Python - Web Scraping HTML table and printing to CSV

I'm pretty much brand new to Python, but I'm looking to build a webscraping tool that will rip data from an HTML table online and print it into a CSV in the same format.

Here's a sample of the HTML table (it's enormous, so I'm going to provide only a few rows).

<div class="col-xs-12 tab-content">
        <div id="historical-data" class="tab-pane active">
          <div class="tab-header">
            <h2 class="pull-left bottom-margin-2x">Historical data for Bitcoin</h2>

            <div class="clear"></div>

            <div class="row">
              <div class="col-md-12">
                <div class="pull-left">
                  <small>Currency in USD</small>
                </div>
                <div id="reportrange" class="pull-right">
                    <i class="glyphicon glyphicon-calendar fa fa-calendar"></i>&nbsp;
                    <span>Aug 16, 2017 - Sep 15, 2017</span> <b class="caret"></b>
                </div>
              </div>
            </div>

            <table class="table">
              <thead>
              <tr>
                <th class="text-left">Date</th>
                <th class="text-right">Open</th>
                <th class="text-right">High</th>
                <th class="text-right">Low</th>
                <th class="text-right">Close</th>
                <th class="text-right">Volume</th>
                <th class="text-right">Market Cap</th>
              </tr>
              </thead>
              <tbody>

                <tr class="text-right">
                  <td class="text-left">Sep 14, 2017</td>
                  <td>3875.37</td>     
                  <td>3920.60</td>
                  <td>3153.86</td>
                  <td>3154.95</td>
                  <td>2,716,310,000</td>
                  <td>64,191,600,000</td>
                </tr>

                <tr class="text-right">
                  <td class="text-left">Sep 13, 2017</td>
                  <td>4131.98</td>     
                  <td>4131.98</td>
                  <td>3789.92</td>
                  <td>3882.59</td>
                  <td>2,219,410,000</td>
                  <td>68,432,200,000</td>
                </tr>

                <tr class="text-right">
                  <td class="text-left">Sep 12, 2017</td>
                  <td>4168.88</td>     
                  <td>4344.65</td>
                  <td>4085.22</td>
                  <td>4130.81</td>
                  <td>1,864,530,000</td>
                  <td>69,033,400,000</td>
                </tr>                
              </tbody>
            </table>
          </div>

        </div>
    </div>

I'm particularly interested in recreating the table with the same column headers provided: "Date," "Open," "High," "Low," "Close," "Volume," "Market Cap." Currently, I've been able to write a simple script that will essentially go to the URL, download the HTML, parse with BeautifulSoup, and then use 'for' statements to get the td elements. Below a sample of my code (URL omitted) and the result:

from bs4 import BeautifulSoup
import requests
import pandas as pd
import csv

url = "enterURLhere"
page = requests.get(url)
pagetext = page.text

pricetable = {
    "Date" : [],
    "Open" : [],
    "High" : [],
    "Low" : [],
    "Close" : [],
    "Volume" : [],
    "Market Cap" : []
}

soup = BeautifulSoup(pagetext, 'html.parser')

file = open("test.csv", 'w')

for row in soup.find_all('tr'):
    for col in row.find_all('td'):
        print(col.text)

sample output

Anyone have any pointers on how to at least reformat the data pull into the table? Thanks.