Python - Pandas Dataframe Table/Column Structure

Question

1. I Have a table like below:

2. I converted the table as I needed like this:

3. But I want to categorize the values with the column names like this (example of result needed):

Here's my code:

inv_power = inv_power.set_axis(['Timestamp', 'Time', 'INV1','INV2','INV3','INV4','INV5','INV6','INV7','INV8','INV9','INV10', 'INV11','INV12','INV13','INV14','INV15','INV16','INV17','INV18','INV19','INV20'], axis=1) 

inv_power = inv_power.replace('', np.nan).set_index('Timestamp').stack().reset_index(name='AC_Power').drop('level_1', 1)

Answer 1

inv_power['Slot No.']= pd.np.tile(inverter, len(inv_power) // len(inverter)).tolist() + inverter[:len(inv_power)%len(inverter)]

try this... this works