Sum values in a column based on two criteria

Question

I have this dataframe:

data = pd.DataFrame({
    'Date': ['2000-01','2000-01', '2000-01','2000-02','2000-03', '2000-03', '2099-01'],
    'Value': [10, 30, 2, 3, 40, 50, 999],
    'Name': ['Peter', 'Peter', 'Jessica','Jessica', 'Will', 'Will', 'Peter']
    })


      Date  Value     Name
0  2000-01     10    Peter
1  2000-01     30    Peter
2  2000-01      2  Jessica
3  2000-02      3  Jessica
4  2000-02     40     Will
5  2000-03     50     Will
6  2099-01    999    Peter

I want to sum the values from Value based on Date and Name such that the results will be below. Here you can see that for Peter and dates 2000-01, there are two values of 10 and 30, where the sum is 40, such that it is added in the first row of Sum. In contrast, Jessica only have one value per month (as can be seen in 2000-01 and 2000-02 with values 2 and 3), such that those two rows will not be summed.

      Date  Value     Name  Sum
0  2000-01     10    Peter   40
1  2000-01     30    Peter   40
2  2000-01      2  Jessica    2
3  2000-02      3  Jessica    3
4  2000-02     40     Will   40
5  2000-03     50     Will   50
6  2099-01    999    Peter  999

How can I sum values based on two criteria as seen above? I only know of pd.pivot_table(), but that will add new columns to the right based on unique values in a column rather downwards.

`data["Sum"] = data.groupby(["Date", "Name"]).transform('sum')` ? — Rakesh, May 16 '19 at 13:01
Need `data["Sum"] = data.groupby(["Date", "Name"])['Value'].transform('sum')` — jezrael, May 16 '19 at 13:02

Sum values in a column based on two criteria

0 Answers0