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Python中使用带循环的漂亮汤的Webscrape交互式图表

beautifulsoup python-3.x python

EricA · 技术社区 · 7 年前

下面的代码提供了页面中所有数字标记的信息。我能用一个过滤器为每个区域提取一次吗

例如: https://opensignal.com/reports/2019/04/uk/mobile-network-experience ,我只对“区域分析”选项卡下的所有区域的数字感兴趣。

import requests
from bs4 import BeautifulSoup

html=requests.get("https://opensignal.com/reports/2019/04/uk/mobile-network-experience").text
soup=BeautifulSoup(html,'html.parser')
items=soup.find_all('div',class_='c-ru-graph__rect')


for item in items:
    provider=item.find('span', class_='c-ru-graph__label').text
    prodvalue=item.find_next_sibling('span').find('span', class_='c-ru-graph__number').text
    print(provider + " : " + prodvalue)

我想要一张桌子或df如下复活节地区

                       o2      Vodaphone   3    EE
4G Availability        82      76.9        73.0   89.2
Upload Speed Experience 5.6    5.9         6.8    9.5

有什么能帮助得到结果的指针吗?

0 回复 | 直到 7 年前

QHarr 7 年前

以下是我将如何为所有地区。需要bs4 4.7.1。AFAICS你必须假设公司的顺序是一致的。

import requests
from bs4 import BeautifulSoup
import pandas as pd

r = requests.get("https://opensignal.com/reports/2019/04/uk/mobile-network-experience")
soup = BeautifulSoup(r.content,'lxml') #'html.parser' if lxml not installed
metrics = ['4g-availability', 'video-experience', 'download-speed' , 'upload-speed', 'latency']
headers = ['02', 'Vodaphone', '3', 'EE']
results = []

for region in soup.select('.s-regional-analysis__region'):
    for metric in metrics:
        providers = [item.text for item in region.select('.c-ru-chart:has([data-metric="' + metric + '"]) .c-ru-graph__number')]
        row = {headers[i] : providers[i] for i in range(len(providers))}
        row['data-metric'] = metric
        row['region'] = region['id'] 
        results.append(row)

df = pd.DataFrame(results, columns = ['region', 'data-metric', '02','Vodaphone', '3', 'EE'] )
print(df)

样本输出:

sentence 7 年前

假设公司的顺序是固定的(事实上是固定的),您可以简单地将要检查的内容减少到只包含所需信息的div。

import requests
from bs4 import BeautifulSoup

html = requests.get("https://opensignal.com/reports/2019/04/uk/mobile-network-experience").text
soup = BeautifulSoup(html,'html.parser')

res = soup.find_all('div', {'id':'eastern'})

aval = res[0].find_all('div', {'data-chart-name':'4g-availability'})
avalname = aval[0].find('span', {'class':'js-metric-name'}).text

upload = res[0].find_all('div', {'data-chart-name':'upload-speed'})
uploadname = upload[0].find('span', {'class':'js-metric-name'}).text

companies = [i.text for i in aval[0].find_all('span', class_='c-ru-graph__label')]

row1 = [i.text for i in aval[0].find_all('span', class_='c-ru-graph__number')]
row2 = [i.text for i in upload[0].find_all('span', class_='c-ru-graph__number')]

import pandas as pd

df = pd.DataFrame({avalname:row1,
                   uploadname:row2})


df.index = companies

df = df.T

输出

                          O2    Vodafone      3      EE
4G Availability         82.0        76.9   73.0    89.2
Upload Speed Experience  5.6         5.9    6.8     9.5