Suggestion: Option to normalize treatment of missing values

A Dataset from an Excel file will store `None` for any empty cell. In CSV the convention is to not distinguish between `,,` and `,"",` and treat all empty cells as empty strings. It would be nice to add a feature like that in `pandas.read_csv()` where `,,` is treated as `NaN`, but `None` here for symmetry with Excel. I know that toggling the `na_filter` argument in `read_csv()` is one way to govern this in pandas.

Anyways, thanks for the useful tool.