import statsmodels.tools.tools as stattools
import pandas as pd
import numpy as np
from sklearn.tree import DecisionTreeClassifier, export_graphviz

adult_tr = pd.read_csv('~/Desktop/Dataset_Assignment/adult_ch6_training',
             usecols=['Marital status','Income','Cap_Gains_Losses'])
y = adult_tr[['Income']]

mar_np = np.array(adult_tr['Marital status']) 
(mar_cat, mar_cat_dict) = stattools.categorical(mar_np, drop=True, dictnames = True)
mar_cat_pd = pd.DataFrame(mar_cat) 

X = pd.concat((adult_tr[['Cap_Gains_Losses']], mar_cat_pd), axis = 1)

X_names = ["Cap_Gains_Losses", "Divorced", "Married",  "Never-married", "Separated", "Widowed"]
y_names = ["<=50K", ">50K"] 

cart01 = DecisionTreeClassifier(criterion = "gini", max_leaf_nodes=5).fit(X,y)

data = export_graphviz(cart01, out_file =None, feature_names=X_names, class_names=y_names)

predIncomeCART = cart01.predict(X)

Struggle to run this program, I wonder if there is anything missing from this code. When I run it, it shows the error message:

NotImplementedError                       Traceback (most recent call last)
Cell In[11], line 11
  8 y = adult_tr[['Income']]
 10 mar_np = np.array(adult_tr['Marital status']) 
---> 11 (mar_cat, mar_cat_dict) = stattools.categorical(mar_np, drop=True, dictnames = True)
 12 mar_cat_pd = pd.DataFrame(mar_cat) 
 14 X = pd.concat((adult_tr[['Cap_Gains_Losses']], mar_cat_pd), axis = 1)

File /opt/anaconda3/lib/python3.11/site-packages/statsmodels/tools/tools.py:151, in      categorical(data, col, dictnames, drop)
 71 def categorical(data, col=None, dictnames=False, drop=False):
 72     """
 73     Construct a dummy matrix from categorical variables
 74 
 (...)
149     >>> design2 = sm.tools.categorical(struct_ar, col='str_instr', drop=True)
150     """
--> 151     raise NotImplementedError("categorical has been removed")

NotImplementedError: categorical has been removed

I tried to search the Internet to find any clue, unfortunately, I did not find anything yet.
Any help will be appreciate it!