It's common to use a datetime64[ns] df.index in Pandas when dealing with timeseries.
In such case our API should just be:

buffer.dataframe(df, table_name="some_name")

This means changing the default logic of the at argument to also accept two new singleton types:

buffer.dataframe(df, ..., at=Server) # timestamps are set by the server -- the current default. buffer.dataframe(df, ..., at=Index) # Use the index.

The new behaviour for the at=None default would be to:

• Use at=Index logic if the index column is a datetime64,
• or use at=Server logic if the index is any other type.

Whilst technically a breaking change, the feature change is minor and is very unlikely to affect any of our users, thus this feature will not require a new major software release number.