tag occurrences of a value multiple times inn column based on dates using pandas [duplicate]

Question

Below is my dataframe:

df = pd.DataFrame({'ID':[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
                   'date': ['2020-12-1', '2020-12-2', '2020-12-3', '2020-12-4', 
                            '2020-12-10', '2020-12-11', '2020-12-12', '2020-12-13', 
                            '2020-12-25', '2020-12-26', '2020-12-27', '2020-12-28'],
                  'name':['a', 'a', 'a', 'a', 'b', 'b', 'b', 'b' , 'a', 'a', 'a', 'a']})

Looks like this:

I want the output with a column added as shown:

The last column adds a unique id for each new occurrence of value 'a' in the column 'name'.

Answer 1

Chain cumsum with shift

df['id2'] = df.name.ne(df.name.shift()).cumsum()
df
Out[456]: 
    ID        date name  id2
0    1   2020-12-1    a    1
1    1   2020-12-2    a    1
2    1   2020-12-3    a    1
3    1   2020-12-4    a    1
4    1  2020-12-10    b    2
5    1  2020-12-11    b    2
6    1  2020-12-12    b    2
7    1  2020-12-13    b    2
8    1  2020-12-25    a    3
9    1  2020-12-26    a    3
10   1  2020-12-27    a    3
11   1  2020-12-28    a    3