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While I was in LA for the useR! 2014 conference last month, I had the great pleasure of being among the participants in the DataScienceLA interview series hosted by Eduardo Ariño de la Rubia. Eduardo is both an R user and an excellent interviewer: his preparation and knowledge of R has resuled in a fascinating interview series for any R user. 

by Norman Matloff

The American Statistical Association (ASA) leadership, and many in Statistics academia. have been undergoing a period of angst the last few years, They worry that the field of Statistics is headed for a future of reduced national influence and importance, with the feeling that:

I was visiting Napa Valley over the weekend, and at around 3:30AM on Sunday morning I awoke suddenly to what felt like some giant at the end of the bed shaking it as hard as he could. It was an earthquake. One of the scariest things about an earthquake is that when it happens, you have no idea how serious it is — you only know what it feels like where you are.

This entire movie — images, music, everything — is generated from a Windows PC executable of just 4,095 bytes. That's not a typo: we're not talking bytes not megabytes or gigabytes here. Less than 4kb total creates this entire scene.

 

By Neera Talbert, VP Services and Ben Wiley, R Programmer at Revolution Analytics

by Joseph Rickert

We are pleased to announce that Jo-fai Chow is the winner of the Revolution Analytics contest. Jo-fai’s entry, which was implemented as a Shiny project, may be viewed by clicking on the figure below.

 

Hilary Parker has contributed a lovely article to Significance, the magazine of the American Statistical Association and the Royal Statistical Society, on using R to set your Google calendar to mark the time of sunsets.

by Nick Elprin, Co-Founder of Domino Data Lab

We built a platform that lets analysts deploy R code to an HTTP server with one click, and we describe it in detail below.  If you have ever wanted to invoke your R model with a simple HTTP call, without dealing with any infrastructure setup or asking for help from developers — imagine Heroku for your R code — we hope you’ll enjoy this.

Introduction

A New York Times article yesterday discovers the 80-20 rule: that 80% of a typical data science project is sourcing cleaning and preparing the data, while the remaining 20% is actual data analysis. The article gives short shrift to this important task by calling it "janitorial work", but whether you call it data munging, data wrangling or anything else, it's a critical part of the data science.

There's a lot of great video on YouTube, and also a lot of boring video that could be interesting if only it was shorter. But speeding up video just amplifies the camera shake to the point of motion sickness. Microsoft has solved that problem with Hyperlapse, which does for video what Panorama mode did for photography:

 

You can learn more about how it's done in this video, or at the Hyperlapse website.