Reshaping a Pandas Dataframe to set values ​from rows to columns

Question

My question is about rearranging the df1 dataframe to match df2. I was thinking in filtering by Num followed by pd.concat(). My question is whether there is a more clever way to do it. Thanks in advance!

df1 = pd.DataFrame({"Month": ["2022-07-01","2022-08-01","2022-09-01","2022-10-01"]*3,
                    "Num": [10,10,10,10,20,20,20,20,30,30,30,30],
                    "MB": range(12)}
                   )
df1["Month"] = pd.to_datetime(df1['Month'])

enter image description here

df2 = pd.DataFrame({"Month": ["2022-06-01"]*3,
                    "Num": [10, 20, 30],
                    "MB1": [0,4,8],
                    "MB2": [1,5,9],
                    "MB3": [2,6,10],
                    "MB4": [3,7,11],
                   }
                  )

df2["Month"] = pd.to_datetime(df2['Month'])

enter image description here

Try to filtering by Num and then made a contatenation over all values.