KNN-German Credit

def solve():
    import pandas as pd
    from sklearn.neighbors import KNeighborsClassifier
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import accuracy_score
    from sklearn.preprocessing import LabelEncoder, StandardScaler
    df = pd.read_csv(____)
    le = LabelEncoder()
    for col in df.columns:
        if df[col].dtype == '____':
            df[col] = le.fit_transform(____)
    X = df.drop(____)
    y = df['____']
    X_train, X_test, y_train, y_test = train_test_split(____)
    scaler = StandardScaler()
    X_train = scaler.fit_transform(____)
    X_test = scaler.transform(____)
    knn = KNeighborsClassifier(____)
    knn.fit(____)
    print('____', round(accuracy_score(y_test, knn.predict(____)), ____))