Many thanks to all who attended the talk @jayjacobs & I gave at RSA on Tuesday, February 26, 2013. It was really great to be able to talk to so many of you afterwards as well.<\/p>\n
We’ve enumerated quite a bit of non-slide-but-in-presentation information that we wanted to aggregate into a blog post so you can viz along at home. If you need more of a guided path, I strongly encourage you to take a look at some of the free courses over at [Coursera](https:\/\/www.coursera.org\/).<\/p>\n
For starters, here’s a bit.ly bundle<\/span> of data analysis & visualization bookmarks that @dseverski & I maintain. We’ve been doing (IMO) a pretty good job adding new resources as they come up and may have some duplicates to the ones below.<\/p>\n – [Stephen Few’s Perceptual Edge blog](http:\/\/www.perceptualedge.com\/) : Start from the beginning to learn from a giant in information visualization – [R](http:\/\/www.r-project.org\/) : Jay & I probably use this a bit too much as a hammer (i.e. treat ever data project as a nail) but it’s just far too flexible and powerful to not use as a go-to resource Many thanks to all who attended the talk @jayjacobs & I gave at RSA on Tuesday, February 26, 2013. It was really great to be able to talk to so many of you afterwards as well. We’ve enumerated quite a bit of non-slide-but-in-presentation information that we wanted to aggregate into a blog post so you […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[24,666,677,678,673,674,670,3,87],"tags":[],"class_list":["post-2190","post","type-post","status-publish","format-standard","hentry","category-charts-graphs","category-d3","category-data-analysis-2","category-data-visualization","category-datavis-2","category-dataviz","category-infographics","category-information-security","category-open-source"],"yoast_head":"\nPeople Mentioned<\/h3>\n
\n– [Andy Kirk’s Visualising Data blog](http:\/\/www.visualisingdata.com\/) (@visualisingdata) : Perhaps the quintessential leader in the modern visualization movement.
\n– [Mike Bostock’s blog](http:\/\/bost.ocks.org\/mike\/) (@mbostock) : Creator of D3 and producer of amazing, interactive graphics for the @NYTimes
\n– [Edward Tufte’s blog](http:\/\/www.edwardtufte.com\/tufte\/) : The father of what we would now identify as our core visualization principles & practices<\/p>\nTools Mentioned<\/h3>\n
\n– [RStudio](http:\/\/www.rstudio.com\/) : An *amazing* IDE for R. I, personally, usually despise IDEs (yes, I even dislike Xcode), but RStudio truly improves workflow by several orders of magnitude. There are both desktop and server versions of it; the latter gives you the ability to setup a multi-user environment and use the IDE from practically anywhere you are. RStudio also makes generating [reproducible research](http:\/\/cran.r-project.org\/web\/views\/ReproducibleResearch.html) a joy with built-in easy access to tools like [kintr](http:\/\/yihui.name\/knitr\/).
\n– [iPython](http:\/\/ipython.org\/) : This version of Python takes an already amazing language and kicks it up a few notches. It brings it up to the level of R+RStudio, especially with it’s knitr-like [iPython Notebooks](http:\/\/ipython.org\/ipython-doc\/dev\/interactive\/htmlnotebook.html) for\u2013again\u2013reproducible research.
\n– [Mondrian](http:\/\/www.theusrus.de\/Mondrian\/) : This tool needs far more visibility. It enables extremely quick visualization of even very large data sets. The interface takes a bit of getting used to, but it’s faster then typing R commands or fumbling in Excel.
\n– [Tableau](http:\/\/www.tableausoftware.com\/) : This tool may be one of the most accessible, fast & flexible ways to explore data sets to get an idea of where you need to\/can do further analysis.
\n– [Processing](http:\/\/processing.org\/) : A tool that was designed from the ground up to help journalists create powerful, interactive data visualizations that you can slipstream directly onto the web via the [Processing.js](http:\/\/processingjs.org\/) library.
\n– [D3](http:\/\/d3js.org\/) : The foundation of modern, data-driven visualization on the web.
\n– [Gephi](https:\/\/gephi.org\/) : A very powerful tool when you need to explore networks & create beautiful, publication-worthy visualizations.
\n– [MongoDB](http:\/\/www.mongodb.org\/) : NoSQL database that’s highly & easily scaleable without a steep learning curve.
\n– [CRUSH Tools by Google](https:\/\/code.google.com\/p\/crush-tools\/) : Kicks up your command-line data munging.<\/p>\n","protected":false},"excerpt":{"rendered":"