Pyhon - Pandas, is it possibleto group rows where a column cell equals a specific value?

Question

I have two rows that look like

CustomerID, CustomerName, ValA, ValB, ValC, Vald
1899, CustomerBlue, 2, 5, 8, 9
1899B, CustomerBlue, 3, 6, 7, 8

I want to combine the rows to become;

1899, CustomerBlue, 5, 11, 15, 17

I started with this;

df.groupby(['CustomerName'], as_index=False).agg('sum')

But obviously that won't work because two columns are strings. Is there a way to replace the first two cells with what I want, and sum the rest?

Does this answer your question? [python pandas: applying different aggregate functions to different columns](https://stackoverflow.com/questions/32374620/python-pandas-applying-different-aggregate-functions-to-different-columns) — ljmc, Jan 06 '23 at 21:04

score 0 · Accepted Answer · answered Jan 06 '23 at 21:08

0

You can use groupby_agg with a dict mapping. Unfortunately, there is no default function to apply. You have to enumerate all columns...

>>> (df.groupby('CustomerName', as_index=False)
       .agg({'CustomerID': 'first', 'ValA': 'sum', 'ValB': 'sum',
             'ValC': 'sum', 'Vald': 'sum'}))

   CustomerName CustomerID  ValA  ValB  ValC  Vald
0  CustomerBlue       1899     5    11    15    17

answered Jan 06 '23 at 21:08

Corralien

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Close. I used this. https://www.statology.org/pandas-combine-rows-with-same-column-value/ – Jan 06 '23 at 21:17
This is the same method :-) – Corralien Jan 06 '23 at 21:18
It is - slightly tweaked. It's why I accepted your answer. Thanks! – Jan 06 '23 at 21:28

Pyhon - Pandas, is it possibleto group rows where a column cell equals a specific value?

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