Polynomial Regression曲线绘制异常求助：如何正确处理难处理数据？

我在执行多项式回归时遇到问题，绘制出的曲线不符合预期。已查阅Stack Overflow上的同类问题，但未找到适用的解决方案。当前以reviews_per_month为自变量X，price为因变量y进行建模。

我尝试过排序X值，但问题仍未解决。以下是我的代码：

# Defining independent and dependent variables
X = cph_listings_df[['reviews_per_month']].values.reshape(-1, 1)
y = cph_listings_df['price'].values.reshape(-1, 1)

# split into test and training
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)

# scale features
scaler = StandardScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)

# Fitting Linear Regression to the dataset
lin_reg = LinearRegression()
lin_reg.fit(X, y)

# Fitting Polynomial Regression to the dataset
poly_model = PolynomialFeatures(degree=2)
X_poly = poly_model.fit_transform(X) # transformer X to poly features
pol_reg = LinearRegression() # instance of lineargression
pol_reg.fit(X_poly, y) # train model
y_predict = pol_reg.predict(X_poly) # predict on trained model
plt.scatter(X, y, color='red') # red = actual data points
    plt.plot(X, y_predict , color='blue') 
    plt.title('Polynomia Regression)') 
    plt.xlabel('Number of reviews')  
    plt.ylabel('Price')
    plt.show()

当前生成的曲线图：

老师要求的曲线图（手绘）：

恳请有类似经验或成功处理过同类数据的人士提供解决方案。

内容的提问来源于stack exchange，提问作者BrunkageCoder