Get the content of tr in tbody

Question

I have the following table :

<table class="table table-bordered adoption-status-table">
        <thead>
            <tr>
                <th>Extent of IFRS application</th>
                <th>Status</th>
                <th>Additional Information</th>
            </tr>
        </thead>
        <tbody>
                    <tr>
                        <td>IFRS Standards are required for domestic public companies</td>
                        <td>
                        </td>
                        <td></td>
                    </tr>
                    <tr>
                        <td>IFRS Standards are permitted but not required for domestic public companies</td>
                        <td>
                                <img src="/images/icons/tick.png" alt="tick">
                        </td>
                        <td>Permitted, but very few companies use IFRS Standards.</td>
                    </tr>
                    <tr>
                        <td>IFRS Standards are required or permitted for listings by foreign companies</td>
                        <td>
                        </td>
                        <td></td>
                    </tr>
                    <tr>
                        <td>The IFRS for SMEs Standard is required or permitted</td>
                        <td>
                                <img src="/images/icons/tick.png" alt="tick">
                        </td>
                        <td>The IFRS for SMEs Standard is permitted, but very few companies use it. Nearly all SMEs use Paraguayan national accounting standards.</td>
                    </tr>
                    <tr>
                        <td>The IFRS for SMEs Standard is under consideration</td>
                        <td>
                        </td>
                        <td></td>
                    </tr>
        </tbody>
    </table>

I am trying to extract the data like in its original source :

This is my work :

from bs4 import BeautifulSoup
import requests
import pandas as pd
import re
# Site URL
url = "https://www.ifrs.org/use-around-the-world/use-of-ifrs-standards-by-jurisdiction/paraguay"
# Make a GET request to fetch the raw HTML content
html_content = requests.get(url).text
# Parse HTML code for the entire site
soup = BeautifulSoup(html_content, "lxml")
gdp = soup.find_all("table", attrs={"class": "adoption-status-table"})
print("Number of tables on site: ",len(gdp))

table1 = gdp[0]
body = table1.find_all("tr")
head = body[0] 
body_rows = body[1:] 

headings = []
for item in head.find_all("th"):
    item = (item.text).rstrip("\n")
    headings.append(item)
print(headings)

all_rows = [] 
for row_num in range(len(body_rows)): 
    row = [] 
    for row_item in body_rows[row_num].find_all("td"):
        aa = re.sub("(\xa0)|(\n)|,","",row_item.text)
        row.append(aa)
    all_rows.append(row)

df = pd.DataFrame(data=all_rows,columns=headings)

This is the only output I get :

Number of tables on site:  1
['Extent of IFRS application', 'Status', 'Additional Information']

I want to replace the NULL cells by False and the path to the image check by True.

Answer 1

Above answer is good, one other option is to use pandas.read_html to extract the table into a dataframe and populate the missing Status column using lxml xpath (or beautifulsoup if you prefer but it's more verbose) :

import pandas as pd
import requests
from lxml import html

r = requests.get("https://www.ifrs.org/use-around-the-world/use-of-ifrs-standards-by-jurisdiction/paraguay")
table = pd.read_html(r.content)[0]
tree = html.fromstring(r.content)
table["Status"] = [True if t.xpath("img") else False for t in tree.xpath('//table/tbody/tr/td[2]')]
print(table)

Try this on repl.it

Answer 2

You need to look for img element inside td. Here is an example:

data = []
for tr in body_rows:
    cells = tr.find_all('td')
    img = cells[1].find('img')
    if img and img['src'] == '/images/icons/tick.png':
        status = True
    else:
        status = False
    
    data.append({
        'Extent of IFRS application': cells[0].string,
        'Status': status,
        'Additional Information': cells[2].string,
    })

print(pd.DataFrame(data).head())