How to reset the indices of remaining dataframe values after removing duplicate rows?

Question

I have a dataframe and have removed duplicate rows using .drop_duplicates() method. But the initial index of the rows and still the same.

data = data.drop_duplicates(keep=False, inplace=True)

    id  Name    Designation     DOB          
2   7934    'MILLER'    'CLERK' 7782.0  '23-JAN-82' 1300        10
8   7521    'WARD'  'SALESMAN'  7698.0  '22-FEB-81' 1250    500.0   30
9   7902    'FORD'  'ANALYST'   7566.0  '3-DEC-81'  3000        20
10  7876    'ADAMS' 'CLERK' 7788.0  '12-JAN-83' 1100        20
11  7566    'JONES' 'MANAGER'   7839.0  '2-APR-81'  2975        20
12  7698    'BLAKE' 'MANAGER'   7839.0  '1-MAY-81'  2850        30
17  7839    'KING-WEB'  'PRESIDENT'     '17-NOV-81' 15000       10

I want to re-index all the rows like this:

    id  Name    Designation     DOB          
1   7934    'MILLER'    'CLERK' 7782.0  '23-JAN-82' 1300        10
2   7521    'WARD'  'SALESMAN'  7698.0  '22-FEB-81' 1250    500.0   30
3   7902    'FORD'  'ANALYST'   7566.0  '3-DEC-81'  3000        20
4   7876    'ADAMS' 'CLERK' 7788.0  '12-JAN-83' 1100        20
5   7566    'JONES' 'MANAGER'   7839.0  '2-APR-81'  2975        20
6   7698    'BLAKE' 'MANAGER'   7839.0  '1-MAY-81'  2850        30
7   7839    'KING-WEB'  'PRESIDENT'     '17-NOV-81' 15000       10

Answer 1

data = data.reset_index(drop=True)