1871 search results for "RSTUDIO"

Shiny Developer Conference

January 31, 2016
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Shiny Developer Conference

Really enjoying RStudio‘s Shiny Developer Conference | Stanford University | January 2016. Winston Chang just demonstrated profvis, really slick. You can profile code just by wrapping it in a profvis({}) block and the results are exported as interactive HTML widgets. For example, running the R code below: if(!('profvis' %in% rownames(installed.packages()))) { devtools::install_github('rstudio/profvis') } library('profvis') nrow … Continue reading...

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R Tagosphere!

January 31, 2016
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R Tagosphere!

This post explores the inter-relationships of StackOverflow Tags for R-related questions. So I grabbed all the questions tagged with “r”, took the other tags in each question and made some network charts that show how often each tag is seen with the other tags. The point is to see the empirical relationships …

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The R-Podcast Episode 16: Interview with Dean Attali

January 30, 2016
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Direct from the first-ever Shiny Developer conference, here is episode 16 of the R-Podcast! In this episode I sit down with Dean Attali for an engaging conversation about his journey to using R, his motivation for creating the innovative shinyjs packa...

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Need any more reason to love R-Shiny? Here: you can even use Shiny to create simple games!

January 26, 2016
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Need any more reason to love R-Shiny? Here: you can even use Shiny to create simple games!

Anyone who reads my blog posts knows by now that I’m very enthusiastic about Shiny (the web app framework for R - if you didn’t know what Shiny is then I suggest reading my previous post about it). One of my reasons for liking Shiny so much is that you can do so much more with it than...

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Bayesian regression with STAN Part 2: Beyond normality

January 26, 2016
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Bayesian regression with STAN Part 2: Beyond normality

In a previous post we saw how to perform bayesian regression in R using STAN for normally distributed data. In this post we will look at how to fit non-normal model in STAN using three example distributions commonly found in empirical data: negative-binomial (overdispersed poisson data), gamma (right-skewed continuous data) and beta-binomial (overdispersed binomial data).

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Using webp in R: A New Format for Lossless and Lossy Image Compression

January 24, 2016
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Using webp in R: A New Format for Lossless and Lossy Image Compression

A while ago I blogged about the brotli, a new general purpose compression algorithm which Google promotes as an alternative to gzip. The same company also happens to be working on a new format for images called webp, which is actually a derivative of the VP8 video format. Google claims...

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Fun Data for teaching R

January 21, 2016
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Fun Data for teaching R

I’ll be running an R course soon and I am looking for fun (public) datasets to use in data manipulation and visualization. I would like to use a single dataset that has some easy variables for the first days, but … Continue reading →

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100 “must read” R-bloggers’ posts for 2015

January 20, 2016
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100 “must read” R-bloggers’ posts for 2015

The site R-bloggers.com is now 6 years young. It strives to be an (unofficial) online news and tutorials website for the R community, written by over 600 bloggers who agreed to contribute their R articles to the website. In 2015, the site served almost 17.7 million pageviews to readers worldwide. In celebration to R-bloggers’ 6th birth-month, here are the top 100 most read R posts written...

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Shiny 0.13.0

January 20, 2016
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Shiny 0.13.0

Shiny 0.13.0 is now available on CRAN! This release has some of the most exciting features we’ve shipped since the first version of Shiny. Highlights include: Shiny Gadgets HTML templates Shiny modules Error stack traces Checking for missing inputs New JavaScript events For a comprehensive list of changes, see the NEWS file. To install the

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R trends in 2015 (based on cranlogs)

January 20, 2016
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It is always fun to look back and reflect on the past year. Inspired by Christoph Safferling's post on top packages from published in 2015, I decided to have my own go at the top R trends of 2015. Contrary to Safferling's post I'll try to also (1) look at packages from previous years that hit the big...

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