids [8,16,23] were remapped to [0,1,2]

Note: the remapping doesn't have to maintain original order of ids. For example, the following remapping would also be fine: [8,16,23] -> [2,0,1], but the id space after remapping should be contiguous.

I'm currently using a for loop and a dict to keep track of the remapping, but it feels like Pandas might have a better solution.

Answer 1

use factorize:

>>> df
   id  count
0   8      5
1  16      8
2  23      7
3   8      1
4  23      2
>>> df['id'] = pd.factorize(df['id'])[0]
>>> df
   id  count
0   0      5
1   1      8
2   2      7
3   0      1
4   2      2