group by, order and detect change between rows

I have a dataframe. I would like group by col1, order by col3 and detect changes from row to row in col2.

Here is my example:

import pandas as pdimport datetimemy_df = pd.DataFrame({'col1': ['a', 'a', 'a', 'b', 'b', 'b'],'col2': [2, 2, 3, 5, 5, 5],'col3': [datetime.date(2023, 2, 1),                               datetime.date(2023, 3, 1),                               datetime.date(2023, 4, 1),                               datetime.date(2023, 2, 1),                               datetime.date(2023, 3, 1),                               datetime.date(2023, 4, 1)]})my_df.sort_values(by=['col3'], inplace=True)my_df_temp = my_df.groupby('col1')['col2'].apply(    lambda x: x != x.shift(1)).reset_index(name='col2_change')

Here is how my dataframe looks:

  col1  col2        col30    a     2  2023-02-011    a     2  2023-03-012    a     3  2023-04-013    b     5  2023-02-014    b     5  2023-03-015    b     5  2023-04-01

Here is how result looks like:

  col1  level_1  col2_change0    a        0         True1    a        1        False2    a        2         True3    b        3         True4    b        4        False5    b        5        False

This is clearly incorrect. What am I doing wrong?