R World News | Listen Notes


A weekly digest of latest packages, papers, blog posts and happenings in the R world, plus book reviews and interviews with those involved in the R community.
2 episodes
since May, 2016


R World News — Episode 2

R World News - Episode 2 R 3.3.0 is here with a host of new features, many aimed at those that do R package development. (http://r.789695.n4.nabble.com/R-3-3-0-is-released-td4720368.html). The repr package (https://cran.r-project.org/web/packages/repr/README.html) by Philipp A., Thomas Kluyver, Jan Schulz, abielr, Denilson Figueiredo de Sa, Jim Hester & karldw is on CRAN. While it was designed to support the IRKernel (the R kernel) of IPytyon and (now) Jupyter notebooks, it provides core functionality to reliably create readable text (and viewable image) representations of data without the side effects print() can cause, such as invoking a pager and plotting to a plot device. In other words, all repr functions and methods are pure. It will also be able to enhance knit output and potentially replace R CMD Rd2pdf. acs (https://cran.r-project.org/web/packages/acs/README.html) is at version 2.0 and provides a general toolkit for downloading, managing, analyzing, and presenting data from the U.S. Census, including SF1 (Decennial short-form), SF3 (Decennial long-form), and the American Community Survey (ACS). Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. Package provides new methods to conduct standard operations on acs objects and present/plot data in statistically appropriate ways. Current version is 2.0 +/- .033. Support for the 2014 ACS is now provided (no more bare API calls!) ShinyDevCon happened earlier this year and the vides are now up! (https://blog.rstudio.org/2016/05/05/shinydevcon-videos-now-available/), We bring on Bhaskar Karambelkar (https://twitter.com/bhaskar_vk) to give us the attendee's view of what to watch first. Finally we talk about Docker Beta for Mac OS X & Windows and how it fits super-well into the R ecosystem thanks to rocker (https://github.com/rocker-org/rocker).


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