How to put book information from amazon into a table form?

I have an amazon link, i.e.,

I'm able to extract Product details from the HTML with soup.select("#detailBullets_feature_div .a-unordered-list:first-child"), i.e.,

<ul class="a-unordered-list a-nostyle a-vertical a-spacing-none detail-bullet-list">
<li><span class="a-list-item"> <span class="a-text-bold">Publisher : </span> <span>Matrix Editions (January 1, 2007)</span> </span></li>
<li><span class="a-list-item"> <span class="a-text-bold">Language : </span> <span>English</span> </span></li>
<li><span class="a-list-item"> <span class="a-text-bold">Hardcover : </span> <span>640 pages</span> </span></li>
<li><span class="a-list-item"> <span class="a-text-bold">ISBN-10 : </span> <span>0971576610</span> </span></li>
<li><span class="a-list-item"> <span class="a-text-bold">ISBN-13 : </span> <span>978-0971576612</span> </span></li>
<li><span class="a-list-item"> <span class="a-text-bold">Item Weight : </span> <span>2.3 pounds</span> </span></li>
</ul>

Could you explain how to put above data in a tabular form? My expected result is

from bs4 import BeautifulSoup
import pandas as pd
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from webdriver_manager.chrome import ChromeDriverManager

link = 'https://www.amazon.com/Functional-Analysis-Dzung-Ha/dp/0971576610'
driver = webdriver.Chrome(service = Service(ChromeDriverManager().install()))
driver.get(link)
soup = BeautifulSoup(driver.page_source, 'html.parser')
soup.select("#detailBullets_feature_div .a-unordered-list:first-child")

You can build a dictionary by using the span.a-text-bolds for keys and the rest of the texts in each span.a-list-item as values (like in the function defined below), and that dictionary can be used to form a row in a DataFrame.

def get_product_details(prod_soup):
    rkSel = 'span.a-list-item>span.a-text-bold:first-child'
    rkSel = f'div#detailBullets_feature_div {rkSel}'

    pDets = {}
    for r in prod_soup.select(rkSel):
        k = r.get_text(' ', strip=True) 
        v = r.parent.get_text(' ', strip=True).replace(k,'',1).strip() 
        if 'Rank' in k and v[:1]=='#': v = ' • #'.join(v.split(' #'))

        pDets[k.split('\n')[0].strip(':')] = v
    return pDets 

For your link, get_product_details(soup) should return

>py
> {'Publisher': 'Matrix Editions (January 1, 2007)',
> 'Language': 'English',
> 'Hardcover': '640 pages',
> 'ISBN-10': '0971576610',
> 'ISBN-13': '978-0971576612',
> 'Item Weight': '2.3 pounds',
> 'Best Sellers Rank': '#7,261,544 in Books ( See Top 100 in Books )',
> 'Customer Reviews': '5.0 out of 5 stars 2 ratings'}
>

and pd.DataFrame([get_product_details(soup)]) should return

You could loop through multiple links to fill multiple rows:

urls_list = [
    'https://www.amazon.com/Atomic-Habits-Proven-Build-Break/dp/0735211299',
    'https://www.amazon.com/Functional-Analysis-Dzung-Ha/dp/0971576610',
    'https://www.amazon.com/Daisy-Jones-Taylor-Jenkins-Reid/dp/1524798649',
    'https://www.amazon.com/Body-Keeps-Score-Healing-Trauma/dp/0143127748',
    'https://www.amazon.com/History-Uncertain-Future-Handwriting/dp/1620402157'
]

books_list = []
for url in urls_list:
    soup = linkToSoup_scrapingAnt(url)
    # books_list.append(get_product_details(soup)) ## no extra columns

    kList, sList = ['Title','Author'], ['span#productTitle','span.author']
    book_info = { k: t.get_text(' ', strip=True) if t else None for k,t 
                  in zip(kList, [soup.select_one(s) for s in sList])    }
    books_list.append({**book_info, **get_product_details(soup)})

Note: If you want only the section covered in the HTML snippet in your question (i.e., without the Best Sellers Rank and Customer Reviews keys/columns), you can define rkSel as

    rkSel = 'ul:first-of-type span.a-list-item>span.a-text-bold:first-child'
    rkSel = f'h2+div#detailBullets_feature_div {rkSel}'