Outils, ressources
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Data Science Toolkit
API: /street2coordinates Street Address to Location calculates the latitude/longitude coordinates for a postal address. Currently restricted to the US and UK.
Think Stats is an introduction to Probability and Statistics for Python programmers.
Think Stats: Probability and Statistics for Programmers
Rapport sur le développement humain 2011, Programme des Nations Unies pour de développement Les données utilisées pour calculer l'Indice de développement humain (IDH) et autres indices composites présentés dans le Rapport sur le développement humain ... données sur le chômage harmonisé pour les pays européens.
Public Data Explorer
L’indice du coût de la construction (ICC) s’établit à 1 638 au quatrième trimestre 2011 après 1 624 au trimestre précédent. En glissement annuel, l’ICC augmente de 6,85 %, après une hausse de 6,84 %, ... En 2010, 251 654 mariages ont été enregistrés en France, dont 245 334 en France métropolitaine.
INSEE
It's been a little over a year since we first announced the V2 engine. After many months of work and help from the Pipes developer community, all Pipes now are running off our new V2 engine! Special thanks to hapdaniel and libra_sun for reporting issues and making V2 a better engine.
Pipes: Rewire the web
So here’s a quick summary of (part of) what I found I could do. The Google spreadsheet function =importHTML(“”,”table”,N) will scrape a table from an HTML web page into a Google spreadsheet. The URL of the target web page, and the target table element both need to be in double quotes. The number N identifies the N’th table in the page (counting starts at 0) as the target table for data scraping. So for example, have a look at the following Wikipedia page – List of largest United Kingdom settlements by population (found using a search on Wikipedia for uk city population ): As well publishing the spreadsheet as an HTML page that anyone can see (and that is pulling data from the WIkipedia page, remember), you can also get access to an RSS feed of the data – and a host of other data formats:
Data Scraping Wikipedia with Google Spreadsheets « OUseful.Info, the blog…
Last night OpenHeatMap creator Pete Warden announced that the tool now allowed you to visualise UK data . I’ve been gleefully playing with the heat-mapping tool today and thought I’d share some pointers on visualising data on a map. This is not a tutorial for OpenHeatMap – Pete’s done a great job of that himself (video below) – but rather an outline of the steps to get some map-ready data in the first place. You firstly need data that fits the geographical areas supported by OpenHeatMap (countries, constituencies, local authorities, districts and counties), and which suits geographical visualisation. My first stop was the data.gov.uk RSS feed to see what recent datasets had been released, but you could also do advanced searches for “unemployment by county” etc. if you are looking for something specific to visualise. Helpfully, each dataset description includes a field on “Geographical granularity”.
Playing with heat-mapping UK data on OpenHeatMap | Online Journalism Blog
Photo by Dan Nguyen/ProPublica Our Dollars for Docs news application [1] lets readers search pharmaceutical company payments to doctors. We’ve written a series of how-to guides explaining how we collected the data. Most of the techniques are within the ability of the moderately experienced programmer. The most difficult-to-scrape site [2] was actually a previous Adobe Flash incarnation [3] of Eli Lilly’s disclosure site.
Scraping for Journalism: A Guide for Collecting Data - ProPublica
Exhibit : "enables you to create html pages with dynamic exhibits of data collections without resorting to complex database and server-side technologies.
digitalresearchtools / Data Visualization
CAR 2011 was stuffed full of information, so much so that the only way to keep up with everything has been to keep a log of what people have been sharing.
Data Visualization Tools, Slides and Links from NICAR11 // Ricochet by Chrys Wu