I have the following data in my data-frame ID currency cost 1 USD 5 1 CNY 3 2 USD 1 2 CNY 1 The group by of cost is easy by id. But the currency column I want to concatenate in the final result. ID currency cost 1 USD,CNY 8 2 USD,CNY 2 Is it possible to pass a custom function to the aggregate column that does the concatenate, like shown below? df = df.groupby(['id']).agg( currency=('runId', **my-custom-concatenate-function**), revenue=('cost', 'sum') ).reset_index()

pandas data frame concatenate as aggregrate function for group by

I have the following data in my data-frame

The group by of cost is easy by id. But the currency column I want to concatenate in the final result.

ID	currency	cost
1	USD,CNY	8
2	USD,CNY	2

Is it possible to pass a custom function to the aggregate column that does the concatenate, like shown below?

df = df.groupby(['id']).agg(
    currency=('runId', **my-custom-concatenate-function**),
    revenue=('cost', 'sum')
).reset_index()