R Weekly 2022-W29 Plumber, magick and lost fares

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Hello and welcome to this new issue!

• How to have (my) content shared by R Weekly?

This week’s release was curated by Batool Almarzouq, with help from the R Weekly team members and contributors.

Highlight

• Recreating the Shiny App tutorial with a Plumber API + React: Part 2

• How much has COVID cost the NYC Subway system in "lost fares"?

• Process Profile Pictures with magick

Insights

• Introducing the {renderthis} package

• 3 frameworks into one — Write your next paper with R Studio!

• Speedups in operations with regular expressions

• Multi-state survival modeling of a Jira issues snapshot

• The Impact of Ordinal Scales on Gaussian Mixture Recovery

R in the Real World

• Process Profile Pictures with magick

• How much has COVID cost the NYC Subway system in "lost fares"?

• R is for actuaRies

R in Organizations

• Jumping Rivers and the Data Science Community

• R Ladies Santa Rosa Leading with Other R Communities in Latin America to Create More Accessibility

• Indy UseR Growing as New Businesses like Insurance and Pharmaceuticals Move into Indianapolis

• R Ladies Cuernavaca Partners with Biotechnology Institute to Quickly Expand Reach in 2022

• rstudio::glimpse() Newsletter
• rOpenSci Code of Conduct Update

Resources

• Modern, colorful population pyramids for a report published by the “Bundesinstitut für Bevölkerungsforschung” (German Federal Institute for Population Research) - Cédric Scherer

• Free Four Week Data Science Course for High School Students, built using Distill.

• R Bootcamp

New Packages

📦 Go Live for More New Pkgs 📦

• {f1dataR}: An R package to access Formula 1 Data from the Ergast API and the official F1 data stream via the fastf1 python library.

CRAN

• {renderthis} 0.1.0: Render Slides to Different Formats ( cran.r-project.org )

• {mapiso} 0.1.2: Create Contour Polygons from Regular Grids.

GitHub or Bitbucket

• {parochial}: R package to make it easier to get started with travel time analyses in bits of Britain.

• {dtrackr}: An R library for managing and documenting dplyr data pipelines.

Updated Packages

• {sfdep}- diffify: A tidy interface for spatial dependence.

• Beta version of NIMBLE with automatic differentiation, including HMC sampling and Laplace approximation

• rfoaas 2.3.2: New upstream accessors

• Rcpp 1.0.9 on CRAN: Regular Updates

• lintr 3.0.0

🔍 Search on R-universe 🔍

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

• How to Read and Merge +1k Excel files using R

• Building a basic Shiny app with Golem

• Lucy Njoki Njuki presents Chapter 10 (“Dynamic UI”) from Mastering Shiny by Hadley Wickham

R Internationally

• A carpentries Workshop under the title “Beginners Guide for R through Open Data Science Practices” is delivered by the Open Science Community Saudi Arabia in collaboration with ArabR, Carpentries in MENA and SSBCB. The materials are taken from “Introduction to Open Data Science with R”.

Tutorials

• Predicting with decision tress using rpart

• Multi-scale model assessment with {spatialsample}

• Eight R Tidyverse tips for everyday data engineering

• Making Slides in Quarto with reveal.js

• Recreating the Shiny App tutorial with a Plumber API + React: Part 2

• World’s simplest R music system. Part 3 - Non-sinusoidal Waveforms

• The best stats you’ve ever seen

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• Why this is the year you should take the stage at EARL 2022…

• A list of R conferences and meetings

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

• Free Four Week Data Science Course for High School Students starts on Monday July 25th.

Call for Participation

• Submit your abstract to NHS-R Community Conference 2022

Your support will keep R Weekly team moving! 💡

Quotes of the Week

If you wish to write quality code that is also highly readable, I cannot recommend "The Art of Readable Code" (https://t.co/WR9ragK0J6) enough! 📖

Read my complete book review here:https://t.co/R6gVuyh3Pn#programming #softwaredevelopment #rstats #python pic.twitter.com/8zQlGArV7A

— Indrajeet Patil (इंद्रजीत पाटील) (@patilindrajeets) July 17, 2022

If you're learning #rstats as a beginner, I recommend keeping an error log when you first start - it will slow you down in the short-term but it should help you to learn and fix recurring errors (and why they're happening). pic.twitter.com/Hi4jKnz7Hn

— Emily Nordmann (@emilynordmann) July 18, 2022

Q for folks who taught themselves #rstats, have taught others, or both: what aspects of the language did you find you or your students tended to struggle most with?

— A. Jordan ''Job Hunting'' Nafa (@adamjnafa) July 13, 2022

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