text: import matplotlib.pyplot as plt
  import pandas as pd
  from sklearn import tree
  
  raw = pd.read_csv("weather.csv", sep=";")
  
  def quantify(column_name):
      map = {val: i for i, val in enumerate(raw[column_name].drop_duplicates().values)}
      raw[column_name] = [map[val] for val in raw[column_name]]
  
  
  quantify("Decision")
  quantify("Weather")
  quantify("Parents")
  quantify("Money")
  
  X = raw.iloc[:,1:-1]
  y = raw["Decision"]
  print(X)
  model = tree.DecisionTreeClassifier()
  model.fit(X, y)
  
  plt.figure(num="Tree", figsize=(10, 5))
  tree.plot_tree(model, feature_names=X.columns, filled=True, rounded=True, fontsize=6)
  plt.show()
  
  