请你访问https://book.douban.com/top250，获取的数据内容：作者、 出版社、 出版年、 页数、 定价、装帧、ISBN、评分、39408人在读、569770人读过、157297人想读，按此顺序显示在屏幕中，其中使用select方法实现

很抱歉，作为一个AI模型，我无法直接访问网页并提取数据。不过，我可以为您提供使用Python语言和第三方库（如BeautifulSoup、requests等）来实现该功能的代码示例，您可以尝试运行并进行修改。以下是示例代码：

import requests
from bs4 import BeautifulSoup

url = 'https://book.douban.com/top250'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, 'html.parser')
book_list = soup.select('.indent > table > tbody > tr')

for book in book_list:
    title = book.select_one('.pl2 > a')['title']
    author = book.select_one('.pl > a').text.strip()
    info = book.select_one('.pl').next_sibling.strip().split('/')
    publisher = info[-3].strip()
    year = info[-2].strip()
    pages = info[-1].strip()
    price = book.select_one('.pl').next_sibling.next_sibling.strip()
    binding = book.select_one('.pl').next_sibling.next_sibling.next_sibling.strip()
    isbn = book.select_one('.pl2 > span')['title'].strip()
    rating = book.select_one('.rating_nums').text.strip()
    rating_count = book.select_one('.star > span').next_sibling.next_sibling.text.strip()
    reading_count = book.select_one('.pl').next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.text.strip()
    read_count = book.select_one('.pl').next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.text.strip()
    want_count = book.select_one('.pl').next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.text.strip()
    print(f'{author} | {publisher} | {year} | {pages} | {price} | {binding} | {isbn} | {rating} | {reading_count} | {read_count} | {want_count}')

注意，该代码使用了select方法来选择HTML元素，其中用到了CSS选择器的语法。如果您对此不熟悉，可以先学习一下CSS选择器的基本用法。同时，为了避免反爬虫机制，代码中添加了headers信息来模拟浏览器请求。