淡.印象 发表于2022-04-20 15:44
                                                                读者您好:
书中源码没有问题,请检查一下您的代码,代码中是否获取了网页地址,完整代码如下:
pandas pd
pd.set_option(, )
df=pd.DataFrame()
url_list=[]
i (1,14):
    url=+(i)
    url_list.append(url)
url url_list:
    df=df.append(pd.read_html(url),=)
(df)
df=df[[x.startswith() x df[3]]]
(df)
df.to_excel(,=[,,,],=)
                                                                                                                                D:\pycharm_Project_数据分析\venv\Scripts\python.exe D:/pycharm_Project_数据分析/pandas学习/dataframe对象/导入HTML文件.py
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
       0                    1                       2            3
1     41     Jaylen Brown, SG          Boston Celtics  $26,758,928
2     42    DeMar DeRozan, SF           Chicago Bulls  $26,000,000
3     43   Draymond Green, PF   Golden State Warriors  $24,026,712
4     44    Nikola Vucevic, C           Chicago Bulls  $24,000,000
5     45     John Collins, PF           Atlanta Hawks  $23,000,000
..   ...                  ...                     ...          ...
479  476  Ryan Arcidiacono, G         New York Knicks     $546,800
480  477  DeAndre' Bembry, SG         Milwaukee Bucks     $518,021
481  478     Goran Dragic, PG           Brooklyn Nets     $460,463
482  479     Jevon Carter, PG         Milwaukee Bucks     $441,277
483  480  Trendon Watford, PF  Portland Trail Blazers     $436,482
[440 rows x 4 columns]
D:\pycharm_Project_数据分析\pandas学习\dataframe对象\导入HTML文件.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  df = df.append(pd.read_html(url),ignore_index=True)
这个返回结果中报错信息太多了