好的，这里有一个使用pd.read_html的选项：

import pandas as pd

wine = pd.read_html(
    "https://github.com/shrikant-temburwar/Wine-Quality-Dataset/blob/master/winequality-white.csv",
    header=0
)[0]

wine.drop('Unnamed: 0', axis=1, inplace=True)
headers = wine.columns[0].replace('"', '').split(';')
wine.columns = ['data']
wine[headers] = wine.data.str.split(';', expand=True)
wine.drop('data', axis=1, inplace=True)
wine.head()

上面的代码将导致：

>>> wine.head()
  fixed acidity volatile acidity citric acid residual sugar chlorides free sulfur dioxide total sulfur dioxide density    pH sulphates alcohol quality
0             7             0.27        0.36           20.7     0.045                  45                  170   1.001     3      0.45     8.8       6
1           6.3              0.3        0.34            1.6     0.049                  14                  132   0.994   3.3      0.49     9.5       6
2           8.1             0.28         0.4            6.9      0.05                  30                   97  0.9951  3.26      0.44    10.1       6
3           7.2             0.23        0.32            8.5     0.058                  47                  186  0.9956  3.19       0.4     9.9       6
4           7.2             0.23        0.32            8.5     0.058                  47                  186  0.9956  3.19       0.4     9.9       6
>>>

但我绝不会用下面的代码片段的简单性来交换上面的代码：

import pandas as pd

wine = pd.read_csv(
    'https://raw.githubusercontent.com/shrikant-temburwar/Wine-Quality-Dataset/master/winequality-white.csv',
    header=0,
    sep=';'
)

你可能会更好地使用github的rawdatacontent地址来消除由于不同html接口而引起的问题。
以下是您可以执行操作

import pandas as pd
import requests
import io
url = "https://raw.githubusercontent.com/shrikant-temburwar/Wine-Quality-Dataset/master/winequality-white.csv"
r = requests.get(url)
obj = io.BytesIO(r.content)
wine = pd.read_csv(obj, delimiter=";")
wine.head()