HTML в элементе проверки отличается от отображаемого на экране. ⇐ Html

[Anonymous]

Я пытаюсь удалить данные с этого сайта
https://www.eurobasket.com/Basketball-B ... 84-Lebanon
На веб-сайте есть две таблицы:
но данные, отображаемые в строке таблиц, отличаются от данных в исходном коде html (после выполнения элемента проверки).
например, это данные для первой строки:

 
SMdRl-XIuQ, zRij
45
4-9 (38.7%)
0-9 (96.3%)
5-5 (5%)
5
6
6
1
6
5
5
6
5
8
86
5
5

но имя игрока Жан Абдель-Нур, а не SMdRl-XIuQ, zRij и тому подобное по цифрам.
Я пробовал селен, но не помогло
import pandas as pd
import requests
from bs4 import BeautifulSoup
from selenium import webdriver

def extract_box_score_from_url(url):
# Fetch the webpage content
driver = webdriver.Chrome() # Ensure ChromeDriver is installed and in PATH
driver.get(url)
html_content = driver.page_source
soup = BeautifulSoup(html_content, 'html.parser')
driver.quit()

# Extract team and opponent names
team = soup.find('table', {'id': 'aannew'}).find('a').text.strip()
opponent = soup.find_all('table', {'id': 'aannew'})[1].find('a').text.strip()

# Extract headers
stats_divs = soup.find_all('div', class_='dvbs')
header_rows = stats_divs[0].find('thead').find_all('tr')

# Flatten headers by concatenating main headers and subheaders
headers = []
for th in header_rows[1].find_all('th'): # Process the second header row
main_header = th.get('colspan', None)
sub_header = th.get_text(strip=True)
headers.append(sub_header)

# Add Team and Opponent columns to headers
headers += ['Team', 'Opponent']

# Function to extract stats table for a team
def extract_team_stats(dvbs):
rows = dvbs.find('tbody').find_all('tr', class_=['my_pStats1', 'my_pStats2'])
stats = []
for row in rows:
cols = row.find_all('td')
player_data = [col.get_text(strip=True) for col in cols]
stats.append(player_data)
return stats

# Extract stats for both teams
team_stats = extract_team_stats(stats_divs[0])
opponent_stats = extract_team_stats(stats_divs[1])

# Add Team and Opponent columns
num_columns = len(headers)
team_stats = [row + [team, opponent] for row in team_stats if len(row) + 2 == num_columns]
opponent_stats = [row + [opponent, team] for row in opponent_stats if len(row) + 2 == num_columns]

# Combine data
combined_stats = team_stats + opponent_stats

# Create dataframe
df = pd.DataFrame(combined_stats, columns=headers)

return df

url = "https://www.eurobasket.com/Basketball-B ... 84-Lebanon"
df = extract_box_score_from_url(url)

df

Можете ли вы помочь мне найти способ очистить эти данные? Я попробовал Селен
import pandas as pd
import requests
from bs4 import BeautifulSoup
from selenium import webdriver

def extract_box_score_from_url(url):
# Fetch the webpage content
driver = webdriver.Chrome() # Ensure ChromeDriver is installed and in PATH
driver.get(url)
html_content = driver.page_source
soup = BeautifulSoup(html_content, 'html.parser')
driver.quit()

# Extract team and opponent names
team = soup.find('table', {'id': 'aannew'}).find('a').text.strip()
opponent = soup.find_all('table', {'id': 'aannew'})[1].find('a').text.strip()

# Extract headers
stats_divs = soup.find_all('div', class_='dvbs')
header_rows = stats_divs[0].find('thead').find_all('tr')

# Flatten headers by concatenating main headers and subheaders
headers = []
for th in header_rows[1].find_all('th'): # Process the second header row
main_header = th.get('colspan', None)
sub_header = th.get_text(strip=True)
headers.append(sub_header)

# Add Team and Opponent columns to headers
headers += ['Team', 'Opponent']

# Function to extract stats table for a team
def extract_team_stats(dvbs):
rows = dvbs.find('tbody').find_all('tr', class_=['my_pStats1', 'my_pStats2'])
stats = []
for row in rows:
cols = row.find_all('td')
player_data = [col.get_text(strip=True) for col in cols]
stats.append(player_data)
return stats

# Extract stats for both teams
team_stats = extract_team_stats(stats_divs[0])
opponent_stats = extract_team_stats(stats_divs[1])

# Add Team and Opponent columns
num_columns = len(headers)
team_stats = [row + [team, opponent] for row in team_stats if len(row) + 2 == num_columns]
opponent_stats = [row + [opponent, team] for row in opponent_stats if len(row) + 2 == num_columns]

# Combine data
combined_stats = team_stats + opponent_stats

# Create dataframe
df = pd.DataFrame(combined_stats, columns=headers)

return df

url = "https://www.eurobasket.com/Basketball-B ... 84-Lebanon"
df = extract_box_score_from_url(url)

df


Подробнее здесь: https://stackoverflow.com/questions/793 ... -on-screen