R Weekly 2024-W46 Computational markdown, Bob's Burgers, S7
This week’s release was curated by Ryo Nakagawara, with help from the R Weekly team members and contributors.
Highlight
Insights
R in the Real World
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Guide to generating and rendering computational markdown content programmatically with Quarto: Learn how to use
knitr::knit()
in inline chunks to correctly render auto-generated R and markdown content in Quarto documents
R in Academia
Resources
New Packages
📦 Keep up to date wtih CRANberries 📦
CRAN
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{tidywater} 0.6.2: Water Quality Models for Drinking Water Treatment Processes.
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{handwriterRF} 1.0.2: Handwriting Analysis with Random Forests.
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{surveydown} 0.4.0: Markdown-Based Surveys Using ‘Quarto’ and ‘shiny’.
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{tidyplots} 0.6.2: Tidy Plots for Scientific Papers.
GitHub or Bitbucket
- {fastml}: Fast Machine Learning Model Training and Evaluation.
- {newplaces}: R-wrapper package to the Google Places API (New)
- {plumber-nextjs-app}: A demo Next.js app that interacts with an R Plumber backend
- {pray}: Display ASCII art of objects for prayer in the R console.
- {ig.degree.betweenness}: Smith-Pittman Community Detection Algorithm for ‘igraph’ Objects (2024) in R.
- {autoimport}: A toolbox to automatically generate @importFrom roxygen tags from R files.
- {peeky}: Download and Extract Shinylive Applications.
Updated Packages
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{S7} 0.2.0: An Object Oriented System Meant to Become a Successor to S3 and S4 - diffify
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{curl} 6.0.0: A Modern and Flexible Web Client for R - diffify
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{salesforcer} 1.0.2: An Implementation of ‘Salesforce’ APIs Using Tidy Principles - diffify
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{libr} 1.3.7: Libraries, Data Dictionaries, and a Data Step for R - diffify
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{zipangu} 0.3.3: Japanese Utility Functions and Data - diffify
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{waldo} 0.6.1: Find Differences Between R Objects - diffify
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{stars} 0.6-7: Spatiotemporal Arrays, Raster and Vector Data Cubes - diffify
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{charcuterie} 0.0.6: Handle Strings as Vectors of Characters - diffify
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{ranger} 0.17.0: A Fast Implementation of Random Forests - diffify
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{knitr} 1.49: A General-Purpose Package for Dynamic Report Generation in R - diffify
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{connectapi} 0.4.0: Utilities for Interacting with the ‘Posit Connect’ Server API - diffify
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{av} 0.9.3: Working with Audio and Video in R - diffify
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{ggreveal} 0.1.3: Reveal a ‘ggplot’ Incrementally - diffify
Videos and Podcasts
Shiny Apps
Tutorials
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Regressions where the coefficients are a simplex. by @ellis2013nz
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Comparison of spatial patterns in categorical raster data for arbitrary regions using R
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How to Use Dollar Sign ($) Operator in R: A Comprehensive Guide for Beginners
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R 3D Charts: Top 3 Packages to Master 3D Data Visualization in R
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Want To Get Even Faster Feedback From Your Unit Tests? Optimize Your Test Files Structure.
R Project Updates
Updates from R Core:
Call for Participation
Upcoming Events in 3 Months
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Connect
Join the Data Science Learning Community
Quotes of the Week
I've just explored the brand-new tidyplots package in R, and it’s impressive how effortlessly it enables you to create beautiful, publication-ready plots. Designed with scientific papers in mind, tidyplots lets you build, adjust, and refine plot components gradually, all with a… pic.twitter.com/ZVaPGoPHXW
— Joachim Schork (@JoachimSchork) November 11, 2024
To be a good geospatial data scientist, you need good tools.
— Yohan (@yohaniddawela) October 31, 2024
My tool of choice is R.
Here are the packages I can't live without:#rstats pic.twitter.com/n4qfYGes3Z