California房价线性回归可视化

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    import numpy as np
    from sklearn.linear_model import LinearRegression
    from sklearn.model_selection import train_test_split
    df = pd.read_csv(____).head(____)
    X = df[["____"]]; y = df["____"]
    X_train, X_test, y_train, y_test = train_test_split(____)
    lr = LinearRegression().fit(____)
    xline = np.linspace(X["____"].min(), X["____"].max(), ____).reshape(____)
    plt.scatter(____)
    plt.plot(xline, lr.predict(____), "____", linewidth=____, label="____")
    plt.xlabel(____); plt.ylabel(____); plt.legend()
    plt.title(____); plt.show()
    print(____)