Python：如何在 Python 中为组内的分类变量分配等级

Question

Given I have a dataset containing only the first two columns, how do I create another column using Python which will contain the rank based on these ranges for each group separately. My desired output would look like this -

id	range	rank
1	10-20	2
1	20-30	3
1	5-10	1
2	20-30	2
2	10-20	1
2
3	10-20	2
3	5-10	1
3	20-30	3
3	30+	4

NOTE - These are the only 4 ranges [5-10, 10-20, 20-30, 30+] that can belong to any id at max. There can be blanks as well For example as given in the reproducible example, if for id 2 there are two ranges 10-20 and 20-30 the corresponding to 10-20 the rank will be 1 and corresponding to 20-30 the rank will be 2. I have checked that df.groupby can be used but I am not being able to figure out how in this case.

Answer 1

Convert your range column to a category dtype before apply rank :

df['range'] = df['range'].astype(pd.CategoricalDtype(
                  ['5-10', '10-20', '20-30', '30+'], ordered=True))

df['rank'] = df.groupby('id')['range'].apply(lambda x: x.rank())

>>> df
   id  range  rank
0   1  10-20   2.0
1   1  20-30   3.0
2   1   5-10   1.0
3   2  20-30   2.0
4   2  10-20   1.0
5   2    NaN   NaN
6   3  10-20   2.0
7   3   5-10   1.0
8   3  20-30   3.0
9   3    30+   4.0