R Weekly 2018-42 RStudio, ORCID

15 Oct 2018

Highlight

• RStudio 1.2 Preview - C/C++ and Rcpp and Reticulated Python

• Distinguish yourself in CRAN person() with ORCID

• What’s new with R Consortium funded projects in Q3 2018

Insights

• Distinguish yourself in CRAN person() with ORCID

• How R gets built on Windows

• RStudio 1.2 Preview: C/C++ and Rcpp

• RStudio 1.2 Preview: Reticulated Python

• faster - Faster R with FastR

• The “Gold Standard” of Data Science Project Management

• Guest Post: Galin Jones on criteria for promotion and tenture in (bio)statistics departments

R in Organizations

• R Consortium grant applications due October 31

• What’s new with R Consortium funded projects in Q3 2018

R in the Real World

• Getting Census data from multiple states using tidycensus and purrr

• I utilized Charlie Thompson’s package “spotifyr” to analyze and cluter Kanye West albums

• Voice controlled Shiny apps

• GeoJSON Version of CBC Quebec Ridings Hex Cartograms with Example Usage in R

• Using the VoteView/NOMINATE model to investigate political ideologies in the 53rd New Mexico State Legislature.

• The Economist’s Big Mac Index is calculated with R

• Modeling airbnb prices

• Gender Analysis of the Pokémon Universe

• GitHub Streak: Round Five

• From 0 to 5: our journey of building an R-package ecosystem

• Understanding the limitations of group-level inequality data

• The economic consequences of MOOCs

Resources

• Presentations of the 6th Use of R in Official Statistics (uRos2018) are now online.

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• MCHT - A Package for Bootstrap and Monte Carlo Hypothesis Testing

GitHub or Bitbucket

• memoisetools - additional caches and helper functions to work alongside the memoise package

Package Releases

• RcppCCTZ 0.2.4 - Library for translating between absolute and civil times using the rules of a time zone.

• digest 0.6.18 - digest creates hash digests of arbitrary R objects

• binb 0.0.3: Now with Monash - A collection of ‘LaTeX’ styles using ‘Beamer’

Tutorials

• Make a trailer for your slidedeck with av

• Point-in-polygon using sf

• How to build your own Neural Network from scratch in R

• Quick Significance Calculations for A/B Tests in R

• Running the Same Task in Python and R

• Processing complicated package outputs

• The world (population) is changing

• Writing a function which respects dplyr::group_by()

• Parsing Metadata with R - A Package Story

• In regression, we assume noise is independent of all measured predictors. What happens if it isn’t?

• Automate the opening of Excel files in R

• Some R Guides: tidyverse and data.table Versions

• engroupify: A function to transform other functions to be aware of dplyr groups

• cransays - Follow your R Package Journey to CRANterbury with our Dashboard!

• Because it’s Friday: Hey, it’s Enrico Pallazzo!

Upcoming Events in 3 Months

Events in 3 Months:

• This week’s local R-User and applied stats events

More past events at R conferences & meetups.

Call for Participation

Your support will keep R Weekly team moving! 💡

Quotes of the Week

#IamABiologist @SheffieldAPS studying how loss & logging of tropical forests influences species' ability to cope with climate change. I've gone from frolicking in Borneo with a thermal camera to being a desk-based #rstats fanatic! pic.twitter.com/ciRIhenBZD

— Rebecca Senior (@RebeccaASenior) October 12, 2018

janitor::clean_names() is my new favorite #rstats function. If you're importing data that has spaces, special characters, and/or capitalization in the column names, give clean_names() a whirl. It just magically deals with all of that for you.

— Kim Cressman (@swmpkim) October 10, 2018