[Python] Machine Learning SciKit Learn High RMSE

I am using SciKit Learn to perform Linear Regression. For some reason I am getting extremely high RMSE. I have checked the data and the car data price min 2000.0 and max price is 38369.0.

Dataset: https://gist.github.com/azamsharp/edc17c9e13a1643ea315d3c3b85fafd4

Do you see anything wrong with the following code?

import pandas as pd
df = pd.read_csv("/content/sample_data/Car_Prices_Dataset__Highly_Correlated__20k_rows_.csv")

from sklearn.preprocessing import StandardScaler

# Standardized
scaler = StandardScaler()
df[["Year", "Mileage"]] = scaler.fit_transform(df[["Year", "Mileage"]])

X = df.drop(["Price"], axis=1)
y = df["Price"]

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

from sklearn.linear_model import LinearRegression

model = LinearRegression()
model.fit(X_train, y_train)

from sklearn.metrics import r2_score, mean_squared_error
y_pred = model.predict(X_test)
r2 = r2_score(y_test, y_pred)
rmse = mean_squared_error(y_test, y_pred)

Test R^2: 0.803
Test RMSE: $21,279,110

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