[Python] Pandas groupBy multiple columns and aggregation (group by frequency and then by value)

I have the following data frame: enter image description here enter image description here

***>> gg = pd.DataFrame(
{
"Tool": [1 , 2 , 1 , 2, 2, 2, 1, 2, 1,2],
"Timestamp": ['2022-05-28 05:03:00','2022-05-29 06:07:00','2022-05-28 07:11:00','2022-05-27 11:04:00','2022-05-27 05:43:00','2022-05-25 06:07:00','2022-05-28 11:22:00','2022-05-28 02:00:00','2022-05-26 04:22:00','2022-05-28 09:55:00'],
"Sensor1": [10,11,12,13,6,7,3,11,8,9],
"Sensor2": [5,4,3,3,5,4,3,3,8,2],
"Sensor3": [1,2,3,6,1,2,3,6,4,5],
}
)
>>gg.groupby(['Tool', 'Timestamp'])[['Sensor1', 'Sensor2', 'Sensor3']].mean()***


But I'd like to group by the tool first and secondly group the sensor values by the same day (sensor value is mean value). Thanks

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