class_docstr: A data interface for public data. This class is an interface to DiCE explainers
  and contains methods to transform user-fed raw data into the format a DiCE explainer
  requires, and vice versa.
docstr: Infers data type of a continuous feature from the training data.
code: def get_data_type(self, col):
      """Infers data type of a continuous feature from the training data."""
      if (
          (self.data_df[col].dtype == np.int64)
          or (self.data_df[col].dtype == np.int32)
          or (self.data_df[col].dtype == np.int16)
          or (self.data_df[col].dtype == np.int8)
      ):
          return "int"
      elif (
          (self.data_df[col].dtype == np.float64)
          or (self.data_df[col].dtype == np.float32)
          or (self.data_df[col].dtype == np.float16)
      ):
          return "float"
      else:
          raise ValueError(
              "Unknown data type of feature %s: must be int or float"
              % col
          )
  
imports: import logging
  from collections import defaultdict
  import numpy
  import pandas
  from raiutils.exceptions import UserConfigValidationException
  from sklearn.preprocessing import LabelEncoder
  from dice_ml.data_interfaces.base_data_interface import _BaseData
  from dice_ml.utils.exception import SystemException
label_desc: Use image node_id 7 for calling the PublicData obj's underlying member method code with example usage: obj.get_data_type(col) and returns: str, str