python - 当表无法返回值时，如何抓取表？ (美汤)

Question

以下是我的代码:

import numpy as np
import pandas as pd
import requests
from bs4 import BeautifulSoup

stats_page = requests.get('https://www.sports-reference.com/cbb/schools/loyola-il/2020.html')
content = stats_page.content
soup = BeautifulSoup(content, 'html.parser')
table = soup.find(name='table', attrs={'id':'per_poss'})

html_str = str(table)
df = pd.read_html(html_str)[0]
df.head()

我得到错误: ValueError: No tables found.但是，当我交换 attrs={'id':'per_poss'}使用不同的表 ID，如 attrs={'id':'per_game'}我得到一个输出。
我不熟悉 html 和抓取，但我注意到在工作表中，这是 html: <table class="sortable stats_table now_sortable is_sorted" id="per_game" data-cols-to-freeze="2">在不起作用的表格中，这是 html: <table class="sortable stats_table now_sortable sticky_table re2 le1" id="totals" data-cols-to-freeze="2">似乎表类不同，我不确定这是否是导致此问题的原因以及如何解决。
谢谢!

Answer 1

发生这种情况是因为表格在 HTML 注释中 <!-- .... --> .
您可以提取表检查标签是否为 Comment 类型:

import pandas as pd
import requests
from bs4 import BeautifulSoup, Comment

URL = "https://www.sports-reference.com/cbb/schools/loyola-il/2020.html"
soup = BeautifulSoup(requests.get(URL).content, "html.parser")

comments = soup.find_all(text=lambda t: isinstance(t, Comment))
comment_soup = BeautifulSoup(str(comments), "html.parser")

table = comment_soup.select("#div_per_poss")[0]
df = pd.read_html(str(comment_soup))
print(df)

输出:

[      Rk             Player   G    GS    MP   FG  ...  AST  STL  BLK  TOV   PF   PTS
0    1.0    Cameron Krutwig  32  32.0  1001  201  ...  133   39   20   81   45   482
1    2.0          Tate Hall  32  32.0  1052  141  ...   70   47    3   57   56   406
2    3.0   Marquise Kennedy  32   6.0   671  110  ...   43   38    9   37   72   294
3    4.0   Lucas Williamson  32  32.0   967   99  ...   53   49    9   57   64   287
4    5.0      Keith Clemons  24  24.0   758   78  ...   47   29    1   32   50   249
5    6.0         Aher Uguak  32  31.0   768   62  ...   61   15    3   59   56   181
6    7.0      Jalon Pipkins  30   1.0   392   34  ...   12   10    1   17   15   101
7    8.0      Paxson Wojcik  30   1.0   327   25  ...   18   14    0   14   23    61
...
...