How can I scrape an HTML table to CSV?

user_4376 0
Viewed 82410

The Problem

I use a tool at work that lets me do queries and get back HTML tables of info. I do not have any kind of back-end access to it.

A lot of this info would be much more useful if I could put it into a spreadsheet for sorting, averaging, etc. How can I screen-scrape this data to a CSV file?

My First Idea

Since I know jQuery, I thought I might use it to strip out the table formatting onscreen, insert commas and line breaks, and just copy the whole mess into notepad and save as a CSV. Any better ideas?

The Solution

Yes, folks, it really was as easy as copying and pasting. Don't I feel silly.

Specifically, when I pasted into the spreadsheet, I had to select "Paste Special" and choose the format "text." Otherwise it tried to paste everything into a single cell, even if I highlighted the whole spreadsheet.

screen-scraping
11 Answers
  • Select the HTML table in your tools's UI and copy it into the clipboard (if that's possible
  • Paste it into Excel.
  • Save as CSV file

However, this is a manual solution not an automated one.

mkoeller_334330

using python:

for example imagine you want to scrape forex quotes in csv form from some site like:fxquotes

then...

from BeautifulSoup import BeautifulSoup
import urllib,string,csv,sys,os
from string import replace

date_s = '&date1=01/01/08'
date_f = '&date=11/10/08'
fx_url = 'http://www.oanda.com/convert/fxhistory?date_fmt=us'
fx_url_end = '&lang=en&margin_fixed=0&format=CSV&redirected=1'
cur1,cur2 = 'USD','AUD'
fx_url = fx_url + date_f + date_s + '&exch=' + cur1 +'&exch2=' + cur1
fx_url = fx_url +'&expr=' + cur2 +  '&expr2=' + cur2 + fx_url_end
data = urllib.urlopen(fx_url).read()
soup = BeautifulSoup(data)
data = str(soup.findAll('pre', limit=1))
data = replace(data,'[<pre>','')
data = replace(data,'</pre>]','')
file_location = '/Users/location_edit_this'
file_name = file_location + 'usd_aus.csv'
file = open(file_name,"w")
file.write(data)
file.close()

edit: to get values from a table: example from: palewire

from mechanize import Browser
from BeautifulSoup import BeautifulSoup

mech = Browser()

url = "http://www.palewire.com/scrape/albums/2007.html"
page = mech.open(url)

html = page.read()
soup = BeautifulSoup(html)

table = soup.find("table", border=1)

for row in table.findAll('tr')[1:]:
    col = row.findAll('td')

    rank = col[0].string
    artist = col[1].string
    album = col[2].string
    cover_link = col[3].img['src']

    record = (rank, artist, album, cover_link)
    print "|".join(record)
user_357810

Even easier (because it saves it for you for next time) ...

In Excel

Data/Import External Data/New Web Query

will take you to a url prompt. Enter your url, and it will delimit available tables on the page to import. Voila.

doofledorfer_316410

Quick and dirty:

Copy out of browser into Excel, save as CSV.

Better solution (for long term use):

Write a bit of code in the language of your choice that will pull the html contents down, and scrape out the bits that you want. You could probably throw in all of the data operations (sorting, averaging, etc) on top of the data retrieval. That way, you just have to run your code and you get the actual report that you want.

It all depends on how often you will be performing this particular task.

James_Van_Huis_318280

Excel can open a http page.

Eg:

  1. Click File, Open

  2. Under filename, paste the URL ie: How can I scrape an HTML table to CSV?

  3. Click ok

Excel does its best to convert the html to a table.

Its not the most elegant solution, but does work!

Christian_Payne_51880

Have you tried opening it with excel? If you save a spreadsheet in excel as html you'll see the format excel uses. From a web app I wrote I spit out this html format so the user can export to excel.

Will_Rickards_2908350

If you're screen scraping and the table you're trying to convert has a given ID, you could always do a regex parse of the html along with some scripting to generate a CSV.

andy_312290
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