feature request: allow NaN handling to be specified per column in read_csv()
Setting na_values = [], keep_default_na = False seems to be the way to go to read data with string columns. (The default behaviour is to stay according to a comments in issue #15669.) However, if the data also contains number columns the user may want to process NaNs is those columns, for example:
```python
import pandas
import io
pandas.read_csv(io.StringIO("""col1,col2
1.23,NA
NA,NB
"""), dtype=str, na_values=[], keep_default_na=False)
```
```
   | col1 | col2
-- | ---- | ----
 0 | 1.23 | NA
 1 | NA   | NB
```
The parameters should be extended so that one can specify the NaN treatment for each column, or better for subsets of columns. I see that @HHest also made this suggesting in a comment in issue #15669.