Blog Archives

Color: The Cinderella of dataviz

March 13, 2009
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Color:  The Cinderella of dataviz

“Avoiding catastrophe becomes the first principle in bringing color to information: Above all, do no harm.”  — Envisioning Information, Edward Tufte, Graphics Press, 1990    Color is one of the most abused and neglected tools in data visualization. It is abused when we make poor color choices; it is neglected when we rely on poor software

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People who love scatter plots & connecting dots

February 20, 2009
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People who love scatter plots & connecting dots

We hosted the first Dataviz Salon SF on Tuesday night, with lightning talks by boredom cop Shane Booth, dataviz wiz Lee Byron , computational journalist Brad Stenger, data wrangler Pete Skomoroch , and any/all data enthusiast Brendan O’Connor . I was going to blog all about it — but Tom Carden of Stamen Design already

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How Google and Facebook are using R

February 19, 2009
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How Google and Facebook are using R

(March 26th Update: Video now available) Last night, I moderated our Bay Area R Users Group kick-off event with a panel discussion entitled “The R and Science of Predictive Analytics”, co-located with the Predictive Analytics World conference here in SF. The panel comprised of four recognized R users from industry: Bo Cowgill, Google Itamar Rosenn,

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What I’ll be presenting at O’Reilly Money Tech 2009

October 21, 2008
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What I’ll be presenting at O’Reilly Money Tech 2009

(April 2009 Update:  Unfortunately, The Money Tech Conference was indefinitely postponed, but fortunately I will be presenting a version of this talk in July at OSCON 2009). I’ve been invited to speak at O’Reilly’s Money Tech conference this coming February 4-6th in New York City and thought I’d share the abstract for my talk here.  I’ll

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How do you measure a major league slugger?

September 1, 2008
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How do you measure a major league slugger?

I gave a talk last month at SAP Labs in Palo Alto, along with Jim Porzak of ResponSys, introducing the R Statistical Language to a Business Intelligence interest group.  The goal was to highlight how open source tools, like R, can be used to build predictive models.  The example I gave centered around baseball and

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