使用Python从HTML表提取数据并打印到CSV时出现问题

Question

I am trying to scrape Stock Ticker List from IB Website and I am having an issue with extracting table information from HTML.

If I use,

import requests
website_url = requests.get('https://www.interactivebrokers.com/en/index.phpf=2222&exch=mexi&showcategories=STK#productbuffer').text
soup = BeautifulSoup(website_url,'lxml')

My_table = soup.find('div',{'class':'table-responsive no-margin'})
print (My_table)

It captures the HTML Data Information, but when I try to use it with the below code, it doesnt like it, so , as a workaround I captured the HTML Table Data Information and parse it manually.

I have the below code :

import pandas as pd
from bs4 import BeautifulSoup

html_string = """
  <div class="table-responsive no-margin">
      <table width="100%" cellpadding="0" cellspacing="0" border="0" 
 class="table table-striped table-bordered">
     <thead>
          <tr>
           <th width="15%" align="left" valign="middle" 
class="table_subheader">IB Symbol</th>
           <th width="55%" align="left" valign="middle" class="table_subheader">Product Description 
                    <span class="text-small">(click link for more details)</span></th>

       <th width="15%" align="left" valign="middle" class="table_subheader">Symbol</th>
       <th width="15%" align="left" valign="middle" class="table_subheader">Currency</th>
      </tr>
     </thead>
     <tbody>
                <tr>
                  <td>0JN9N</td>
                             <td><a href="javascript:NewWindow('https://misc.interactivebrokers.com/cstools/contract_info/index2.php?action=Details&amp;site=GEN&amp;conid=189723078','Details','600','600','custom','front');" class="linkexternal">DSV AS</a></td>
                  <td>0JN9N</td>
       <td>MXN</td>
      </tr>
                <tr>
                  <td>0QBON</td>
                             <td><a href="javascript:NewWindow('https://misc.interactivebrokers.com/cstools/contract_info/index2.php?action=Details&amp;site=GEN&amp;conid=189723075','Details','600','600','custom','front');" class="linkexternal">COLOPLAST-B</a></td>
                  <td>0QBON</td>
       <td>MXN</td>
      </tr>
                <tr>
                  <td>0R87N</td>
                             <td><a href="javascript:NewWindow('https://misc.interactivebrokers.com/cstools/contract_info/index2.php?action=Details&amp;site=GEN&amp;conid=195567802','Details','600','600','custom','front');" class="linkexternal">ASSA ABLOY AB-B</a></td>
                  <td>0R87N</td>
       <td>MXN</td>
      </tr>
          </tbody>
      </table>"""

soup = BeautifulSoup(html_string, 'lxml') # Parse the HTML as a string
table = soup.find_all('table')[0] # Grab the first table
new_table = pd.DataFrame(columns=range(0,4), index = [0]) # I know the size
row_marker = 0

for row in table.find_all('tr'):
    column_marker = 0
    columns = row.find_all('td')
    for column in columns:
        new_table.iat[row_marker,column_marker] = column.get_text()
        column_marker += 1

print(new_table)

But it is only showing the last line :

If I remove the last part , and add the following :

soup = BeautifulSoup(html, 'lxml')
table = soup.find("div")

# The first tr contains the field names.
headings = [th.get_text().strip() for th in 
table.find("tr").find_all("th")]

print(headings)

datasets = []
for row in table.find_all("tr")[1:]:
    df = pd.DataFrame(headings, (td.get_text() for td in 
    row.find_all("td")))
    datasets.append(df)

print(datasets)

df.to_csv('Path_to_file\\test1.csv')

It sees the rest of the items, but it is completely out of format and in the csv, it is only printing the last item of the list.

How can I extract the details of the HTML table directly from the website and print it to csv in the format of the first image ?

Answer 1

You can delete row_marker = 0

for row_marker, row in enumerate(table.find_all('tr')):
    column_marker = 0
    columns = row.find_all('td')
    try:
        new_table.loc[row_marker] = [column.get_text() for column in columns]
    except ValueError:
        # It's a safe way when [column.get_text() for column in columns] is empty list.
        continue