One option is with [pivot_longer](https://pyjanitor-devs.github.io/pyjanitor/api/functions/#janitor.functions.pivot.pivot_longer) from [pyjanitor](https://pyjanitor-devs.github.io/pyjanitor/) - in this case we use the special placeholder `.value` to identify the parts of the column that we want to remain as headers, while the rest get collated into a new column :
```py # pip install pyjanitor import pandas as pd import janitor
(df .pivot_longer( index = [slice('Start', 'Type'), slice('Re', 'Set3')], names_to = ("Range", ".value"), names_sep = " ") )
Start Date End Area Final Type Re Set Set2 Set3 Range Stat Stat1 0 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC 0 0 0 0 Middle 226 0 1 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA 0 0 0 0 Middle 130 0 2 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC 0 0 0 0 Low 20 0 3 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA 0 0 0 0 Low 50 0 4 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC 0 0 0 0 High 10 0 5 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA 0 0 0 0 High 0 0 ```

One option is with [pivot_longer](https://pyjanitor-devs.github.io/pyjanitor/api/functions/#janitor.functions.pivot.pivot_longer) from [pyjanitor](https://pyjanitor-devs.github.io/pyjanitor/) - in this case we use the special placeholder `.value` to identify the parts of the column that we want to remain as headers, while the rest get collated into a new column :
```py # pip install pyjanitor import pandas as pd import janitor
(df .pivot_longer( index = slice('Start', 'Type'), names_to = ("Range", ".value"), names_sep = " ") ) Start Date End Area Final Type Range Stat Stat1 0 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC Middle 226 0 1 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA Middle 130 0 2 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC Low 20 0 3 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA Low 50 0 4 8/1/2013 9/1/2013 10/1/2013 NY 3/1/2023 CC High 10 0 5 8/1/2013 9/1/2013 10/1/2013 CA 3/1/2023 AA High 0 0 ```