R Weekly 2019-13 R-hub, CII, C++

01 Apr 2019

Highlight

• R package developers, why should you care about R-hub?

• CII Best Practices – R Package Leaderboard

• Use of C++ in Packages

Insights

• Package licensing and enterprise use

• R package developers, why should you care about R-hub?

• Code challenge: find every way to create an identity matrix in R

• Choosing the best open source project (Github, Gitlab, etc.) depends on the quality of documentation, where it sits in the open-source life cycle, transparency, dependencies, and benchmarking.

• CII Best Practices – R Package Leaderboard

• Use of C++ in Packages

• #21: A Third and Final (?) Post on Stripping R Libraries

R in the Real World

• Rome Was Not Built In A Day But widgetcard Was!

• Better predictions for AFL from adjusted Elo ratings

• Web Scraping Amazon Reviews (March 2019)

• ELK+R Stack

• Shiny VS. Dash: A Side-by-side Comparison

• Super Dark IDE Theme, R-Studio, Inverted Color

• Sunny day at the office, and new mocha cup!

• no country for old liars

R in Organizations

• Summer Interns 2019

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• lconnect - patch connectivity metrics and patch prioritization

• February 2019: “Top 40” New CRAN Packages

GitHub or Bitbucket

• ggdebug - a package for debugging ggplot stats

• Human Face Detection with R

• dundermifflin

• gglabeller - Shiny gadget for labeling points on ggplot

Updated Packages

• drat 0.1.5 - Drat R Archive Template

R Internationally

• (German) Speeding up R Code: Loop vs. Vectorized function vs. Lookup-Table - What is faster than a for loop in R (almost any alternative) and faster than a vectorized function? Assigning values to 1000 Skat cards, the Lookup Table beats the vectorized function by far.

Tutorials

• What It the Interpretation of the Diagonal for a ROC Curve

• Use RStudio Server in a Virtual Environment with Docker in Minutes!

• Function factories, partial application & quasiquotation - FP with purrr & friends part 3

• How to create GPS heatmaps in ggplot

• With the #NFLDraft a month away, I am writing a series of blog posts about my data-informed approach to predicting the draft using mock draft data called “Grinding the Mocks” an homage to #DraftTwitter. First, a post laying out my theory of mock drafts with a link to my Shiny app that I created to aid in my analysis!

• R’s Killer Feature: RMarkdown is a short article aimed at total R newbies that explains what RMarkdown is and why it is so valuable.

• Drrrawing with purrr

• Useful tips to be more productive while working with R Studio.

• Multiplot with ggplot

• Subsetting Phylogenetic Trees

• Writing clean and readable R code the easy way

• Using RStudio and LaTeX

• R blogs I follow

• Create a dynamic number of UI elements in Shiny with purrr

• Thinking numbers in logarithms or in power? Scanning all of Wikipedia to find evidence for a 19th century psychophysics law

• Exercise in data wrangling and plot building by analyzing your Apple Health data in R

• Image-grid with Ninjutsu CSS theme in Xaringan

• nice student project

• Assessing Heterogeneity of Treatment Effect, Estimating Patient-Specific Efficacy, and Studying Variation in Odds ratios, Risk Ratios, and Risk Differences

• Getting started with emmeans

• Operator Notation for Data Transforms

• R code golf: the identity matrix

• (x=scan())%in%(2*4^(n=0:x)-2^n-1)

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• satRday Johannesburg - 6th April

• satRday Newcastle - 6th April

• satRday Los Angeles - 6th April

• The Uncoast Unconference - 14th to 16th April

• Tokyo.R #77 - 13th April

• A list of R conferences and meetings

• 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

Just spent 10 minutes trying to analyze a weird outlier in my boxplot, only to realize that it was food on my screen. TGIF

#rstats #statstwitter #epitwitter

— Lindsay Lucas (@StatsCurious) March 29, 2019

dplyr::coalesce() is very good #rstats pic.twitter.com/2bro5oq2iE

— tj mahr 🍕🍍 (@tjmahr) March 28, 2019

Animating motion capture data using dplyr, ggplot, and gganimate. Switched to R 1.5 year ago and never looked back.@thomasp85 #rstats pic.twitter.com/oBIXCag55S

— Steen Harsted (@SteenHarsted) March 28, 2019

TIL you can embed a "code download" button in an HTML #rmarkdown doc so that users can click to download your source .Rmd from the rendered HTML version...without GitHub 🤩 #rstats

YAML:

---
output:
html_document:
code_download: true
---

Test: https://t.co/bp7w7XKF8b pic.twitter.com/uMQK0mvYcF

— Alison Hill (@apreshill) March 22, 2019

It's official: UG teaching @Sussex_Psych is moving from SPSS to R next year. I'll be writing a new first year stats module from scratch! Any advice/resources from people who teach #Rstats at UG level/have made this switch in their methods teaching? #excitedandterrified

— Dr. Jennifer Mankin (@jenaesthesia) March 28, 2019