Pandas - Pivot and Rearrange Table With Multiple Labels in Same Header - pandas

Question

I have an xlsx file with tabs for multiple years of data. Each tab contains a table with many columns and the table is structured like this:
+-----------+-------+-------------------------+----------------------+
| City | State | Number of Drivers, 2019 | Number of Cars, 2019 |
+-----------+-------+-------------------------+----------------------+
| LA | CA | 123 | 10.0 |
| San Diego | CA | 456 | 2345 |
+-----------+-------+-------------------------+----------------------+
I would like to rearrange the table to look like this, and do it for each tab in the xlsx:
+-----------+-------+------+-------------------+---------------+
| City | State | Year | Measure Name | Measure Value |
+-----------+-------+------+-------------------+---------------+
| LA | CA | 2019 | Number of Drivers | 123 |
| San Diego | CA | 2019 | Number of Drivers | 456 |
| LA | CA | 2019 | Number of Cars | 10 |
| San Diego | CA | 2019 | Number of Cars | 2345 |
+-----------+-------+------+-------------------+---------------+
There are a lot of moving pieces to this and has been a little tricky to get the final formatting correct.

Answer 1

We do melt then join with str.split
s=df.melt(['City','State'])
s=s.join(s.variable.str.split(',',expand=True))
Out[120]:
City State variable value 0 1
0 LA CA NumberofDrivers,2019 123.0 NumberofDrivers 2019
1 SanDiego CA NumberofDrivers,2019 456.0 NumberofDrivers 2019
2 LA CA NumberofCars,2019 10.0 NumberofCars 2019
3 SanDiego CA NumberofCars,2019 2345.0 NumberofCars 2019
# if you need change the name adding .rename(columns={}) at the end

Answer 2

This is how I wwas able to apply Yoben's solution to every tab in the xlsx file, append them together and write the full table to a .csv:
sheets_dict = pd.read_excel(r'file.xlsx', sheet_name=None)
full_table = pd.DataFrame()
for name, sheet in sheets_dict.items():
sheet['sheet'] = name
sheet = sheet.melt(['City','State'])
sheet = sheet.join(sheet.variable.str.split(',' , expand=True))
full_table = full_table.append(sheet)
full_table.reset_index(inplace=True, drop=True)
full_table.to_csv('Full Table.csv')