问题描述
您好，我正在尝试从实时股票网站上抓取一些数据.我想显示公司名称和股票价格，%change 等.每页显示 25 家公司的详细信息，这些详细信息遵循相同的格式，一行数据位于标签下，具有相同的 css 选择器，然后是其余元素，例如公司股价的名称，%change 等是该标签的子代.由于所有数据都遵循相同的格式，我的问题是如何过滤显示该行数据的每个标签?
Hi i'm trying to scrape some data from a live stocks website. I want to display the companies name and stock price, %change ect. The details of 25 companies are shown per page, and these details follow the same format, one row of data comes under the tag, have the same css selector and then the rest of the elements e.g. Name of the company share price, %change ect are children of that tag. Since all data follows the same format, my question is how do i filter through each tag displaying data for that row?
我想过:
使用 for 循环按类名查找元素(因为它们都具有相同的类)然后循环遍历这些但我不知道如何选择该类的子项:
using a for loop to find the elements by class name (since they all have the same class) and then cycle through these but I don't how to select a child of that class:
这里是 html 代码:
Here' the html code:
这是网站的链接https://uk.finance.yahoo.com/most-active
推荐答案
伙计！我在尝试从类似的股票网站抓取数据时遇到了类似的问题
Here ya go man! I had similar issues when trying to scrape data from a similar stock site
from bs4 import BeautifulSoup
from urllib.request import urlopen as uReq
url = "https://uk.finance.yahoo.com/most-active"
uClient = uReq(url)
html_page = uClient.read()
uClient.close()
soup = BeautifulSoup(html_page, 'html.parser')
full_table = soup.find_all("tr", class_="simpTblRow")
for tr in full_table:
td = tr.find_all('td')
row = [i.text for i in td]
print(row)
您可以创建自己的数据结构来保存每个打印值，它会与此输出一起运行(没有标签，输出看起来很混乱，但您可以查看该站点以供参考)
You can make your own data structure to hold each of the printed values, it runs with this output (without labels, the output looks confusing but you can look at the site for reference)
['ICON.L', 'Iconic Labs Plc', '0.0132', '0.0000', '0.00%', '1.291B', '412.755M',
'1.299M', 'N/A', '']
['SYME.L', 'Supply@ME Capital plc', '0.8020', '+0.2320', '+40.70%', '1.145B',
'173.333M', '262.694M', 'N/A', '']
['UJO.L', 'Union Jack Oil plc', '0.2925', '-0.0075', '-2.50%', '210.666M', '154.613M',
'45.165M', 'N/A', '']
['TOM.L', 'TomCo Energy Plc', '0.8750', '+0.0750', '+9.37%', '197.389M', '49.702M',
'5.894M', 'N/A', '']
['PREM.L', 'Premier African Minerals Limited', '0.0680', '-0.0045', '-6.21%',
'193.547M', '136.558M', '8.542M', 'N/A', '']
['COPL.L', 'Canadian Overseas Petroleum Limited', '0.4000', '-0.0200', '-4.76%',
'139.094M', '211.933M', '9.549M', 'N/A', '']
['MSMN.L', 'Mosman Oil And Gas Limited', '0.1800', '+0.0200', '+12.50%', '136.04M',
'51.481M', '2.854M', 'N/A', '']
['VAST.L', 'Vast Resources plc', '0.2100', '-0.0090', '-4.11%', '133.599M',
'243.076M', '25.673M', 'N/A', '']
['UKOG.L', 'UK Oil & Gas Investments PLC', '0.2250', '+0.0150', '+7.14%', '114.909M',
'275.501M', '24.974M', 'N/A', '']
['7DIG.L', '7digital Group plc', '2.8000', '-0.3000', '-9.68%', '111.529M', '23.568M',
'68.752M', 'N/A', '']
['ALBA.L', 'Alba Mineral Resources PLC', '0.0925', '-0.0125', '-11.90%', '99.299M',
'39.579M', '4.472M', 'N/A', '']
['LLOY.L', 'Lloyds Banking Group plc', '28.18', '-0.44', '-1.54%', '98.424M',
'263.235M', '19.948B', '70.46', '']
['KOD.L', 'Kodal Minerals Plc', '0.0475', '0.0000', '0.00%', '111.583M', '75.563M',
'5.278M', 'N/A', '']
['UFO.L', 'Alien Metals Limited', '0.3600', '+0.0500', '+16.13%', '84.677M',
'52.319M', '8.516M', 'N/A', '']
['EDL.L', 'Edenville Energy Plc', '0.0500', '-0.0025', '-4.76%', '80.171M', '47.879M',
'4.073M', 'N/A', '']
['EQT.L', 'EQTEC plc', '0.5300', '+0.0650', '+13.98%', '73.296M', '144.02M',
'36.929M', 'N/A', '']
['BOIL.L', 'Baron Oil Plc', '0.1000', '-0.0025', '-2.44%', '73.45M', '71.853M',
'4.426M', 'N/A', '']
['BREE.L', 'Breedon Group plc', '83.20', '+2.20', '+2.72%', '63.05M', '4.616M',
'1.403B', '43.79', '']
['AMGO.L', 'Amigo Holdings PLC', '9.30', '+0.55', '+6.29%', '62.892M', '20.841M',
'44.206M', 'N/A', '']
['INSP.L', 'Inspirit Energy Holdings Plc', '0.0800', '+0.0025', '+3.23%', '61.622M',
'73.243M', '2.323M', 'N/A', '']
['TRAF.L', 'Trafalgar Property Group plc', '0.2000', '0.0000', '0.00%', '55.959M',
'40.707M', '2.85M', 'N/A', '']
['RBD.L', 'Reabold Resources plc', '0.7300', '-0.0350', '-4.58%', '51.697M',
'23.499M', '51.808M', 'N/A', '']
['CPI.L', 'Capita plc', '28.70', '-7.18', '-20.01%', '48.494M', '12.711M', '478.994M',
'N/A', '']
['GGP.L', 'Greatland Gold plc', '12.20', '-0.80', '-6.15%', '44.829M', '33.176M',
'461.41M', 'N/A', '']
['SRES.L', 'Sunrise Resources plc', '0.3000', '-0.0100', '-3.23%', '39.45M',
'15.895M', '9.963M', 'N/A', '']
这篇关于硒使用元素的子元素抓取数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！