如何使用python从html页面中提取多个值? [英] How do I pull multiple values from html page using python?

问题描述

我正在根据 nhl 点差/投注赔率信息对自己的知识进行一些数据分析.我能够提取一些信息，但不能提取整个数据集.我想将游戏列表和相关内容拉入熊猫数据帧，但我已经能够围绕 html 标签执行正确的循环.我已经尝试了 findAll 选项和 xpath 路由.我也没有成功.

I'm performing some data analysis for my own knowledge from nhl spread/betting odds information. I'm able to pull some information, but Not the entire data set. I want to pull the list of games and the associated into a panda dataframe, but I have been able to perform the proper loop around the html tags. I've tried the findAll option and the xpath route. I'm not successful with either.

from bs4 import BeautifulSoup
import requests

page_link = 'https://www.thespread.com/nhl-hockey-public-betting-chart'

page_response = requests.get(page_link, timeout=5)

# here, we fetch the content from the url, using the requests library
page_content = BeautifulSoup(page_response.content, "html.parser")


# Take out the <div> of name and get its value
name_box = page_content.find('div', attrs={'class': 'datarow'})
name = name_box.text.strip()

print (name)

推荐答案

此脚本遍历每个数据行并单独拉出每个项目，然后将它们附加到 Pandas DataFrame 中.

This script goes through each datarow and pulls out each item individually and then appends them into a pandas DataFrame.

from bs4 import BeautifulSoup
import requests
import pandas as pd

page_link = 'https://www.thespread.com/nhl-hockey-public-betting-chart'

page_response = requests.get(page_link, timeout=5)

# here, we fetch the content from the url, using the requests library
page_content = BeautifulSoup(page_response.content, "html.parser")


# Take out the <div> of name and get its value
tables = page_content.find_all('div', class_='datarow')

# Iterate through rows
rows = []

# Iterate through each datarow and pull out each home/away separately
for table in tables:
    # Get time and date
    time_and_date_tag = table.find_all('div', attrs={"class": "time"})[0].contents
    date = time_and_date_tag[1]
    time = time_and_date_tag[-1]
    # Get teams
    teams_tag = table.find_all('div', attrs={"class": "datacell teams"})[0].contents[-1].contents
    home_team = teams_tag[1].text
    away_team = teams_tag[-1].text
    # Get opening
    opening_tag = table.find_all('div', attrs={"class": "child-open"})[0].contents
    home_open_value = opening_tag[1]
    away_open_value = opening_tag[-1]
    # Get current
    current_tag = table.find_all('div', attrs={"class": "child-current"})[0].contents
    home_current_value = current_tag[1]
    away_current_value = current_tag[-1]
    # Create list
    rows.append([time, date, home_team, away_team,
                 home_open_value, away_open_value,
                 home_current_value, away_current_value])

columns = ['time', 'date', 'home_team', 'away_team',
           'home_open', 'away_open',
           'home_current', 'away_current']

print(pd.DataFrame(rows, columns=columns))

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