当数字没有在html中显示时，如何从网站中提取表格？

Question

我试图提取下表中的所有行业和时期的网站。然而，当我下载html时，在网站上显示的数字在任何地方都找不到。如何检索表的条目？你知道吗

https://csimarket.com/Industry/industry_Efficiency.php?ind=102

下面的代码提取了html。经过检查，表中的数字没有出现在任何地方，所以我无法提取它们。问题是他们在哪里？如何访问和提取它们？你知道吗

请注意，我是新来的要求和美丽的汤！ 非常感谢！你知道吗

import requests

my_target='https://csimarket.com/Industry/industry_Efficiency.php?ind=102'

r  = requests.get(my_target)
data = r.text

Answer 1

使用熊猫会更整洁read_html

import pandas as pd
tables = pd.read_html('https://csimarket.com/Industry/industry_Efficiency.php?ind=102')
print(tables[6].fillna(''))

Answer 2

您可以使用requests，但您需要使用r.content而不是r.text：

import requests

my_target='https://csimarket.com/Industry/industry_Efficiency.php?ind=102'

r  = requests.get(my_target)
data = r.content

您也可以使用^{} module来解析html，如下所示：

import requests
#load beautifullsoup
from bs4 import BeautifulSoup 
my_target='https://csimarket.com/Industry/industry_Efficiency.php?ind=102'
r  = requests.get(my_target)
#get raw html
data = r.content
#soup the content
soup = BeautifulSoup(data, 'html.parser')
#find table element
table_element = soup.find('table',{"class":"osnovna_tablica_bez_gifa"})
#print text version of table element
print table_element.text

这给了你：

Chemicals - Plastics & Rubber Industry
3 Q
2 Q
1 Q
4 Q
3 Q


 

2018
2018
2018
2017
2017


Revenue/Employee (TTM) $
428,075
327,852
323,322
338,175
325,069


Sales/Employee Ranking
# 22
# 78
# 79
# 68
# 74


Net Income/Employee (TTM) $
37,510
18,571
20,953
27,151
18,810


Net Income/Employee 
                  Ranking 
# 16
# 72
# 69
# 58
# 64


Receivable Turnover Ratio (TTM)
7.53
5.17
5.07
5.17
5.11


Receivable Turnover Ranking 
# 31
# 88
# 90
# 87
# 89


Inventory Turnover Ratio (TTM) Sales
8.1
5.56
5.65
6.13
6.45


Inventory Turnover (Sales)
                  Ranking 
# 31
# 90
# 90
# 86
# 85


Inventory Turnover Ratio (TTM) COS
5.77
3.83
3.81
4.16
4.37


Inventory Turnover (COS)
                  Ranking 
# 24
# 79
# 81
# 75
# 77


Asset Turnover Ratio (TTM)
0.92
0.47
0.52
0.6
0.69


Asset Turnover Ranking 

# 31
# 72
# 68
# 63
# 49

Answer 3

您可以使用urllib包，然后使用正则表达式提取数字。执行：

import urllib3
from bs4 import BeautifulSoup

http = urllib3.PoolManager()

url = "https://csimarket.com/Industry/industry_Efficiency.php?ind=102"
response = http.request('GET', url)

soup = BeautifulSoup(response.data)

spans = soup.find_all("span")

for span in spans:

  print(span)

这将提供：

<span class="">428,075</span>
<span class="">327,852</span>
<span class="">323,322</span>
...
<span class="siva3">31</span>
<span class="siva3"># 5</span>
<span class="siva3"># 31</span>