Currently if any column in a table is a MaskedColumn, then all other columns are "upgraded" to be masked as well. This happens on initialization and if any column in an existing table is converted from Column to MaskedColumn. This is entirely a holdover from the original implementation of table using a numpy structured array.

In the current architecture there is really no reason to do this. I suspect the implementation of this would be relatively easy. The main reservation is about stability and breaking code.

The main API changes would be:

• In order to automatically add new columns as MaskedColumn, one would need to supply masked=True when creating the table. Currently this happens if any of the columns are masked.
• Adding a MaskedColumn to an unmasked table would not automatically "upgrade" other columns (this is a good thing to me).

The Table.masked attribute would still reflect if there are any MaskedColumns that have masked elements, so no change there.