R Weekly 2026-W12 Sharing across shiny modules, F1 data

16 Mar 2026

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

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

Highlight

• Sharing data across shiny modules, an update

• Formula 1 Analysis in R with f1dataR: Lap Times, Pit Stops and Driver Performance

Insights

• Sharing data across shiny modules, an update

• Three Posit Platform Features Worth Knowing About

• posit::glimpse() Newsletter – March 2026

• Does every finite string of numbers appear within π?

• Breaking Release of the patentsview R Package

R in the Real World

• Pacific island remittances by @ellis2013nz

• From Black to Glass Box: Rethinking the Actuarial Lifecycle

• Formula 1 Analysis in R with f1dataR: Lap Times, Pit Stops and Driver Performance

R in Organizations

• Igniting an R Movement in the Philippines: RNVSU’s Open Science Vision

• Doing More with Cortex: Introducing the Databot Snowflake Skill for Semantic Awareness

R in Academia

• Addressing a Decade-Old ‘Continentai Fallacy’ in Spatial Econometrics

Tutorials

• DuckDB + dbplyr: When Your Pipeline Gives Different Results Every Time It Runs

• Using Quarto to Write a Book

• Getting to the bottom of TMLE: forcing the target to behave

• Get Better: loading multiple csv files in R

• Learning PK/PD Simulation: A Beginner’s Monte Carlo Analysis With mrgsolve in R

Resources

• QuickStats: WebR-powered browser-based statistical analysis tool.

New Packages

📦 Keep up to date wtih CRANberries 📦

CRAN

• {obr} 0.2.2: Access Office for Budget Responsibility Data

• {decisionpaths} 0.1.0: Construct and Audit Longitudinal Decision Paths

• {brightspaceR} 0.1.0: Access D2L ‘Brightspace’ Data Sets via the ‘BDS’ API

• {stacr} 0.1.0: Tidy ‘STAC’ Workflows for R

• {readoecd} 0.3.0: Download and Tidy Data from the OECD

• {ons} 0.1.0: Download Data from the Office for National Statistics

• {hmrc} 0.3.0: Download and Tidy HMRC Statistical Data

• {boe} 0.1.0: Download Data from the Bank of England Statistical Database

• {ardlverse} 1.1.2: Comprehensive ARDL Modeling Framework: Panel, Bootstrap, Quantile-Nonlinear, and Fourier Extensions

• {earthUI} 0.1.1: Interactive ‘shiny’ GUI for the ‘earth’ Package

• {llmjson} 0.1.0: Repair Malformed JSON Strings

• {ggsky} 0.1.0: Galactic and Equatorial Coordinate Implementation for ‘ggplot2’

• {rapidcodeR} 0.1.0: Optimized Data Analysis System for AI-Based Text Processing

• {ROOT} 0.1.1: Rashomon Set of Optimal Trees

• {lucidr} 0.1.0: ‘Lucide’ Icons for ‘R’

• {comexr} 0.2.0: Client for the Brazilian Foreign Trade Statistics API (‘ComexStat’)

• {pep725} 1.0.0: Pan-European Phenological Data Analysis

• {fozziejoin} 0.0.13: Utilities for Joining Dataframes with Inexact Matching

• {restrictR} 0.1.0: Composable Runtime Contracts for R

GitHub

• {freestiler} 0.1.0: Create Vector Tiles from Spatial Data

• {entsoeapi} 0.9.5.1: R wrapper for ENTSO-E Transparency Platform API — electricity prices, generation, load, cross-border flows

Updated Packages

🔍 Search on R-universe 🔍

• {qol} 1.2.2: Powerful ‘SAS’ Inspired Concepts for more Efficient Bigger Outputs - diffify

• {vapour} 0.16.0: Access to the ‘Geospatial Data Abstraction Library’ (‘GDAL’) - diffify

• {geomorph} 4.1.0: Geometric Morphometric Analyses of 2D and 3D Landmark Data - diffify

• {laminr} 1.3.0: Client for ‘LaminDB’ - diffify

• {BMA} 3.18.21: Bayesian Model Averaging - diffify

• {glasstabs} 0.1.1: Animated Glass-Style Tabs and Multi-Select Filter for ‘Shiny’ - diffify

• {miceadds} 3.19-16: Some Additional Multiple Imputation Functions, Especially for ‘mice’ - diffify

• {cffr} 1.3.0: Generate Citation File Format (‘cff’) Metadata for R Packages - diffify

• {ipumsr} 0.10.0: An R Interface for Downloading, Reading, and Handling IPUMS Data - diffify

• {globals} 0.19.1: Identify Global Objects in R Expressions - diffify

• {orbital} 0.5.1: Predict with ‘tidymodels’ Workflows in Databases - diffify

• {igoR} 1.0.1: Intergovernmental Organizations Database - diffify

• {protolite} 2.4.0: Highly Optimized Protocol Buffer Serializers - diffify

• {epiworldR} 0.13.0.0: Fast Agent-Based Epi Models - diffify

• {CopernicusMarine} 0.4.5: Search Download and Handle Data from Copernicus Marine Service Information - diffify

• {picasso} 1.5: Sparse Learning with Convex and Concave Penalties - diffify

• {blocking} 1.0.2: Various Blocking Methods for Entity Resolution - diffify

• {units} 1.0-1: Measurement Units for R Vectors - diffify

• {rJava} 1.0-15: Low-Level R to Java Interface - diffify

• {effectsize} 1.0.2: Indices of Effect Size - diffify

• {tidyterra} 1.1.0: ‘tidyverse’ Methods and ‘ggplot2’ Helpers for ‘terra’ Objects - diffify

• {listenv} 0.10.1: Environments Behaving (Almost) as Lists - diffify

• {sdcMicro} 5.8.1: Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation - diffify

• {otelsdk} 0.2.3: R SDK and Exporters for OpenTelemetry - diffify

• {wbids} 1.1.4: Seamless Access to World Bank International Debt Statistics (IDS) - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

• Abuja R User Group: Outgrowing your laptop with R and Positron by Julia Silge

R Project Updates

Updates from R Core:

We are pleased to announce that Heather Turner @heathrturnr.fosstodon.org.ap.brid.gy has joined the R Core Team. She has been an active contributor notably via the R Dev Days, and has greatly improved cooperation between R Core and the R community in more ways #RStats.

— The R Foundation (@r-foundation.bsky.social) 12 March 2026 at 13:30

R version 4.5.3 "Reassured Reassurer" (source version) has been released. It should be on CRAN by now. #rstats

— Peter Dalgaard (@pdalgd.bsky.social) 11 March 2026 at 11:56

Call for Participation

• AI in Production 2026 Workshops: What’s Coming in June

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

Connect

Join the Data Science Learning Community

Quotes of the Week

R version 4.5.3 (Reassured Reassurer) #rstats

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— superboreen (@superboreen.bsky.social) 11 March 2026 at 10:34

A really fun dataset for this week's #TidyTuesday, looking at how people interpret different probabilistic statements 📊 There's so many aspects of this to visualise, but I decided make some barcode plots comparing how people from the UK and US responded! #DataViz #RStats #ggplot2

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— Nicola Rennie (@nrennie.bsky.social) 11 March 2026 at 10:18