如何从网页的图形中提取数据

Question

我正在尝试从网页中抓取图形数据：'https://cawp.rutgers.edu/women-percentage-2020-candidates'

我尝试了以下代码从Graph中提取数据：

import requests
from bs4 import BeautifulSoup
Res = requests.get('https://cawp.rutgers.edu/women-percentage-2020-candidates').text
soup = BeautifulSoup(Res, "html.parser")
Values= [i.text for i in soup.findAll('g', {'class': 'igc-graph'}) if i]
Dates = [i.text for i in soup.findAll('g', {'class': 'igc-legend-entry'}) if i]
print(Values, Dates) ## both list are empty
Data= pd.DataFrame({'Value':Values,'Date':Dates}) ## Returning an Empty Dataframe

我想从所有的4条图中提取日期和值。请任何人建议我在这里必须做什么来提取图形数据，或者有没有其他方法可以尝试提取数据。谢谢

Answer 1

此图位于此url上：https://e.infogram.com/5bb50948-04b2-4113-82e6-5e5f06236538

如果您查找具有属性data-id:值的类infogram-embed的div，则可以直接在原始url上找到信息图id(目标url的路径(

<div class="infogram-embed" data-id="5bb50948-04b2-4113-82e6-5e5f06236538" data-title="Candidate Tracker 2020_US House_Proportions" data-type="interactive"> </div>

从这个url，它以javascript加载一个静态JSON。您可以使用regex来提取它，并解析JSON结构以获得行/列和不同的表：

import requests
from bs4 import BeautifulSoup
import re
import json
original_url = "https://cawp.rutgers.edu/women-percentage-2020-candidates"
r = requests.get(original_url)
soup = BeautifulSoup(r.text, "html.parser")
infogram_url = f'https://e.infogram.com/{soup.find("div",{"class":"infogram-embed"})["data-id"]}'
r = requests.get(infogram_url)
soup = BeautifulSoup(r.text, "html.parser")
script = [
t 
for t in soup.findAll("script") 
if "window.infographicData" in t.text
][0].text
extract = re.search(r".*window.infographicData=(.*);$", script)
data = json.loads(extract.group(1))
entities = data["elements"]["content"]["content"]["entities"]
tables = [
(entities[key]["props"]["chartData"]["sheetnames"], entities[key]["props"]["chartData"]["data"])
for key in entities.keys()
if ("props" in entities[key]) and ("chartData" in entities[key]["props"])
]
data = []
for t in tables:
for i, sheet in enumerate(t[0]):
data.append({
"sheetName": sheet,
"table": dict([(t[1][i][0][j],t[1][i][1][j])  for j in range(len(t[1][i][0])) ])
})
print(data)

输出：

[{'sheetName': 'Sheet 1',
'table': {'': '2020', 'Districts Already Filed': '435'}},
{'sheetName': 'All',
'table': {'': 'Filed', '2016': '17.8%', '2018': '24.2%', '2020': '29.1%'}},
{'sheetName': 'Democrats Only',
'table': {'': 'Filed', '2016': '25.1%', '2018': '32.5%', '2020': '37.9%'}},
{'sheetName': 'Republicans Only',
'table': {'': 'Filed', '2016': '11.5%', '2018': '13.7%', '2020': '21.3%'}}]