Creating new Dataframe by Indexing Column

Question

I just can't seem to connect the dots on this. I'm trying to do something similar to this question

I have a dataframe that takes the form:

Origination	Orig Balance
Q1	3000
Q1	2000
Q1	4000
Q2	3000
Q2	3000
Q3	1000
Q3	4000
Q3	3000

And I'm trying to create a dataframe that looks like this:

Origination	Orig Balance
Q1	9000
Q2	6000
Q3	8000

I don't want to set the specific parameters, so something like df.loc[df['Origination'] == 'Q1', 'Orig Balance'].sum() wouldn't work for me.

Answer 1

You want to group by Origination first, then take the sum of Orig Balance:

sums = df.groupby('Origination')['Orig Balance'].sum().reset_index()

Output:

>>> sums
  Origination  Orig Balance
0          Q1          9000
1          Q2          6000
2          Q3          8000

Answer 2

What about pandas.DataFrame.groupby?

df.groupby(by=["Origination"]).sum()

Answer 3

Can use aggregate sum

df.groupby('Origination').agg('sum').reset_index()