I essentially wish to break down a dataframe by splicing and creating a wide format, but also adding additional logic

here is the data

year    quarter  Date      Location ID  Role    Type    alias   box status
2025    Q1 2025 2025-01-01  NY          aa     Growth   iaa     5       WIP
2025    Q1 2025 2025-01-01  NY          aa     Total    iaa     5       WIP
2025    Q1 2025 2025-01-01  NY          bb     Growth   ibb    0.633259 WIP
2025    Q1 2025 2025-01-01  NY          bb     Total    ibb    0.633259 WIP
2025    Q1 2025 2025-01-01  CA          aa     Total    iaa    0        WIP
2025    Q1 2025 2025-01-01  CA          bb     Total    ibb    0        WIP
2025    Q2 2025 2025-04-01  NY          aa     Growth   iaa    2.298517 WIP
2025    Q2 2025 2025-04-01  NY          aa     Refresh  iaa    0.889888 WIP
2025    Q2 2025 2025-04-01  NY          aa     Total    iaa    3.188404 WIP
2025    Q2 2025 2025-04-01  NY          bb     Growth   ibb    0.546924 WIP
2025    Q2 2025 2025-04-01  NY          bb     Refresh  ibb    0.590793 WIP
2025    Q2 2025 2025-04-01  NY          bb     Total    ibb    1.137717 WIP
2025    Q2 2025 2025-04-01  CA          aa     Growth   iaa    0.732325 WIP
2025    Q2 2025 2025-04-01  CA          aa     Total    iaa    0.732325 WIP
2025    Q2 2025 2025-04-01  CA          bb     Growth   ibb    0.122307 WIP
2025    Q2 2025 2025-04-01  CA          bb     Refresh  ibb    0.093777 WIP
2025    Q2 2025 2025-04-01  CA          bb     Total    ibb    0.216083 WIP

Desired

Location    Type    Role    alias   Q1 2025 Q2 2025
NY          Growth  iaa     aa      5       2.298517
NY          Growth  ibb     bb      0.633259    0.546924
NY          Refresh iaa     aa      0           0.889888
NY          Refresh ibb     bb      0           0.590793
NY          Total   iaa     aa      5           3.188404
NY          Total   ibb     bb      0.633259    1.137717
CA          Growth  iaa     aa      0           0.732325
CA          Growth  ibb     bb      0           0.122307
CA          Refresh iaa     aa      0           0
CA          Refresh ibb     bb      0           0.093777
CA          Total   iaa     aa      0           0.732325
CA          Total   ibb     bb      0           0.216083

Doing

pivot_df = result_df.pivot_table(index=['Location', 'Type', 'Role', 'alias'], 
                          columns='quarter', values='Racks', fill_value=0).reset_index()

Logic:

Creating a pivot table and each location must have Growth Refresh and Total. If there are no values provided for either Growth, Refresh or Total, just input 0. The quarters should be columns

we are showing the growth, refresh and total for each role and alias
and location

However, this keep deleting some of my values.
Any suggestion is appreciated.