Create a new column that starts counting from 0 until the value in another column changes

Question

I have a dataframe df that looks like this:

ID	Months	Borrow_Rank
1	0	1
1	1	1
1	2	1
2	0	1
2	1	1
2	2	1
3	0	2
3	1	2
4	0	1
4	1	1

I want to create a new variable Months_Adjusted that starts counting from 0 for as long as Borrow_Rank remains the same.

ID	Months	Borrow_Rank	Months_Adjusted
1	0	1	0
1	1	1	1
1	2	1	2
2	0	1	3
2	1	1	4
2	2	1	5
3	0	2	0
3	1	2	1
4	0	1	0
4	1	1	1

Thank you all and I apologise if I could have written the question better. This is my first post.

Answer 1

import pandas as pd

df = pd.DataFrame({'Borrow_Rank':[1,1,1,1,1,1,1,2,2,2,2,2,3,3,3,1,1,1]})
selector = (df['Borrow_Rank'] != df['Borrow_Rank'].shift()).cumsum()
df['Months_Adjusted'] = df.groupby(selector).cumcount()

Answer 2

Here is a solution using itertools.groupby -

from itertools import groupby
df['Months_Adjusted'] = pd.concat(
          [pd.Series(range(len(list(g)))) 
           for k, g in groupby(df['Borrow_Rank'])],
ignore_index=True)

Output

   ID  Months  Borrow_Rank  Months_Adjusted
0   1       0            1                0
1   1       1            1                1
2   1       2            1                2
3   2       0            1                3
4   2       1            1                4
5   2       2            1                5
6   3       0            2                0
7   3       1            2                1
8   4       0            1                0
9   4       1            1                1