Want to compute rolling mean dynamically ( Loop ) & then sum by month

Question

I am beginner for Python & needs your help.

Want to pickup the mean input values from df1 , apply it to df2 to compute rolling mean on the fly & then sum it up the rolling mean by month in df3 with expected format & then export it to excel.

So far I gathered below given codes , it is working fine but want to export "groupby sum" in desired format to excel. Mean calculation columns in df2 is not needed , presently it is populating in df2 for each value in df1-Master.

sample data in df1 & df2 are attached below , and df3 - expected out put format also attached below.

from datetime import date
import pandas as pd
import numpy as np
df1 = pd.read_excel('E:\Python\My Test.xlsx', 'Master')
df2 = pd.read_excel('E:\Python\My Test.xlsx', 'Data')
df3 = pd.read_excel('E:\Python\My Test.xlsx', 'Result')

for window1 in df1['Mean-1 input Value']:
    df2[f"Mean {window1}"] = df2['Number'].rolling(window=window1).mean()
for window2 in df1['Mean-2 input Value']:
    df2[f"Mean {window2}"] = df2['Number'].rolling(window=window2).mean()

df3 = df2.groupby('Month').sum()
with pd.ExcelWriter('E:\Python\My Test updated.xlsx') as writer:
    df1.to_excel(writer, sheet_name='Master')
    df2.to_excel(writer, sheet_name='Data')
    df3.to_excel(writer, sheet_name='Result')

df1 ( Master sheet imported from excel )

Mean-1 input Value	Mean-1 input Value
2	3
4	5
...	...

df2 ( Data sheet imported from excel )

Date	Month	Number
01-Jan-22	Jan-22	1
02-Jan-22	Jan-22	2
03-Jan-22	Jan-22	3
04-Jan-22	Jan-22	4
05-Jan-22	Jan-22	5
06-Jan-22	Jan-22	6
07-Jan-22	Jan-22	7
08-Jan-22	Jan-22	8
09-Jan-22	Jan-22	9
10-Jan-22	Jan-22	10
01-Feb-22	Feb-22	11
02-Feb-22	Feb-22	12
03-Feb-22	Feb-22	13
04-Feb-22	Feb-22	14
05-Feb-22	Feb-22	15
06-Feb-22	Feb-22	16
07-Feb-22	Feb-22	17
08-Feb-22	Feb-22	18
09-Feb-22	Feb-22	19
10-Feb-22	Feb-22	20
...	...	...

Expected output in df3 & want to export to Result sheet

Mean-1 input Value	Mean-2 input Value	Sum Item	Jan-22	Feb-22	...
2	3	Sum Mean-1	49.5	150	...
2	3	Sum Mean-2	44	145	...
4	5	Sum Mean-1	38.5	140	...
2	3	Sum Mean-2	30.5	130	...
...	...	...	...	...	...