code: def get_type_string(variables, variable_types):
      var_types = []
      for variable in variables:
          if variable_types[variable] in ["b", "d", "o", "u"]:
              if variable_types[variable] in ["o", "u"]:
                  var_types.append(variable_types[variable])
              else:
                  var_types.append("u")
          elif variable_types[variable] in ["c"]:
              var_types.append("c")
          else:
              raise Exception(
                  "Variable type {} for variable {} not a recognized type.".format(
                      variable_types[variable], variable
                  )
              )
      return "".join(var_types)
  
file_path: dowhy/dowhy/utils/propensity_score.py
imports: import numpy
  import pandas
  from pandas import get_dummies
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import LabelEncoder
  from statsmodels.nonparametric.kernel_density import EstimatorSettings, KDEMultivariateConditional
label_desc: Use image node_id 6 for calling a global function with example usage: get_type_string(variables, variable_types) and returns: str