import pandas as pd
 from sklearn.datasets import load_iris
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import accuracy_score,confusion_matrix,classification_report
 iris=load_iris()
 df=pd.DataFrame(data=iris.data,columns=iris.feature_names)
 print(df.head())
 df['Species']=iris.target
 x=df.drop('Species',axis=1)
 y=df['Species']
 x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=42)
 model=DecisionTreeClassifier(random_state=42)
 model.fit(x_train,y_train)
 y_pred=model.predict(x_test)
 print(accuracy_score(y_test,y_pred))
 print(confusion_matrix(y_test,y_pred))
 print(classification_report(y_test,y_pred))