Python 3.x 如何使用bs4提取html表

我正在尝试从以下位置刮取第二个HTML表：'https://www.realclearpolitics.com/epolls/2020/president/pa/pennsylvania_trump_vs_biden-6861.html"

当我运行脚本时，我得到第一个Html表。如何从上面的URL中提取第二个表

我尝试使用以下代码：

from bs4 import BeautifulSoup
import requests
import pandas as pd
import re

Res = requests.get('https://www.realclearpolitics.com/epolls/2020/president/pa/pennsylvania_trump_vs_biden-6861.html')

Soup = BeautifulSoup(Res.text , 'html.parser')

table = Soup.find('table',{'class':'data large'})

list_of_rows = []
for row in table.findAll('tr'):
    list_of_cells = []
    for cell in row.findAll(["td"]):
        try:
            Cell = cell.find('a', {'class': 'mobile_pollster_name'})
            text = re.sub(r'\n\t+', '', Cell.text)
            list_of_cells.append(text)
        except:
            text = re.sub(r'\n\t+', '', cell.text)
            list_of_cells.append(text)
            pass
            
    list_of_rows.append(list_of_cells)
for item in list_of_rows:
    ' '.join(item)
data = pd.DataFrame(list_of_rows)

---

下面的脚本将两个表作为列表中的数据帧提供给您

from bs4 import BeautifulSoup
import requests
import pandas as pd
import re

Res = requests.get('https://www.realclearpolitics.com/epolls/2020/president/pa/pennsylvania_trump_vs_biden-6861.html')

Soup = BeautifulSoup(Res.text , 'html.parser')

tables = Soup.find_all('table',{'class':'data large'})

list_of_dfs = []

for table in tables:
    columns = [i.get_text(strip=True) for i in table.find_all('th')]
    list_of_rows = []
    for row in table.findAll('tr'):
        list_of_rows.append([i.get_text(strip=True) for i in row.find_all('td')])
    df = pd.DataFrame(list_of_rows, columns=columns)
    print(df)
    list_of_dfs.append(df)
    print("---" * 10)

输出：

                           Poll         Date   Sample   MoE Biden (D) Trump (R)      Spread
0                          None         None     None  None      None      None        None
1                   RCP Average  7/15 - 7/26       --    --      49.4      43.4  Biden +6.0
2  CNBC/Change Research (D)CNBC  7/24 - 7/26   382 LV    --        48        46    Biden +2
3                  GravisGravis  7/22 - 7/24  1006 LV   3.1        48        45    Biden +3
4        Franklin & MarshallF&M  7/20 - 7/26   667 RV   5.5        50        41    Biden +9
5              FOX NewsFOX News  7/18 - 7/20   793 RV   3.5        50        39   Biden +11
6    Rasmussen ReportsRasmussen  7/15 - 7/16   750 LV   3.5        51        46    Biden +5
------------------------------
                                     Poll           Date   Sample   MoE Biden (D) Trump (R)      Spread
0                                    None           None     None  None      None      None        None
1                             RCP Average    7/15 - 7/26       --    --      49.4      43.4  Biden +6.0
2            CNBC/Change Research (D)CNBC    7/24 - 7/26   382 LV    --        48        46    Biden +2
3                            GravisGravis    7/22 - 7/24  1006 LV   3.1        48        45    Biden +3
4                  Franklin & MarshallF&M    7/20 - 7/26   667 RV   5.5        50        41    Biden +9
5                        FOX NewsFOX News    7/18 - 7/20   793 RV   3.5        50        39   Biden +11
6              Rasmussen ReportsRasmussen    7/15 - 7/16   750 LV   3.5        51        46    Biden +5
7            CNBC/Change Research (D)CNBC    7/10 - 7/12   743 LV    --        50        42    Biden +8
8                        MonmouthMonmouth     7/9 - 7/13   401 LV   4.9        52        42   Biden +10
9            Trafalgar Group (R)Trafalgar     6/29 - 7/2  1062 LV   2.9        48        43    Biden +5
10           CNBC/Change Research (D)CNBC    6/26 - 6/28   760 LV    --        50        44    Biden +6
11                 SusquehannaSusquehanna    6/15 - 6/23   715 LV   3.8        46        41    Biden +5
12           CNBC/Change Research (D)CNBC    6/12 - 6/14   491 LV    --        49        46    Biden +3
13                NY Times/SienaNYT/Siena     6/8 - 6/16   651 RV   4.2        50        40   Biden +10
14           CNBC/Change Research (D)CNBC    5/29 - 5/31   579 LV    --        46        50    Trump +4
15                   Harper (R)Harper (R)    4/21 - 4/26   644 LV   3.9        49        43    Biden +6
16                       FOX NewsFOX News    4/18 - 4/21   803 RV   3.5        50        42    Biden +8
17                 SusquehannaSusquehanna    4/14 - 4/20   693 LV   3.7        48        42    Biden +6
18                Yahoo News/YouGovYouGov      3/6 - 3/8       RV    --        46        40    Biden +6
19               Morning CallMorning Call    2/12 - 2/20   424 RV   5.5        47        47         Tie
20  Univ. of Wis/State JournalU. of Wisc.    2/11 - 2/20  1249 LV   3.5        46        45    Biden +1
21                   QuinnipiacQuinnipiac    2/12 - 2/18   845 RV   3.4        50        42    Biden +8
22               Morning CallMorning Call    11/4 - 11/9   410 RV   6.0        52        43    Biden +9
23                NY Times/SienaNYT/Siena  10/13 - 10/26   661 LV   4.4        46        45    Biden +1
24                   QuinnipiacQuinnipiac     5/9 - 5/14   978 RV   4.2        53        42   Biden +11
25                         EmersonEmerson    3/26 - 3/28   808 RV   3.4        55        45   Biden +10
------------------------------

---

嗨@bigbounty有没有办法忽略重复的文本。例如：Emerson Emerson，这里重复Emerson。我们如何消除这种情况一旦获得数据帧，就可以保存到csv文件，然后在数据帧上应用函数。这样，您就不会丢失已刮取的数据