即使 csv 文件包含列名quality，也不存在名为quality的目标

Question

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, r2_score

# Load the wine quality dataset
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv"
data = pd.read_csv(url)  # Adjust the separator if needed

# Explore the dataset
data.head()

# Split the dataset into features (X) and target variable (y)

X = data.drop('quality', axis=1)
y = data['quality']

# Split the data into a training and test set (80% training, 20% testing)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Creating a linear regression model
model = LinearRegression()

# Training the model on the training data
model.fit(X_train, y_train)

# Making predictions on the test data
y_pred = model.predict(X_test)

# Evaluating the model
mse = mean_squared_error(y_test, y_pred)
r2 = r2_score(y_test, y_pred)

print(f"Mean Squared Error: {mse}")
print(f"R-squared: {r2}")

# Plotting as predicted vs. actual 
plt.scatter(y_test, y_pred)
plt.xlabel("Actual Quality")
plt.ylabel("Predicted Quality")
plt.title("Actual vs. Predicted Wine Quality")
plt.show()

上面的代码给出以下错误：

PS C:\Users\JARVIS\Desktop\wine+quality> python -u "c:\Users\JARVIS\Desktop\wine+quality\deleteit.py" 回溯（最近一次调用最后一次）： 文件“c:\Users\JARVIS\Desktop\wine+quality\deleteit.py”，第 16 行，位于 X = data.drop('质量', axis=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 文件“C：\ Users \ JARVIS \ AppData \ Local \ Programs \ Python \ Python311 \ Lib \ site-packages \ panda