R Weekly 2024-W20 Aesthetics Wiki, Dplyr vs DuckDB, TLG Catalog WebR

13 May 2024

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

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

Highlight

• The Aesthetics Wiki - an R Addendum

• R Dplyr vs. DuckDB - How to Enhance Your Data Processing Pipelines with R DuckDB

• TLG Catalog 🤝 WebR

Insights

• Statement on CVE-2024-27322

• The True ROI of Doing It Right the First Time in Software Projects

• R Dplyr vs. DuckDB - How to Enhance Your Data Processing Pipelines with R DuckDB

• Worldwide Bureaucracy Indicators - Comparison of the salaries of the Government Doctors in different countries

• The Aesthetics Wiki - an R Addendum

• Demo repository for creating a Quarto workflow with {quarto-webr} and {quarto-pyodide}

• Data Usage with Postprocessing

• If Doom runs everywhere, it must run on Shiny

R in Organizations

• TLG Catalog 🤝 WebR

R in Academia

• Dynamic Interactions for R and Python

New Releases

• RStudio IDE and Posit Workbench 2024.04.0: What’s New

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• RcppArmadillo 0.12.8.3.0 on CRAN: Upstream Bugfix

• First release of mvgam(v1.1.0) to CRAN

• {shinymgr} 1.1.0: A Framework for Building, Managing, and Stitching ‘shiny’ Modules into Reproducible Workflows
• {heiscore} 0.0.1: Score and Plot the Healthy Eating Index from NHANES Data
• {lzstring} 0.1.2: Wrapper for ‘lz-string’ ‘C++’ Library
• {lotterybr} 0.1.0: Lottery Datasets from Caixa Economica Federal
• {modelgrid} 1.2.0: A Framework for Creating, Managing and Training Multiple ‘caret’ Models
• {flexlsx} 0.2.1: Exporting ‘flextable’ to ‘xlsx’ Files

Updated Packages

🔍 Search on R-universe 🔍

• ShinyProxy 3.1.0

• {gwavr} 0.3.1: Get Water Attributes Visually in R - diffify
• {geostan} 0.6.1: Bayesian Spatial Analysis - diffify
• {plume} 0.2.4: A Simple Author Handler for Scientific Writing - diffify
• {paws.storage} 0.6.0: ‘Amazon Web Services’ Storage Services - diffify
• {paws.machine.learning} 0.6.0: ‘Amazon Web Services’ Machine Learning Services - diffify
• {FaaSr} 1.2.1: FaaS (Function as a Service) Package - diffify
• {paws.database} 0.6.0: ‘Amazon Web Services’ Database Services - diffify
• {EpiNow2} 1.5.0: Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters - diffify
• {popEpi} 0.4.12: Functions for Epidemiological Analysis using Population Data - diffify
• {fslr} 2.25.3: Wrapper Functions for ‘FSL’ (‘FMRIB’ Software Library) from Functional MRI of the Brain (‘FMRIB’) - diffify
• {fmtr} 1.6.4: Easily Apply Formats to Data - diffify
• {ftExtra} 0.6.4: Extensions for ‘Flextable’ - diffify
• {ExpImage} 0.10.1: Analysis of Images in Experiments - diffify
• {arcgisutils} 0.3.0: ArcGIS Utility Functions - diffify
• {logr} 1.3.8: Creates Log Files - diffify
• {insurancerating} 0.7.3: Analytic Insurance Rating Techniques - diffify
• {leaflegend} 1.2.1: Add Custom Legends to ‘leaflet’ Maps - diffify
• {taylor} 3.1.0: Lyrics and Song Data for Taylor Swift’s Discography - diffify
• {scientific} 2024.2: Highly Customizable ‘rmarkdown’ Theme for Scientific Reporting - diffify
• {ggsurvfit} 1.1.0: Flexible Time-to-Event Figures - diffify
• {tidylog} 1.1.0: Logging for ‘dplyr’ and ‘tidyr’ Functions - diffify
• {formatdown} 0.1.4: Formatting Numbers in ‘rmarkdown’ Documents - diffify
• {tinycodet} 0.5.0: Functions to Help in your Coding Etiquette - diffify
• {jsmodule} 1.5.4: ‘RStudio’ Addins and ‘Shiny’ Modules for Medical Research - diffify Fitting - diffify
• {editbl} 1.0.4: ‘DT’ Extension for CRUD (Create, Read, Update, Delete) Applications in ‘shiny’ - diffify
• {streetscape} 1.0.1: Collect And Investigate Street Views For Urban Science - diffify
• {happign} 0.3.0: R Interface to ‘IGN’ Web Services - diffify
• {manydata} 0.9.3: A Portal for Global Governance Data - diffify
• {activAnalyzer} 2.1.1: A ‘Shiny’ App to Analyze Accelerometer-Measured Daily Physical Behavior Data - diffify
• {flextable} 0.9.6: Functions for Tabular Reporting - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

• R’s new exploit: how it works & other ways you’re vulnerable

R Internationally

• Modelación Ordenada con R: Aprende todo sobre el proceso de creación de modelos de aprendizaje automático con esta traducción de “Modelación Ordenada con R” un libro de Max Kuhn y Julia Silge con el que aprenderas a través de ejemplos todo lo realcionado con la creación de modelos de aprendizaje automático listos para producción.

• SatRdays London 2024: Thanks for coming!

Tutorials

• Calculating the proportion of US state borders that are coastlines: Measuring coastlines is hard and causes fractal paradoxes, but we can use R and {sf} to try!

• mlsauce’s v0.18.2: various examples and benchmarks with dimension reduction

• Time Series Forecasting: The BIST Banks Index

• Treemaps In R

• How to Check if a Column Contains a String in R
• How to Collapse Text by Group in a Data Frame Using R
• How to Select Columns by Index in R (Using Base R)
• Counting NA Values in Each Column: Comparing Methods in R
• Exploring Model Selection with TidyDensity: Understanding AIC for Statistical Distributions

• 3MW (Event listeners with R-Shiny)

• Reproducing and adapting the UN Population Projections by @ellis2013nz

R Project Updates

Updates from R Core:

Call for Participation

• Register for R/Pharma at posit::conf(2024)

Upcoming Events in 3 Months

Events in 3 Months:

• A list of R conferences and meetings

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

• Weekly R Workshops for Ukraine

• Cluster Analysis in R workshop

• Reproducible research with Nix and rix Workshop

Connect

Join the Data Science Learning Community

rtistry

Getting ready for summer with a spinning render of Enoshima. 🏖️ Data from OpenStreetMap contributors. Tried hard to find lidar data but failed.#rayshader adventures, an #rstats tale pic.twitter.com/5iW1F2KOl9

— terence (@researchremora) May 11, 2024

Almost forgot this projection so here it is with the world's ocean currents. Should I name the currents?#rayshader adventures, an #rstats tale pic.twitter.com/4qCcHaHXy2

— terence (@researchremora) May 8, 2024

Quotes of the Week

Had a great example recently of the advantages of using #targets for #rstats workflows. My EC2 instance decided to eat itself & crash a few hrs in. Yes the current function was lost but the 3hrs of analysis prior was perfectly captured in targets, ready to run where it left off👍 pic.twitter.com/ohxY5j3IXK

— Luke Pembleton (@lwpembleton) May 10, 2024

https://t.co/h5jhKAY5nw pic.twitter.com/LsDuISEYhm

— Bruno Rodrigues (@[email protected]) (@brodriguesco) May 8, 2024