# Creating a new feature: 'Pass' based on 'Score' df['Pass'] = df['Score'].apply(lambda x: 'Yes' if x >= 90 else 'No')
# Assuming X is your feature data and y is your target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) z5pHwQybCwiXFwWqMv3v.zip
y_pred = model.predict(X_test) print("Accuracy:", accuracy_score(y_test, y_pred)) This process can vary widely depending on your specific data and goals. If you have more details about the zip file's contents and what you're trying to achieve, I could provide more targeted advice. # Creating a new feature: 'Pass' based on
import zipfile