title: How to use Python (preferably pandas) to scrape data from Javascript table?
body: <p>I am using pandas to grab some ice hockey stats from a web page as shown below:</p>
  
  <pre><code>import pandas as pd
  
  url_goal = 'http://www.quanthockey.com/nhl/records/nhl-players-all-time-goals-per-game-leaders.html'
  df_goal = pd.read_html(url_goal, index_col=0, header=0)[0]
  </code></pre>
  
  <p>This works great, but the problem is that switching to the second page of the stats table on the homepage, does not change the url, so I cannot use the same approach to grab more than the top 50 players. There is a javascript address to the table that does change as the page number switches. I read a little about selenium and beautifulsoup, but I don't have these installed so I would prefer to do it without them is possible. So my question is two-fold:</p>
  
  <ol>
  <li><p>Is there any way to grab data from the different pages in this
  javascript table using only pandas and standard Python/SciPy
  libraries (Anaconda to be exact)?</p></li>
  <li><p>If not, how would you go about getting this data into a pandas data frame with the help of selenium or your package of choice?</p></li>
  </ol>