R Weekly 2024-W12 Patterns and anti-patterns, Shitty R help, and R Cheat Sheet

This article is originally published at

Hello and welcome to this new issue!

• 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

• Patterns and anti-patterns of data analysis reuse

• Shitty R help from shitty AI

• Best Practice for R :: Cheat Sheet

Insights

• What we can learn from esoteric patterns

• Pre Self: what fraction of a journal’s papers are preprinted?

• Football Multiplicities

• Unleash the Power of Your Data: Extend Excel with Python and R!

• Patterns and anti-patterns of data analysis reuse

• Integrating Snowflake and Posit for enhanced analytics

• Shitty R help from shitty AI

• Ellipses, eclipses and bulletses

• No installation required: how WebAssembly is changing scientific computing

• rOpenSci Dev Guide 0.9.0: Multilingual Now! And Better

• Fuzzy Grouping

• Best Practice for R :: Cheat Sheet

R in the Real World

• ShinyConf 2024: A Sneak Peek into the Agenda

R in Organizations

• ISC-funded Grant: Secure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences

New Packages

📦 Go Live for More New Pkgs 📦

tidychatmodels: Chat With All Kinds of AI Models Through a Common Interface

• ciw 0.0.1 on CRAN: New Package!

• digest 0.6.35 on CRAN: New xxhash code

• 🚀 Exciting News! 🚀

CRAN

• {mosaicCalc} 0.6.1: R-Language Based Calculus Operations for Teaching
• {palette} 0.0.2: Color Scheme Helpers
• {updateme} 0.1.0: Informative Messages About Outdated Packages
• {theftdlc} 0.1.0: Analyse and Interpret Time Series Features
• {ggbrick} 0.3.0: Waffle Style Chart with a Brick Layout in ‘ggplot2’
• {r2stl} 1.0.3: Visualizing Data using a 3D Printer
• {ciw} 0.0.1: Watch the CRAN Incoming Directories
• {xxhashlite} 0.2.2: Extremely Fast Hashing of R Objects, Raw Data and Files using ‘xxHash’ Algorithms
• {CompGR} 0.1.3: Complete Annual Growth Rate Generator
• {phoenix} 1.0.0: The Phoenix Pediatric Sepsis and Septic Shock Criteria
• {infoelectoral} 1.0.0: Download Spanish Election Results
• {link} 2024.4.0: Hyperlink Automatic Detection
• {rnames} 1.0.1: Recursive Display of Items in Nested Lists
• {rsleep} 1.0.12: Analysis of Sleep Data
• {SouthParkRshiny} 1.0.0: Data and ‘Shiny’ Application for the Show ‘SouthPark’
• {bandicoot} 1.0.0: Light-Weight ‘python’-Like Object-Oriented System
• {MSBStatsData} 0.0.2: Data Sets for Courses at the Münster School of Business
• {nycflights23} 0.1.0: Flights and Other Useful Metadata for NYC Outbound Flights in 2023
• {fillpattern} 1.0.1: Patterned Fills for ‘ggplot2’ and ‘grid’ Graphics
• {bibliorefer} 0.1.0: Generator of Main Scientific References
• {movegroup} 2024.03.05: Visualizing and Quantifying Space Use Data for Groups of Animals
• {iimi} 1.0.2: Identifying Infection with Machine Intelligence

GitHub or Bitbucket

• {scimo} 0.0.1: Extra Recipes Steps For Dealing With Omics Data

• {robodeck}

Updated Packages

🔍 Search on R-universe 🔍

• {visachartR} 3.3.0: Wrapper for ‘Visa Chart Components’ - diffify
• {tinytex} 0.50: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents - diffify
• {teal.reporter} 0.3.1: Reporting Tools for ‘shiny’ Modules - diffify
• {sass} 0.4.9: Syntactically Awesome Style Sheets (‘Sass’) - diffify
• {visR} 0.4.1: Clinical Graphs and Tables Adhering to Graphical Principles - diffify
• {folders} 0.1.0: Standardized Folder Names - diffify
• {aifeducation} 0.3.2: Artificial Intelligence for Education - diffify
• {tfrmt} 0.1.1: Applies Display Metadata to Analysis Results Datasets - diffify
• {moodlequizR} 2.0.2: Easily Create Fully Randomized ‘Moodle’ Test Questions - diffify
• {flashr} 0.1.2: Create Flashcards of Terms and Definitions - diffify
• {topr} 2.0.1: Create Custom Plots for Viewing Genetic Association Results - diffify
• {formatdown} 0.1.3: Formatting Tools for ‘rmarkdown’ Documents - diffify
• {fable} 0.3.4: Forecasting Models for Tidy Time Series - diffify
• {s3fs} 0.1.5: ‘Amazon Web Service S3’ File System - diffify
• {NeuroDecodeR} 0.2.0: Decode Information from Neural Activity - diffify
• {feasts} 0.3.2: Feature Extraction and Statistics for Time Series - diffify
• {framecleaner} 0.2.1: Clean Data Frames - diffify
• {CDCPLACES} 1.1.5: Access the ‘CDC PLACES’ API - diffify
• {vivainsights} 0.5.2: Analyze and Visualize Data from ‘Microsoft Viva Insights’ - diffify
• {bigrquery} 1.5.1: An Interface to Google’s ‘BigQuery’ ‘API’ - diffify
• {contingencytables} 3.0.0: Statistical Analysis of Contingency Tables - diffify
• {cliot} 0.2.0: Clinical Indices and Outcomes Tools - diffify
• {evsim} 1.4.0: Electric Vehicle Charging Sessions Simulation - diffify
• {evprof} 1.1.2: Electric Vehicle Charging Sessions Profiling and Modelling - diffify
• {rnames} 1.0.1: Recursive Display of Items in Nested Lists - diffify
• {ggscidca} 0.1.9: Plotting Decision Curve Analysis with Coloured Bars - diffify
• {targets} 1.6.0: Dynamic Function-Oriented ‘Make’-Like Declarative Pipelines - diffify
• {Rd2md} 1.0.0: Markdown Reference Manuals - diffify
• {oaii} 0.5.0: ‘OpenAI’ API R Interface - diffify
• {deepdep} 0.4.3: Visualise and Explore the Deep Dependencies of R Packages - diffify
• {text2map} 0.1.9: R Tools for Text Matrices, Embeddings, and Networks - diffify
• {cansim} 0.3.16: Accessing Statistics Canada Data Table and Vectors - diffify
• {landsepi} 1.4.0: Landscape Epidemiology and Evolution - diffify
• {geomtextpath} 0.1.3: Curved Text in ‘ggplot2’ - diffify
• {tidyAML} 0.0.5: Automatic Machine Learning with ‘tidymodels’ - diffify
• {cffr} 1.0.0: Generate Citation File Format (‘cff’) Metadata for R Packages - diffify
• {arrow} 15.0.1: Integration to ‘Apache’ ‘Arrow’ - diffify
• {AllMetrics} 0.2.1: Calculating Multiple Performance Metrics of a Prediction Model - diffify
• {mdbr} 0.2.1: Work with Microsoft Access Files - diffify
• {f1dataR} 1.5.1: Access Formula 1 Data - diffify
• {tinytable} 0.1.0: Simple and Configurable Tables in ‘HTML’, ‘LaTeX’, ‘Markdown’, ‘Word’, ‘PNG’, ‘PDF’, and ‘Typst’ Formats - diffify
• {Rd2roxygen} 1.15: Convert Rd to ‘Roxygen’ Documentation - diffify
• {arcpullr} 0.2.9: Pull Data from an ‘ArcGIS REST’ API - diffify
• {nonmem2R} 0.2.5: Loading NONMEM Output Files with Functions for Visual Predictive Checks (VPC) and Goodness of Fit (GOF) Plots - diffify
• {gcplyr} 1.9.0: Wrangle and Analyze Growth Curve Data - diffify
• {openair} 2.18-2: Tools for the Analysis of Air Pollution Data - diffify
• {usa} 0.1.2: Updated US State Facts and Figures - diffify
• {tm} 0.7-12: Text Mining Package - diffify
• {srt} 1.0.4: Read Subtitle Files as Tabular Data - diffify
• {metro} 0.9.3: Washington Metropolitan Area Transit Authority API - diffify
• {tidyselect} 1.2.1: Select from a Set of Strings - diffify
• {epiR} 2.0.70: Tools for the Analysis of Epidemiological Data - diffify
• {digest} 0.6.35: Create Compact Hash Digests of R Objects - diffify
• {theft} 0.6.1: Tools for Handling Extraction of Features from Time Series - diffify
• {greta} 0.4.5: Simple and Scalable Statistical Modelling in R - diffify
• {gluedown} 1.0.9: Wrap Vectors in Markdown Formatting - diffify
• {fflr} 2.2.3: Retrieve ESPN Fantasy Football Data - diffify
• {duckplyr} 0.3.1: A ‘DuckDB’-Backed Version of ‘dplyr’ - diffify

Call for Participation

• 2024 DuckDB User Survey (as featured on https://duckdb.org)

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast
• Use CSS Selection to Style Existing HTML Code

• Use ChatGPT, Mistral and ollama for Text Processing in R

• Adam Austin @ The Hartford - Data Science Hangout

• R Shiny in Life Sciences – Top 7 Dashboard Examples by Ismael Rodriguez

R Internationally

• R-Ladies Goiânia: Promoting Diversity and Inclusion in Local R Community

Tutorials

• WebDev4R: CSS Selection

• Introducing tidychatmodels for communicating with AI chatbots

• Explain XGBoost

• Pi Day Circles

• Bird’s Eye View: using R to generate inventory maps for lab reagents

• Plotting Training and Testing Predictions with tidyAML

• The Fun in Functional Programming

• Add shiny in quarto blog with shinylive

• Mastering Random Sampling in R with the sample() Function
• Wrangling Names in R: Your Guide to the make.names() Function

• Taming the Nameless: Using the names() Function in R

• 3MW (Enjoy the break with AI)

• Object Oriented Programming in R (Part 3): A Practical Guide to the S4 System

• How To Write E2E Tests Selectors That Stand The Test Of Time

R Project Updates

Updates from R Core:

Updates from the R Contribution Working Group (RCWG):

• Announcing R Dev Day @ Imperial, London, UK on Friday 26 April. Registration deadline Sunday 14 April.

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

• Introduction to Causal Machine Learning estimators in R

• 2024 Workshops Series Kick-off

Grants & Funding

Datasets

Jobs

💼 Explore Jobs & Gigs Board on RStudio Community 💼

rtistry

Heres a look at how I wrote an implementation of the rolling shutter effect in #rstats

Worked example in the repo: https://t.co/Vod9oQtYwz pic.twitter.com/DlfVg2Q35g

— chris (@dickie_roper) March 15, 2024

#rstats #rspatial and other #geospatial folks, I am pleased to announce the {centerline} package! It's a small but powerful tool that can find a centerline of closed polygons. https://t.co/hMYYpYT6a3 pic.twitter.com/dix2pVm3n7

— Anatolii Tsyplenkov (@atsyplen) March 16, 2024

Roads of Hokkaidō. This was a trial render that took a good 1.5 hours just to draw the over 600k linestrings. Don't want to think how long it'll think to path trace so here's the draft render. Will try overnight, maybe.#rayshader adventures, an #rstats tale pic.twitter.com/xUFJpyAyPn

— tterence on bsky (@researchremora) March 12, 2024

Thanks for visiting r-craft.org
This article is originally published at
Please visit source website for post related comments.