R Weekly 2024-W21, Automate code refactoring, Faster Code, Open-Source Project

21 May 2024

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

Highlight

• Automate code refactoring with {xmlparsedata} and {brio}

• Find Out How many Times Faster your Code is

• Communication Tips for your Open-Source Project

Insights

• Gergely Daróczi’s Journey: Empowering R Users in Hungary

• Enhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative

• The Evolution of Melbourne’s Business Analytics and R Business User Group

• Communication Tips for your Open-Source Project

R in the Real World

• New York City’s POC Population
  

New Packages

📦 Go Live for More New Pkgs 📦

• RApiSerialize 0.1.3 on CRAN: Skipping XDR
  CRAN

• {ravetools} 0.1.5: Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data

• {mgwrhw} 1.1.1.5: Displays GWR (Geographically Weighted Regression) and Mixed GWR Output and Map

• {crosstalkr} 1.0.5: Analysis of Graph-Structured Data with a Focus on Protein-Protein Interaction Networks

• {crosslag} 0.1.0: Perform Linear or Nonlinear Cross Lag Analysis

• {bbnet} 1.0.1: Create Simple Predictive Models on Bayesian Belief Networks

• {CDGHMM} 0.1.0: Hidden Markov Models for Multivariate Panel Data

• {BioM2} 1.0.6: Biologically Explainable Machine Learning Framework

• {srcpkgs} 0.1: R Source Packages Manager

• {tricolore} 1.2.4: A Flexible Color Scale for Ternary Compositions

• {biologicalActivityIndices} 0.1.0: Biological Activity Indices

• {arcgisplaces} 0.1.0: Search for POIs using ArcGIS ‘Places Service’

• {rechaRge} 1.0.0: HydroBudget – Groundwater Recharge Model

• {rKolada} 0.2.3: Access Data from the ‘Kolada’ Database

• {qlcVisualize} 0.2.1: Visualization for Quantitative Language Comparison

• {ggspark} 0.0.2: ‘ggplot2’ Functions to Create Tufte Style Sparklines

Updated Packages

🔍 Search on R-universe 🔍

• {radiant} 1.6.1: Business Analytics using R and Shiny - diffify

• {ggsci} 3.0.3: Scientific Journal and Sci-Fi Themed Color Palettes for ‘ggplot2’ - diffify

• {deps} 0.2.0: Dependency Management with ‘roxygen’-Style Comments - diffify

• {cleanNLP} 3.1.0: A Tidy Data Model for Natural Language Processing - diffify

• {FIESTA} 3.6.3: Forest Inventory Estimation and Analysis - diffify

• {fuj} 0.2.1: Functions and Utilities for Jordan - diffify

• {shiny.react} 0.4.0: Tools for Using React in Shiny - diffify

• {rspm} 0.5.3: ‘RStudio’ Package Manager - diffify

• {ledger} 2.0.11: Utilities for Importing Data from Plain Text Accounting Files - diffify

• {spNetwork} 0.4.4: Spatial Analysis on Network - diffify

• {ggscidca} 0.2.3: Plotting Decision Curve Analysis with Coloured Bars - diffify

• {fedmatch} 2.0.6: Fast, Flexible, and User-Friendly Record Linkage Methods - diffify

• {openairmaps} 0.9.0: Create Maps of Air Pollution Data - diffify

• {prqlr} 0.8.1: R Bindings for the ‘prqlc’ Rust Library - diffify

• {modelsummary} 2.1.0: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready - diffify

• {glossr} 0.8.0: Use Interlinear Glosses in R Markdown - diffify

• {xaringanExtra} 0.8.0: Extras and Extensions for ‘xaringan’ Slides - diffify

• {ruminate} 0.2.3: A Pharmacometrics Data Transformation and Analysis Tool - diffify

• {SSBtools} 1.5.2: Statistics Norway’s Miscellaneous Tools - diffify

• {fscache} 1.0.3: File System Cache - diffify

• {drake} 7.13.10: A Pipeline Toolkit for Reproducible Computation at Scale - diffify

• {iraceplot} 1.3: Plots for Visualizing the Data Produced by the ‘irace’ Package - diffify

• {simstudy} 0.8.0: Simulation of Study Data - diffify

• {hmer} 1.5.9: History Matching and Emulation Package - diffify

• {seqgendiff} 1.2.4: RNA-Seq Generation/Modification for Simulation - diffify

• {latrend} 1.6.1: A Framework for Clustering Longitudinal Data - diffify

• {microeco} 1.7.0: Microbial Community Ecology Data Analysis - diffify

• {ggblanket} 9.0.0: Simplify ‘ggplot2’ Visualisation - diffify

• {misty} 0.6.3: Miscellaneous Functions ‘T. Yanagida’ - diffify

• {tidyEdSurvey} 0.1.3: Integration of ‘dplyr’ and ‘ggplot2’ with ‘EdSurvey’ - diffify

• {unix} 1.5.8: POSIX System Utilities - diffify ct.org/package=opencpu): Producing and Reproducing Results - diffify

• {nsRFA} 0.7-17: Non-Supervised Regional Frequency Analysis - diffify

• {rgoogleads} 0.11.0: Loading Data from ‘Google Ads API’ - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

R Internationally

• Big Book of R now has ( books in Spanish!)

Tutorials

• AIC in the well-specified linear model: theory and simulation

• Find Out How many Times Faster your Code is

• Automate code refactoring with {xmlparsedata} and {brio}

• gitlabr V2.1.0 – gitlab-ci with ‘pak’ and functions to deal with groups on GitLab

• A simple probabilistic algorithm for estimating the number of distinct elements in a data stream

• Probability of receiving a credit; using learningmachine

• How to replace some non-available values in a vector with values coming from another vector?

• How to filter values in a nested tibble without using filter() from dplyr?

• Mastering gregexpr() in R: A Comprehensive Guide

• Counting Words in a String in R: A Comprehensive Guide

• How to Select Columns Containing a Specific String in R

• Checking if Multiple Columns are Equal in R

• How to Check if a Column Exists in a Data Frame in R

• 3MW (Reactive expressions in R-Shiny)

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:

• Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research - 21st May

• 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

artistry

Quotes of the Week

When you're about to start writing about creating art with sine and cosine waves for the #rtistry book, but your numerophobic self has to explain the math behind the sine and cosine waves first 🫠: pic.twitter.com/g7wy923bgh

— Meghan Harris (@meghansharris) March 16, 2024