Conditional Numerical Formatting for Datatable (Some Rows Not Others)

Is there a way to apply conditional numerical formatting to a datatable so that it affects some rows but not others?

I have a datatable created from a pandas dataframe where the first 20 or so rows are money, but the last 10 rows are integers. I can easily format the entire table as money with:

columns = [{'name': i, 'id': i, 'type':'numeric','format':} for i in table.columns]

But I really only want it to format the first 20 rows as “money,” leaving the last 10 or so rows as plain numbers.

I know I can fudge this by changing the dtypes of the rows that I don’t want formatted (e.g., if I change the last 10 rows to strings, those rows won’t be formatted by, but changing the dtype of some rows impacts the dtype of the entire column (because of the mixed dtypes). I’d prefer to avoid this

I was hoping there was a better way to accomplish this using conditional formatting. Any suggestions?