Is there a way in pandas to import NA fields as a string rather than NaN?
Use the pandas.read_csv() options:

d = pandas.read_csv('foo.csv', keep_default_na=False)



  na_values : scalar, str, list-like, or dict, default None
  
  Additional strings to recognize as NA/NaN. If dict passed, specific >per->column NA values. By default the following values are interpreted as >NaN: ‘’, ‘#N/A’, ‘#N/A N/A’, ‘#NA’, ‘-1.#IND’, ‘-1.#QNAN’, ‘-NaN’, ‘-nan’, >‘1.#IND’, ‘1.#QNAN’, ‘N/A’, ‘NA’, ‘NULL’, ‘NaN’, ‘n/a’, ‘nan’, ‘null’.
  
  keep_default_na : bool, default True
  
  If na_values are specified and keep_default_na is False the default NaN >values are overridden, otherwise they’re appended to.
  
  from here