prepare_test_data.py

prepare_test_data.py

X_test = X_test_raw.copy()

# Add columns
X_test['can_vote'] = X_test['Age'].apply(lambda age: 1 if age >= 18 else 0)
X_test.loc[:, 'cabin_letter'] = X_test['Cabin'].apply(
    lambda cabin: cabin[0] if cabin and type(cabin) is str else None,
)

# Remove columns
X_test = X_test.drop(columns=['Name', 'PassengerId'])

# Impute values
X_test.loc[X_test['Cabin'].isna(), 'Cabin'] = 'somewhere out of sight'
X_test.loc[X_test['cabin_letter'].isna(), 'cabin_letter'] = 'ZZZ'
X_test.loc[:, ['Age']] = age_imputer.transform(X_test[['Age']])
X_test.loc[X_test['Embarked'].isna(), 'Embarked'] = 'no idea'

# Scale columns
X_test.loc[:, ['Age']] = scaler.transform(X_test[['Age']])

# Encode values
X_test.loc[:, new_column_names] = categorical_encoder.transform(
    X_test[categorical_columns],
).toarray()

# Select features
X_test = X_test[features_to_use].copy()