code: def convert_json_field_to_pandas_type(field):
      
      typ = field['type']
      if typ == 'string':
          return 'object'
      elif typ == 'integer':
          return 'int64'
      elif typ == 'number':
          return 'float64'
      elif typ == 'boolean':
          return 'bool'
      elif typ == 'duration':
          return 'timedelta64'
      elif typ == 'datetime':
          if field.get('tz'):
              return 'datetime64[ns, {tz}]'.format(tz=field['tz'])
          else:
              return 'datetime64[ns]'
      elif typ == 'any':
          if 'constraints' in field and 'ordered' in field:
              return CategoricalDtype(categories=field['constraints']['enum'],
                                      ordered=field['ordered'])
          else:
              return 'object'
  
      raise ValueError("Unsupported or invalid field type: {}".format(typ))
docs: Converts a JSON field descriptor into its corresponding NumPy / pandas type
  
      Parameters
      ----------
      field
          A JSON field descriptor
  
      Returns
      -------
      dtype
  
      Raises
      -----
      ValueError
          If the type of the provided field is unknown or currently unsupported
  
      Examples
      --------
      >>> convert_json_field_to_pandas_type({'name': 'an_int',
                                             'type': 'integer'})
      'int64'
      >>> convert_json_field_to_pandas_type({'name': 'a_categorical',
                                             'type': 'any',
                                             'contraints': {'enum': [
                                                            'a', 'b', 'c']},
                                             'ordered': True})
      'CategoricalDtype(categories=['a', 'b', 'c'], ordered=True)'
      >>> convert_json_field_to_pandas_type({'name': 'a_datetime',
                                             'type': 'datetime'})
      'datetime64[ns]'
      >>> convert_json_field_to_pandas_type({'name': 'a_datetime_with_tz',
                                             'type': 'datetime',
                                             'tz': 'US/Central'})
      'datetime64[ns, US/Central]'