class_docstr: A data interface for private data with meta information.
class_docstr_tok: ["A","data","interface","for","private","data","with","meta","information","."]
docstr: "Gets the precision of continuous features in the data.
docstr_tok: ["``","Gets","the","precision","of","continuous","features","in","the","data","."]
code: def get_decimal_precisions(self, output_type="list"):
      """ "Gets the precision of continuous features in the data."""
      precisions_dict = defaultdict(int)
      precisions = [0] * len(self.feature_names)
      for ix, feature_name in enumerate(self.continuous_feature_names):
          type_prec = self.type_and_precision[feature_name]
          if type_prec == "int":
              prec = 0
          else:
              prec = self.type_and_precision[feature_name][1]
          precisions[ix] = prec
          precisions_dict[feature_name] = prec
      if output_type == "list":
          return precisions
      elif output_type == "dict":
          return precisions_dict
  
imports: import collections
  import logging
  import sys
  from collections import defaultdict
  import numpy
  import pandas
  from sklearn.preprocessing import LabelEncoder
  from dice_ml.data_interfaces.base_data_interface import _BaseData
label_desc: Use image node_id 18 for calling the PrivateData obj's underlying member method code with example usage: obj.get_decimal_precisions(output_type) and returns: precisions, precisions_dict