13

晚上好，我使用 BeautifulSoup 从网站中提取了一些数据，如下所示：

from BeautifulSoup import BeautifulSoup
from urllib2 import urlopen

soup = BeautifulSoup(urlopen('http://www.fsa.gov.uk/about/media/facts/fines/2002'))

table = soup.findAll('table', attrs={ "class" : "table-horizontal-line"})

print table

这给出了以下输出：

[<table width="70%" class="table-horizontal-line">
<tr>
<th>Amount</th>
<th>Company or person fined</th>
<th>Date</th>
<th>What was the fine for?</th>
<th>Compensation</th>
</tr>
<tr>
<td><a name="_Hlk74714257" id="_Hlk74714257">&#160;</a>£4,000,000</td>
<td><a href="/pages/library/communication/pr/2002/124.shtml">Credit Suisse First Boston International </a></td>
<td>19/12/02</td>
<td>Attempting to mislead the Japanese regulatory and tax authorities</td>
<td>&#160;</td>
</tr>
<tr>
<td>£750,000</td>
<td><a href="/pages/library/communication/pr/2002/123.shtml">Royal Bank of Scotland plc</a></td>
<td>17/12/02</td>
<td>Breaches of money laundering rules</td>
<td>&#160;</td>
</tr>
<tr>
<td>£1,000,000</td>
<td><a href="/pages/library/communication/pr/2002/118.shtml">Abbey Life Assurance Company ltd</a></td>
<td>04/12/02</td>
<td>Mortgage endowment mis-selling and other failings</td>
<td>Compensation estimated to be between £120 and £160 million</td>
</tr>
<tr>
<td>£1,350,000</td>
<td><a href="/pages/library/communication/pr/2002/087.shtml">Royal &#38; Sun Alliance Group</a></td>
<td>27/08/02</td>
<td>Pension review failings</td>
<td>Redress exceeding £32 million</td>
</tr>
<tr>
<td>£4,000</td>
<td><a href="/pubs/final/ft-inv-ins_7aug02.pdf" target="_blank">F T Investment &#38; Insurance Consultants</a></td>
<td>07/08/02</td>
<td>Pensions review failings</td>
<td>&#160;</td>
</tr>
<tr>
<td>£75,000</td>
<td><a href="/pubs/final/spe_18jun02.pdf" target="_blank">Seymour Pierce Ellis ltd</a></td>
<td>18/06/02</td>
<td>Breaches of FSA Principles ("skill, care and diligence" and "internal organization")</td>
<td>&#160;</td>
</tr>
<tr>
<td>£120,000</td>
<td><a href="/pages/library/communication/pr/2002/051.shtml">Ward Consultancy plc</a></td>
<td>14/05/02</td>
<td>Pension review failings</td>
<td>&#160;</td>
</tr>
<tr>
<td>£140,000</td>
<td><a href="/pages/library/communication/pr/2002/036.shtml">Shawlands Financial Services ltd</a> - formerly Frizzell Life &#38; Financial Planning ltd)</td>
<td>11/04/02</td>
<td>Record keeping and associated compliance breaches</td>
<td>&#160;</td>
</tr>
<tr>
<td>£5,000</td>
<td><a href="/pubs/final/woodwards_4apr02.pdf" target="_blank">Woodward's Independent Financial Advisers</a></td>
<td>04/04/02</td>
<td>Pensions review failings</td>
<td>&#160;</td>
</tr>
</table>]

我想将其导出为 CSV，同时保持网站上显示的表格结构，这可能吗？如果可以，如何？

在此先感谢您的帮助。

4

1 回答 1

27

这是您可以尝试的基本操作。这假设所有数据headers都在<th>标签中，并且所有后续数据都在<td>标签中。这适用于您提供的单一案例，但我确信如果其他案例有必要进行调整:) 一般的想法是，一旦您找到您的table（这里使用find拉第一个），我们headers通过迭代所有th元素来获得，将它们存储在列表中。然后，我们创建一个rows列表，其中包含表示每行内容的列表。这是通过查找标签td下的所有元素并采用, 将其编码为 UTF-8（来自 Unicode）来填充的。然后你打开一个 CSV，写第一个，然后写所有trtextheadersrows, but using(row for row in rows if row)` 以消除任何空白行）：

In [117]: import csv

In [118]: from bs4 import BeautifulSoup

In [119]: from urllib2 import urlopen

In [120]: soup = BeautifulSoup(urlopen('http://www.fsa.gov.uk/about/media/facts/fines/2002'))

In [121]: table = soup.find('table', attrs={ "class" : "table-horizontal-line"})

In [122]: headers = [header.text for header in table.find_all('th')]

In [123]: rows = []

In [124]: for row in table.find_all('tr'):
   .....:     rows.append([val.text.encode('utf8') for val in row.find_all('td')])
   .....: 

In [125]: with open('output_file.csv', 'wb') as f:
   .....:     writer = csv.writer(f)
   .....:     writer.writerow(headers)
   .....:     writer.writerows(row for row in rows if row)
   .....: 

In [126]: cat output_file.csv
Amount,Company or person fined,Date,What was the fine for?,Compensation
" £4,000,000",Credit Suisse First Boston International ,19/12/02,Attempting to mislead the Japanese regulatory and tax authorities, 
"£750,000",Royal Bank of Scotland plc,17/12/02,Breaches of money laundering rules, 
"£1,000,000",Abbey Life Assurance Company ltd,04/12/02,Mortgage endowment mis-selling and other failings,Compensation estimated to be between £120 and £160 million
"£1,350,000",Royal & Sun Alliance Group,27/08/02,Pension review failings,Redress exceeding £32 million
"£4,000",F T Investment & Insurance Consultants,07/08/02,Pensions review failings, 
"£75,000",Seymour Pierce Ellis ltd,18/06/02,"Breaches of FSA Principles (""skill, care and diligence"" and ""internal organization"")", 
"£120,000",Ward Consultancy plc,14/05/02,Pension review failings, 
"£140,000",Shawlands Financial Services ltd - formerly Frizzell Life & Financial Planning ltd),11/04/02,Record keeping and associated compliance breaches, 
"£5,000",Woodward's Independent Financial Advisers,04/04/02,Pensions review failings,
于 2013-01-05T02:22:20.560 回答