code: def z_train_good(self, row_number):
      row = self.df.iloc[row_number]
      # remove row from the data
      df = self.df
      df = self.df.drop(self.df.index[row_number])
      if self.classification == True:
          predict_value = row[self.y_variable]
          df = df[
              df[self.y_variable] == predict_value
          ]  # choose prediction: 0/1
      row1 = row.values
      array = df.values
      Z = row1.reshape(-1, 1).T
  
      return array, Z
  
file_path: explainx/lib/protodash.py
imports: from imports import *
  from encode_decode_cat_col import *
  from rescale_numeric_feature import *
  from PDASH import ProtodashExplainer
  from PDASH_utils import *
label_desc: Use image node_id 8 for calling the protodash obj's underlying member method code with example usage: obj.z_train_good(row_number) and returns: array,  Z