id3

import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split

data = pd.read_csv('data.csv')
X = data.iloc[:, :-1]
y = data.iloc[:, -1]
X = pd.get_dummies(X)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)

clf = DecisionTreeClassifier()
clf.fit(X_train, y_train)

print("Accuracy:", clf.score(X_test, y_test))

new_data = pd.DataFrame({
    'outlook': ['overcast'],
    'temp': ['mild'],
    'humidity': ['high'],
    'windy': ['FALSE']
})
new_data = pd.get_dummies(new_data)
new_data = new_data.reindex(columns=X.columns, fill_value=0)
prediction = clf.predict(new_data)

print("Prediction:", prediction[0])