docs: def _update_pandas_kwargs(self,  dtype=False, parse_dates=True, kwargs= {}):
          """ Construct args suitable for pandas read_csv
          :param dtype: If true, create a dtype type map. Otherwise, pass argument value to read_csv
          :param parse_dates: If true, create a list of date/time columns for the parse_dates argument of read_csv
          :param kwargs:
          :return:
          """
  
          from datetime import datetime, time, date
  
          type_map = {
              None: None,
              'string': str,
              'text': str,
              'number': float,
              'integer': int,
              'datetime': datetime,
              'time': time,
              'date': date
  
          }
  
          if dtype is True:
              kwargs['dtype'] = { c['name']:type_map.get(c['datatype'], c['datatype']) for c in self.columns() }
          elif dtype:
              kwargs['dtype'] = dtype
  
          if parse_dates is True:
               date_cols = [ c['name'] for c in self.columns() if c['datatype'] in ('date','datetime','time') ]
               kwargs['parse_dates'] = date_cols or True
          elif parse_dates:
              kwargs['parse_dates'] = parse_dates
  
          kwargs['low_memory'] = False
  
          return kwargs