Sum column values of a group in python dataframe

Asked Apr 19 '20 at 08:52

Active Apr 19 '20 at 09:08

Viewed 38 times

I have created a group that displays the the total number of items in a sale and the amount of receipts that have total number.

e.g.

1 18853
2 9485

There is another column in the dataframe called total that displays the price of every item in a sale.

Looking at the example output of 1 18853, that indicates that there were 18853 transactions with 1 item. How do I get the SUM price of all 18853 single transaction that contains 1 item, and then do this for every transaction size.

--EDIT-- More context

Here is the code that I used to generate the group

items=supermarket.groupby(['Time', 'Receipt']).size().value_counts()
print(items,'\n')
print('The basket size which is most popular is a basket of 1 items. This is responsible for 18853 seperate transactions.\n\n')

Say there are three seperate items in a transaction for a certain time:

[Time]     [Receipt]     [Total]
12:24:32   124395        5.5
12:24:32   124395        6.3
12:24:32   124395        7.2

I want my output to appear as:

[Time]     [Reciept]     [TotalPrice]
12:24:32   124395        19.0

edited Apr 19 '20 at 09:08

asked Apr 19 '20 at 08:52

Keyan H

3

Pleas can you share a more complete example and the expected output? – yatu Apr 19 '20 at 08:53
1

Just updated it – Keyan H Apr 19 '20 at 08:58
`supermarket.groupby(["Time", "Reciept"]).sum().reset_index()` ? – Alexandre B. Apr 19 '20 at 09:00
This doesnt work, it prints out another column from the dataframe except with weird values. – Keyan H Apr 19 '20 at 09:02

Sum column values of a group in python dataframe

0 Answers0