R Weekly 2023-W34 Cleaning Data, Analyzing Data, and Infinite Data

21 Aug 2023

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This week’s release was curated by Jonathan Carroll, with help from the RWeekly team members and contributors.

Highlight

• Best Practices for Data Cleaning and Preprocessing

• Analyzing new USDA data using open source tools

• Taking from Infinite Sequences

Insights

• Object of type closure can shut up

• Best Practices for Data Cleaning and Preprocessing

• webR 0.2.0 has been released

• Taking from Infinite Sequences

• Pythagorean Triples with Comprehensions

• Analyzing new USDA data using open source tools
• Little useless-useful R functions – Goldbach’s conjecture and Sieve of Sundaram
• Can a Simple Multi-Agent Model Replicate Complex Stock Market Behaviour?
• Copernicus OpenEO NDVI time series

• How to Sum Rows in R: Master Summing Specific Rows with dplyr
• How to Check if a File is Empty in R: Practical Examples
• Ordinal Models for Paired Data
• #43: r2u Faster Than the Alternatives
• #41: Using r2u in Codespaces

• Omitted Variable Effects in Logistic Regression

• Exploring Data Distribution with Box Plots in R
• Mastering Data Approximation with R’s approx() Function
• Exploring the Power of the curve() Function in R
• Solving Systems of Equations in R using the solve() Function
• The substring() function in R

• pmax() and pmin(): Finding the Parallel Maximum and Minimum in R

• Tidy Tuesday: Spam mail

R in the Real World

• From Blood to Oil: A techies perspective on how the USAAF’s pragmatism destroyed the Luftwaffe, dropped the A, and yet failed on it’s Grandest Ambitions

• R performance tuning #1 #2 #3

• Use R to explore the link between literacy and suicide in 1830s France

R in Academia

• Equivalence Tests Using {marginaleffects}

• Benchmarking Firth’s Logit: {brglm2} versus {logistf}

R Users

• Use of R for Pharma in Rosario, Argentina

Resources

• Introduction to structural causal modelling

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {happign} 0.2.0: Easy acces to IGN data (French National Geographic Institute)

• {shiny.emptystate} 0.1.0: Empty State Components for ‘Shiny’ (post)

• {gghdx} 0.1.1: HDX Theme, Scales, and Other Conveniences for ‘ggplot2’
• {dateback} 1.0.2: Collect and Install R Packages on a Specified Date with Dependencies
• {Rgb} 1.7.5: The R Genome Browser
• {itscalledsoccer} 0.2.3: American Soccer Analysis API Client
• {formods} 0.1.1: ‘Shiny’ Modules for General Tasks
• {f1dataR} 1.3.0: Access Formula 1 Data
• {YTAnalytics} 0.0.4: Wrapper for ‘YouTube Analytics’ API
• {lettervalue} 0.1.0: Computing Letter Values
• {easy.utils} 0.0.1: Frequently Used Functions for Easy R Programming
• {codecountR} 0.0.2.0: Counting Codes in a Text and Preparing Data for Analysis
• {ggordiplots} 0.4.2: Make ‘ggplot2’ Versions of Vegan’s Ordiplots
• {lit} 1.0.0: Latent Interaction Testing for Genome-Wide Studies
• {bulkreadr} 0.1.0: The Ultimate Tool for Reading Data in Bulk
• {jqbr} 1.0.3: ‘jQuery QueryBuilder’ Input for ‘Shiny’
• {osmdata} 0.2.5: Import ‘OpenStreetMap’ Data as Simple Features or Spatial Objects
• {screenshot} 0.9.0: Take Screenshots (Screen Capture) from R Command

GitHub or Bitbucket

• {yyjsonr} 0.1.1

Updated Packages

🔍 Search on R-universe 🔍

• RcppArmadillo 0.12.6.1.0 on CRAN: New Upstream

• Reticulate 1.31

• {tidyEmoji} 0.1.1: Discovers Emoji from Text - diffify
• {hash} 2.2.6.3: Full Featured Implementation of Hash Tables/Associative Arrays/Dictionaries - diffify
• {wrapr} 2.1.0: Wrap R Tools for Debugging and Parametric Programming - diffify
• {leaflegend} 1.1.1: Add Custom Legends to ‘leaflet’ Maps - diffify
• {geomapdata} 2.0-2: Data for Topographic and Geologic Mapping - diffify
• {RSQL} 0.2.2: Database Agnostic Package to Generate and Process ‘SQL’ Queries in R - diffify
• {RcppRedis} 0.2.4: ‘Rcpp’ Bindings for ‘Redis’ using the ‘hiredis’ Library - diffify
• {quantreg} 5.97: Quantile Regression - diffify
• {nasapower} 4.0.11: NASA POWER API Client - diffify
• {GMMBoost} 1.1.5: Likelihood-Based Boosting for Generalized Mixed Models - diffify
• {BT} 0.4: (Adaptive) Boosting Trees Algorithm - diffify
• {emayili} 0.7.17: Send Email Messages - diffify
• {fontawesome} 0.5.2: Easily Work with ‘Font Awesome’ Icons - diffify
• {Rlabkey} 2.12.0: Data Exchange Between R and ‘LabKey’ Server - diffify
• {crandep} 0.3.2: Network Analysis of Dependencies of CRAN Packages - diffify
• {languageserver} 0.3.16: Language Server Protocol - diffify
• {Cairo} 1.6-1: R Graphics Device using Cairo Graphics Library for Creating High-Quality Bitmap (PNG, JPEG, TIFF), Vector (PDF, SVG, PostScript) and Display (X11 and Win32) Output - diffify
• {audio} 0.1-11: Audio Interface for R - diffify
• {tok} 0.1.1: Fast Text Tokenization - diffify
• {tikzDevice} 0.12.5: R Graphics Output in LaTeX Format - diffify
• {parsnip} 1.1.1: A Common API to Modeling and Analysis Functions - diffify
• {textrecipes} 1.0.4: Extra ‘Recipes’ for Text Processing - diffify
• {rsconnect} 1.0.2: Deploy Docs, Apps, and APIs to ‘Posit Connect’, ‘shinyapps.io’, and ‘RPubs’ - diffify
• {ggspatial} 1.1.9: Spatial Data Framework for ggplot2 - diffify
• {fusen} 0.5.2: Build a Package from Rmarkdown Files - diffify
• {emmeans} 1.8.8: Estimated Marginal Means, aka Least-Squares Means - diffify
• {hockeystick} 0.8.1: Download and Visualize Essential Climate Change Data - diffify
• {uuid} 1.1-1: Tools for Generating and Handling of UUIDs - diffify
• {proj4} 1.0-13: A simple interface to the PROJ.4 cartographic projections library - diffify
• {shinyChatR} 1.1.0: R Shiny Chat Module - diffify
• {pins} 1.2.1: Pin, Discover and Share Resources - diffify
• {jstor} 0.3.11: Read Data from JSTOR/DfR - diffify

Videos and Podcasts

• Listen to the R-Weekly Highlights Podcast

• Brief introduction to R, 2023

Tutorials

Reproducible data science with Nix, part 4 – So long, {renv} and Docker, and thanks for all the fish

R Project Updates

Updates from R Core:

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

• Multilingual Publishing

• An Introduction to Bayesian A/B Testing in Stan, R, and Python workshop

Jobs

💼 Explore Jobs & Gigs Board on RStudio Community 💼

• Senior Software Sustainability Engineer - Data.Org

rtistry

Quotes of the Week