Making wide-to-long transformation based on the values of a column

I need to make a wide-to-long transformation using Pandas.

Considering the given dataframe input :

import pandas as pd
df = pd.DataFrame({'Id': ['AA', 'BB', 'CC'], 'Value': [4, 2, 3]})

>>> df

I’m looking for a way to have this kind of output :

I tried to make a list (from 1 to the value of the second column) but I got the error below :

df['pos'] = df.apply(list(range(1, df['Value'])))
df.explode('pos')

TypeError: ‘Series’ object cannot be interpreted as an integer

Do you know you have to fix that or any other suggestions to make this transformation work ?

>Solution :

You can turn Value column into list then explode

out = (df.assign(Value=df['Value'].apply(lambda x: range(1, x+1)))
       .explode('Value', ignore_index=True))

print(out)

   Id Value
0  AA     1
1  AA     2
2  AA     3
3  AA     4
4  BB     1
5  BB     2
6  CC     1
7  CC     2
8  CC     3