This is obviously simple, but as a numpy newbe I\'m getting stuck.
I have a CSV file that contains 3 columns, the State, the Office ID, and the Sales for that office
df = pd.DataFrame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3,
'office_id': list(range(1, 7)) * 2,
'sales': [np.random.randint(100000, 999999)
for _ in range(12)]})
grouped = df.groupby(['state', 'office_id'])
100*grouped.sum()/df[["state","sales"]].groupby('state').sum()
Returns:
sales
state office_id
AZ 2 54.587910
4 33.009225
6 12.402865
CA 1 32.046582
3 44.937684
5 23.015735
CO 1 21.099989
3 31.848658
5 47.051353
WA 2 43.882790
4 10.265275
6 45.851935