R Weekly 2019-46 Autoconf, {tune}, {leaflet}

18 Nov 2019

Release Date: 2019-11-18

This week’s release was curated by Jonathan Carroll, with help from the RWeekly team members and contributors.

Highlight

• An Autoconf Primer for R Package Authors
• Testing the tune package from tidymodels
• A more convincing Leaflet visualizations from R - customizing markers, icons, color scales & HTML popups.

Insights

• future 1.15.0 - Lazy Futures are Now Launched if Queried
• Statistical uncertainty with R and pdqr
• An Autoconf Primer for R Package Authors

• An API for @racently
• When Cross-Validation is More Powerful than Regularization
• workloopR: Analysis of work loops and other data from muscle physiology experiments in R
• #30DayMapChallenge: 30 days building maps (2) - tmap
• An htmlwidget to visualise large monopartite graphs.
• Visualize urban growth in Spain
• Calculating (Twitter) Vocabulary Breadth of U.S. Presidential Candidates Using Type-Token Ratio (TTR)
• A Shiny App visualising the CRAN Dependency graph

• Analyzing restaurants visited last 12 months
• Testing the tune package from tidymodels
• Best practices for setting automated test architecture for Shiny apps
• Generating Oxford Comma triples and generating sequentially numbered BibTeX entries
• space = “free” or how to fix your facet (width)
• Import and work with formatted spreadsheet data

• For advanced R Shiny applications, R6 classes help you organize your code.
• Breast cancer awareness campaign with Swedish incidence and mortality data.
• Softcoding Constants in the App
• Follow a spatial particle over a raster map in 3D using rayshader
• Exploring highcharts in R
• Javascript is your friend
• Mapping the underlying social structure of Reddit
• Rugby World Cup history with ggalluvial

• Using session data
• Understanding the concept of variance explained.
• My R Journey: Jon Harmon

R in the Real World

• Area Under Curve of Daily Temperature Oscillation as a Temperature Unpleasantness Index
• How news media are setting the 2020 election agenda: Chasing daily controversies, often burying policy

R in Organizations

• The NHS-R Conference 2019

R in Academia

• Advances in Machine Learning for the Behavioral Sciences Kliegr, T., Bahník, Š., & Fürnkranz, J. (2019). Advances in Machine Learning for the Behavioral Sciences. American Behavioral Scientist. https://doi.org/10.1177/0002764219859639
• List-columns in {data.table}: Nesting and unnesting data tables and vectors

Resources

• {kakashi} theme for {xaringan} slides
• Practical Data Science with R, 2nd Edition, IS OUT!!!!!!!

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {pdqr} 0.2.0: Work with Custom Distribution Functions
• {varycoef} 0.2.9: An R Package to Model Spatially Varying Coefficients
• {VancouvR} 0.1.1: Access the ‘City of Vancouver’ Open Data API
• {azuremlsdk} 0.5.7: Interface to the ‘Azure Machine Learning’ ‘SDK’
• {chk} 0.2.0: Check User-Supplied Function Arguments
• {dietr} 1.0: Diet Estimated Trophic Levels
• {docknitr} 0.4.0: Use Docker Images to Process Rmarkdown Blocks
• {dupree} 0.2.0: Identify Duplicated R Code in a Project
• {easyr} 0.1.0: Helpful Functions from Oliver Wyman Actuarial Consulting
• {effectsize} 0.0.1: Indices of Effect Size and Standardized Parameters
• {ip2location} 8.0.0: Lookup for IP Address Information
• {marindicators} 1.0.0: Marine Ecosystem and Fishing Pressure Indicators
• {reactable} 0.1.0: Interactive Data Tables Based on ‘React Table’
• {subformula} 0.1.0: Create Subformulas of a Formula
• {SummaryLasso} 1.2.1: Building Polygenic Risk Score Using GWAS Summary Statistics
• {tidydice} 0.0.3: Simulates Dice Rolls and Coin Flips
• {wiesbaden} 1.2.0: Access Databases from the Federal Statistical Office of Germany

GitHub or Bitbucket

• {colRoz}: A colour palette for the land down under
• {workloopR}: Analysis of work loops and other data from muscle physiology experiments in R
• {globe4r}: Interactive globes for R, seamlessly integrated with shiny.
• {tune}: Tidy Tuning Tools

Updated Packages

• {Rcpp} 1.0.3: More Spit and Polish
• {RcppAnnoy} 0.0.14
• AzureR updates: AzureStor, AzureVM, AzureGraph, AzureContainers
• {roxygen2} 7.0.0
• {badger} 0.0.7: Badge for R Package
• {bujar} 0.2.7: Buckley-James Regression for Survival Data with High-Dimensional Covariates
• {dlstats} 0.1.3: Download Stats of R Packages
• {dti} 1.4.3: Analysis of Diffusion Weighted Imaging (DWI) Data
• {exPrior} 1.0.1: Prior Distributions Using a Bayesian Hierarchical Framework
• {fmri} 1.9.2.1: Analysis of fMRI Experiments
• {iq} 1.1: Protein Quantification in Mass Spectrometry-Based Proteomics
• {patternplot} 0.3.1: Versatile Pie Charts, Ring Charts, Bar Charts and Box Plotsusing Patterns, Colors and Images
• {RAINBOWR} 0.1.14: Genome-Wide Association Study with SNP-Set Methods

Videos and Podcasts

• Azure AI and Machine Learning talk series
• forecast combination talk (16 mins)

Gist & Cookbook

• Using tidyverse, tidycensus, suncalc, gganimate, etc. to see how sunset times are distributed across the population of (most of) the US. (based on this tweet)

R Internationally

• (French) “How to turn multiple R scripts into a proper R package”
• (Spanish) Usando el paquete Janitor para limpiar datos de forma fácil y prolija

Tutorials

• Statistical uncertainty with R and pdqr
• Soviet Space Dogs (Part 2): A walk through of {ggplot2} annotation using {ggforce} & {ggtext}
• Using reticulate with arcpy on a Windows machine
• A more convincing Leaflet visualizations from R - customizing markers, icons, color scales & HTML popups.
• Tweets from Chile using {rtweet} and {wordcloud2}

R Project Updates

• Updates from R Core

• Data-Driven Tracking and Discovery of R Consortium Activities

Upcoming Events in 3 Months

Events in 3 Months:

• Yes We Cran: A conference on R packages and their applications, December 6-8

• BioC Asia, December 5-6

• Japan.R 2019, December 7

• rOpenSci OzUnconf, December 11-13

• R @ ISSA, December 26

• Tidyverse Dev Day, January 31

• 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

• Community Call - Last Night, Testing Saved my Life

Your support will keep R Weekly team moving! 💡

Quotes of the Week

TIL about another great base #R function: ls.str(). Nice dplyr::glimpse()-like view of all the objects (dataframes, lists, vectors, functions) in local environment #rstats pic.twitter.com/8SpzVdMXIh

— Kurtis Pivert (@kpivert) November 12, 2019

I have absolutely nothing nice to say about `difftime()` #rstats

I had banned `-.POSIXt` in linked thread, I think I'll write `good_difftime()` and define `difftime <- function(...) stop("never again, use good_difftime() instead")` in my RProfile too,https://t.co/WdXkrqt8XR pic.twitter.com/I8iT3oQn93

— Antoine Fabri (@antoine_fabri) November 13, 2019

If you want to try out GitHub Actions for #rstats packages, we have custom actions and example workflows at https://t.co/R94ru1USN1 https://t.co/VH4hsK7QyG

— Jim Hester (@jimhester_) November 13, 2019