Python 从多个链接中删除表格数据，并将其合并到一个excel文件中

我有一个链接，在这个链接中，我有一些产品。每种产品都有一个规格表。该表的第一列应该是标题，第二列应该是与之对应的数据。每个表的第一列都不同，有一些重叠的类别。我想得到一个大桌子，上面有所有这些类别，每行都有不同的产品。我能够获得一个表（一种产品）的数据，如下所示：

import requests
import pandas as pd
import xlsxwriter
import csv
from lxml import html
from bs4 import BeautifulSoup
url= "https://www.1800cpap.com/resmed-airfit-n30-nasal-cpap-mask-with-headgear"
source_code= requests.get(url)
plain_text= source_code.text
soup= BeautifulSoup(plain_text, 'html.parser')
table= soup.find("table", {"class":"table"})

print(table)
output_rows=[]
table_rows= table.find_all('tr')
#print(table_rows)

headers = [td.text for td in soup.select_one('.table').select('td:nth-of-type(1)')]
with open("data.csv", "w", encoding="utf-8-sig", newline='') as csv_file:
    w = csv.writer(csv_file, delimiter = ",", quoting=csv.QUOTE_MINIMAL)
    w.writerow(headers)
    for table in soup.select('table'):
        w.writerow([td.text for td in table.select('td:nth-of-type(2)')])

我知道，对于不同的产品，我必须循环到eac产品的链接，我能够做到这一点。但是，如何将每个表附加到以前的输出中，以保持所需的表结构

import requests
import pandas as pd
from bs4 import BeautifulSoup


url = 'https://www.1800cpap.com/cpap-masks/nasal'

def get_item(url):
    soup = BeautifulSoup(requests.get(url).content, 'html.parser')

    print('Getting {}..'.format(url))

    title = soup.select_one('h1.product-details-full-content-header-title').get_text(strip=True)

    all_data = {'Item Title': title}
    for tr in soup.select('#product-specs-list tr'):
        h, v = [td.get_text(strip=True) for td in tr.select('td')]
        all_data[h.rstrip(':')] = v

    return all_data

all_data = []
for page in range(1, 2):
    print('Page {}...'.format(page))
    soup = BeautifulSoup(requests.get(url, params={'page': page}).content, 'html.parser')

    for a in soup.select('a.facets-item-cell-grid-title'):
        u = 'https://www.1800cpap.com' + a['href']
        all_data.append(get_item(u))

df = pd.DataFrame(all_data)
df.to_csv('data.csv')

印刷品：

Page 1...
Getting https://www.1800cpap.com/resmed-airfit-n30-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/dreamwear-nasal-cpap-mask-with-headgear-by-philips-respironics..
Getting https://www.1800cpap.com/eson-2-nasal-cpap-mask-with-headgear-by-fisher-and-paykel..
Getting https://www.1800cpap.com/resmed-mirage-fx-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n30i-nasal-cpap-mask-by-resmed..
Getting https://www.1800cpap.com/dreamwisp-nasal-cpap-mask-fitpack..
Getting https://www.1800cpap.com/respironics-comfortgel-blue-cpap-nasal-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-mirage-fx-for-her-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n20-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/wisp-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/pico-nasal-cpap-mask-with-headgear-by-philips-respironics-2..
Getting https://www.1800cpap.com/airfit-n20-for-her-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/airfit-f10-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/fisher-and-paykel-zest-q-nasal-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-swift-fx-nano-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-ultra-mirage-2-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n10-for-her-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/eson-nasal-cpap-mask-by-fisher-and-paykel..
Getting https://www.1800cpap.com/resmed-swift-fx-nano-nasal-cpap-mask-for-her-with-headgear..
Getting https://www.1800cpap.com/mirage-activa-lt-cpap-mask-by-resmed..
Getting https://www.1800cpap.com/resmed-mirage-micro-cpap-mask..
Getting https://www.1800cpap.com/phillips-respironics-trueblue-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/fisher-paykel-zest-cpap-mask..
Getting https://www.1800cpap.com/viva-nasal-cpap-mask-by-3b-medical..

并保存

data.csv

（来自LibreOffice的屏幕截图）：

印刷品：

Page 1...
Getting https://www.1800cpap.com/resmed-airfit-n30-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/dreamwear-nasal-cpap-mask-with-headgear-by-philips-respironics..
Getting https://www.1800cpap.com/eson-2-nasal-cpap-mask-with-headgear-by-fisher-and-paykel..
Getting https://www.1800cpap.com/resmed-mirage-fx-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n30i-nasal-cpap-mask-by-resmed..
Getting https://www.1800cpap.com/dreamwisp-nasal-cpap-mask-fitpack..
Getting https://www.1800cpap.com/respironics-comfortgel-blue-cpap-nasal-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-mirage-fx-for-her-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n20-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/wisp-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/pico-nasal-cpap-mask-with-headgear-by-philips-respironics-2..
Getting https://www.1800cpap.com/airfit-n20-for-her-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/airfit-f10-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/fisher-and-paykel-zest-q-nasal-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-swift-fx-nano-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/resmed-ultra-mirage-2-nasal-cpap-mask..
Getting https://www.1800cpap.com/airfit-n10-for-her-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/eson-nasal-cpap-mask-by-fisher-and-paykel..
Getting https://www.1800cpap.com/resmed-swift-fx-nano-nasal-cpap-mask-for-her-with-headgear..
Getting https://www.1800cpap.com/mirage-activa-lt-cpap-mask-by-resmed..
Getting https://www.1800cpap.com/resmed-mirage-micro-cpap-mask..
Getting https://www.1800cpap.com/phillips-respironics-trueblue-nasal-cpap-mask-with-headgear..
Getting https://www.1800cpap.com/fisher-paykel-zest-cpap-mask..
Getting https://www.1800cpap.com/viva-nasal-cpap-mask-by-3b-medical..

并保存

data.csv

（来自LibreOffice的屏幕截图）：

---

将所有结果附加到一个列表中，即创建一个列表，然后调用

pd.DataFrame（data=my_data，headers=[col_name]）

我试着写了这篇文章，现在我得到了所有附加的表，但是如何过滤唯一的值，以便只有唯一的头出现在第一行中，这些产品在这些类别中按序列号分类？将所有结果附加到列表中，即制作列表，然后调用

pd.DataFrame（data=my_data，headers=[col_name]）

我尝试编写了这篇文章，现在我得到了所有附加的表，但是如何过滤唯一值，以便只有唯一的头出现在第一行中，这些产品在这些类别中按序列号归类？