code: def infer_column_types(self):
      column_types = {}
  
      for i in range(self.num_col):
          if self.count_categorical[i] > 0:
              column_types[self.column_names[i]] = CATEGORICAL
          elif (
              len(self.count_unique_numerical[i])
              / self.count_numerical[i]
              < 0.05
          ):
              column_types[self.column_names[i]] = CATEGORICAL
          else:
              column_types[self.column_names[i]] = NUMERICAL
  
      # Partial column_types is provided.
      if self.column_types is None:
          self.column_types = {}
      for key, value in column_types.items():
          if key not in self.column_types:
              self.column_types[key] = value
  
imports: import numpy
  import tensorflow
  from autokeras.engine import analyser
label_desc: Use image node_id 7 for calling the StructuredDataAnalyser obj's underlying member method code with example usage: obj.infer_column_types() without return types