How many times have you wanted to find some information on a website only to be disappointed with the filtering and discovery options available. Learn how to get data from a site and look for the data that you really care about.
Unlocking the Future of AI Agents with Large Language Models
Mining the web, no experience required
1. Mining the web, no experience required.
Ruairí Fahy, 25th
October 2015
2. Scrapinghub - Who are we?
● Provider of cloud based web-crawling
solutions
● Builder of spiders and crawling
solutions
● Creator of open source projects like
Scrapy, Portia and Splash
● Find out more at scrapinghub.com
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
Splash
Portia
Scrapy
3. The Project
Obtain and compare house types and
prices across the country
● Build a spider for daft.ie using Portia
● Crawl daft.ie to obtain housing data
● Process the data using Pandas
● Visualise the data using CartoDB
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
4. The Basics
Web Scraping - The process of extracting
data from the web
Spider - A piece of software designed to
extract links and items from webpages
Crawl - Visit all pages of interest on a site
using your spider
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
5. Build a spider using Portia
● Portia is a tool for building spiders
without having to write any code.
● It has a simple UI for loading pages
that you want to extract data from.
● Create Samples by highlighting data
that you want on a page.
● Use these samples to train the
extraction algorithm.
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
https://github.com/scrapinghub/portia
6. Run our spider
● Scrapy Cloud - Hosted crawling at scrapinghub.com
● Scrapyd - Run your own server for crawling
● Portiacrawl - Run the spider locally using scrapy
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
7. Process our data with Pandas
● The spider has extracted the house type,
price, BER, number of bedrooms and
address for all houses for sale on daft.ie.
● Clean and normalise data
● Add a geopoint column so the houses can
be placed on a map.
● Process fields to prepare them for plotting
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015
Notebook: https://gist.github.com/ruairif/80102746320d0229a0ce
8. Visualise the data using CartoDB
● Create a dataset from our csv file
● Plot our data on a map
● Compare prices across the country
● Compare property type
● Compare BER
● http://cdb.io/1POBIU8
Mining the web, no experience required. - Ruairi Fahy, 25 October 2015 - Scrapinghub ⓒ 2015