Pandas groupby sum resulting in blanks

Question

I have a pandas dataframe which looks like this:

Sub Code	Date	End Date	Monthly Sub Budget	Monthly Sub Spend	Cum Sub Spend
345	3450	9-1-20	12-1-20	$100	$70
345	3450	10-1-20	12-1-20	$100	$50
345	3450	11-1-20	12-1-20	$100	$80
345	3450	12-1-20	12-1-20	$100	$50
345	3451	12-1-21	1-1-21	$90	$10
981	9810	11-1-20	1-1-21	$80	$50
981	9810	12-1-20	1-1-21	$80	$30

I want to calculate both 'Total Subscription Budget' (the sum of all monthly subscription budgets) and 'Cumulative Subscription Budget' (cumulative sum of monthly subscription budgets) so that the df would look like this:

Sub Code	Date	End Date	Monthly Sub Budget	Monthly Sub Spend	Cum Sub Spend	Tot Sub Budget	Cum Sub Budget
3450	9-1-20	12-1-20	$100	$70	$70	$400	$100
3450	10-1-20	12-1-20	$100	$50	$120	$400	$200
3450	11-1-20	12-1-20	$100	$80	$200	$400	$300
3450	12-1-20	12-1-20	$100	$50	$250	$400	$400
3451	12-1-21	1-1-21	$90	$10	$10	$90	$100
9810	11-1-20	1-1-21	$80	$50	$50	$160	$80
9810	12-1-20	1-1-21	$80	$30	$80	$160	$160

Right now I am using the below code which is working for the cumsum but not for the sum. The Cumulative Sub Budget column is populated correctly, but the Total Sub Budget column is empty.

df['Total Subscription Budget'] = df.groupby('Sub Code')['Monthly Sub Budget'].sum()  
df['Cumulative Subscription Budget'] = df.groupby('Sub Code')['Monthly Sub Budget'].cumsum()

I have found plenty of cases where sum worked and cumsum didn't but haven't seen anyone else have this problem. What should I do to make the .sum() work?

Answer 1

Try with transform

df['Total Subscription Budget'] = df.groupby('Sub Code')['Monthly Sub Budget'].transform('sum')  

Answer 2

Here is a roundabout approach:

#Sum does not work because it doesn't repeat the value for each row.
x = df.groupby('Sub Code')['Monthly Sub Budget'].sum()
x.rename('Total Subscription Budget', inplace=True)

#I think what we can do is join this output to the main table like this
pd.merge(df, x, on='Sub Code')