title: extract multiple "td' classes from a table
body: <p>I have a site with many tables on it and I am looping through them and getting the data from all tables and exporting that to a csv file. The issue I have is that each table has multiple 'td' classes and I only want a couple of them but I don't know how to narrow them down to just what I want. 
  when I run my current code i get extra parts of the table that I don't want and it makes my csv file very messy.
  Here is a snippet of the html code for the page that contains the info I want. </p>
  
  <p><div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
  <div class="snippet-code">
  <pre class="snippet-code-html lang-html prettyprint-override"><code>&lt;tr class="table_title"&gt;
    &lt;td class="sportPicksBorderL2 tanBg fourleft regular" nowrap="nowrap"&gt;
      607 &lt;a class="black" href="/college-basketball/teams/team-page.cfm/team/oakland"&gt;OAKLND&lt;/a&gt;
    &lt;/td&gt;
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;&amp;nbsp;136.5&amp;nbsp;&lt;/td&gt;
  
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;28&lt;/td&gt;
  
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;32&lt;/td&gt;
  
  
    &lt;td class="sportPicksBorderL2 tanBg zerocenter sub_title_red" nowrap="nowrap"&gt;60&lt;/td&gt;
  
    &lt;td class="sportPicksBorderR2 tanBg zerocenter regular" nowrap="nowrap" width="100"&gt;Cover: +1.5&amp;nbsp;&lt;/td&gt;
  
  &lt;/tr&gt;
  &lt;tr class="table_title"&gt;
    &lt;td class="sportPicksBorderL2 tanBg fourleft regular" nowrap="nowrap"&gt;
      608 &lt;a class="black" href="/college-basketball/teams/team-page.cfm/team/youngstown-state"&gt;YOUNG&lt;/a&gt; &lt;span class="sub_title_red"&gt;«&lt;/span&gt;
    &lt;/td&gt;
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;&amp;nbsp;-2.5&amp;nbsp;&lt;/td&gt;
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;24&lt;/td&gt;
    &lt;td class="sportPicksBorderL2 tanBg zerocenter regular" nowrap="nowrap"&gt;37&lt;/td&gt;
  
    &lt;td class="sportPicksBorderL2 tanBg zerocenter sub_title_red" nowrap="nowrap"&gt;61&lt;/td&gt;
  
    &lt;td class="sportPicksBorderR2 tanBg zerocenter regular" nowrap="nowrap" width="100"&gt;Under: 121&amp;nbsp;&lt;/td&gt;
  
  &lt;/tr&gt;</code></pre>
  </div>
  </div>
  </p>
  
  <p>Here is what I run to extract my data</p>
  
  <pre><code>import bs4 as bs
  import urllib.request
  from requests import get
  import pandas as pd
  from csv import writer
  url = 'https://www.vegasinsider.com/college-basketball/scoreboard/scores.cfm/game_date/01-12-2020'
  source = urllib.request.urlopen(url)
  soup = bs.BeautifulSoup(source, 'lxml')
  tables = soup.find_all('table', attrs={'class': 'sportPicksBorder'})
  filename = 'C:\\Users\\mylocation\\Documents\\tables.csv'
  with open(filename, 'w')as f:
      data = []
      csv_writer = writer(f)
      for table in tables:
          rows = table.find_all('tr')
          for row in rows:
              columns = row.find_all('td')
              csv_writer.writerow([column.text.strip() for column in columns])
  </code></pre>
  
  <p>what I want is the a class="black"/a this has my team name without a red arrow by it
  class=sportPicksBorderL2
  class=sportPicksBorderR2</p>
  
  <p>My original code returns these 4 rows for each table.</p>
  
  <pre><code>Final Score Score                                                   
  Teams   Odds    1   2   T   ATS                                 
  847 ARIZNA  -4  31  34  65  Over: 147                                   
  848 OREGST Â«   143.5   31  51  82  Cover: +21
  </code></pre>
  
  <p>What I would like to keep from this is. </p>
  
  <pre><code>ARIZNA  -4  31  34  65  Over: 147                                   
  OREGST 143.5 31 51  82  Cover: +21
  </code></pre>
  
  <p>I want to strip off the Â«, the numbers before the team names, and the first 2 table rows from what I am scraping, but still being a novice in web scraping and python, am I finding it difficult to figure out. If anyone has a good training resource, i'm all ears.</p>