R Weekly 2021-W24

07 Jun 2021

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

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

Highlight

• Everybody Loves Raymond: Running Animal Crossing Villagers through the Google Vision API

• Shiny Developer Series Episode 21: RStudio software engineer Nick Strayer returns to share how he arrived to RStudio and motivations behind the new Shiny App Stories.

• Shiny in Production: Database Transactions

Insights

• Use the new R pipe built into R 4.1

• Pipe-esque Programming with {ggplot2}’s Plus Operator

• Wes McKinney InteRview

• Debugging cantrip from an #rstats wizard

• Building Effective Data Science Teams: Answering Your Questions

• Simulating the OLS Consistency When X and ε are Dependent

• RStudio v1.4 Update: What’s New

• New TabularData Available in Swift on macOS Monterery (et al)

• R Conferences that Serve a Diverse Population

R in the Real World

• Estimating win probability from best-of-7 series is not straightforward

• FPL – Point Project Part 3

• Return based quality factor on Warsaw Stock Exchange

• Hybrid machine learning forecasts for the UEFA Euro 2020

• The evolution of squad compositions at UEFA European Championships

• Shiny in Production: Database Transactions

• Celebrating World Ocean Day rOpenSci Style

• Texas winter storm excess deaths analysis

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {fitbitr} 0.1.0: Interface with the ‘Fitbit’ API
• {daiR} 0.9.0: Interface with Google Cloud Document AI API
• {mcboost} 0.3.0: Multi-Calibration Boosting
• {jackstraw} 1.3.1: Statistical Inference for Unsupervised Learning

GitHub or Bitbucket

• {codehover}: Hoverable HTML Table for Displaying Intermediary Code Results (e.g. Pipes)
• {plotme}: Human friendly interface for plots that are otherwise quite hard to create in R (e.g. sunburst)

Updated Packages

• {ComplexUpset} 1.3.0: Create Complex UpSet Plots Using ‘ggplot2’ Components

• {gghighlight} 0.3.2: Highlight Lines and Points in ‘ggplot2’
• {progressr} 0.8.0:: An Inclusive, Unifying API for Progress Updates
• {mapsapi} 0.4.9: ‘sf’-Compatible Interface to ‘Google Maps’ APIs
• {themis} 0.1.4: Extra Recipes Steps for Dealing with Unbalanced Data
• {wrapr} 2.0.8: Wrap R Tools for Debugging and Parametric Programming
• {cdata} 1.2.0: Fluid Data Transformations
• {torch} 0.4.0: Tensors and Neural Networks with ‘GPU’ Acceleration
• {mlr3data} 0.4.0: Collection of Machine Learning Data Sets for ‘mlr3’
• {radiant} 1.4.0: Business Analytics using R and Shiny
• {sparklyr} 1.7.0: R Interface to Apache Spark
• {tidyBF} 0.5.1: Tidy Wrapper for ‘BayesFactor’ Package
• {ffscrapr} 1.4.3: API Client for Fantasy Football League Platforms

Videos and Podcasts

• Shiny Developer Series Episode 21: RStudio software engineer Nick Strayer returns to share how he arrived to RStudio and motivations behind the new Shiny App Stories.

• #33: Collaborative Editing and Execution in Shared Byoby Sessions

• TidyX Episode 62 | Data Cleaning - Regex Applied & stringr : Ellis Hughes and Patrick Ward continue their regular expressions exploration

Gist & Cookbook

• Modeling and simulation of the Euro Cup by Luke Benz

Tutorials

• Don’t forget your inits

• Everybody Loves Raymond: Running Animal Crossing Villagers through the Google Vision API

• Using Geospatial Data in R

• Functional PCA with R

• Financial X-Rays: Dissect any Price Series with a simple Payoff Diagram

• Stream makes a streamplot

• Estimating multilevel models for change in R

• Hierarchical forecasting of hospital admissions

• Visualizing Distributions with Raincloud Plots with ggplot2

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• R in spoRts analytics!

• Upcoming Webinar - Incorporating R into your Clinical Legacy Workflows

• A list of R conferences and meetings

• This week’s local R-User and applied stats events

Datasets

• Russian Journals indexed by Scopus, RSCI, and WoS

Call for Participation

• Coding in the Open – lunchtime seminars

Your support will keep R Weekly team moving! 💡

Quotes of the Week

How much do you need to earn to be able to buy the average house in your region?
I saw an equivalent map for the US and decided to replicate it for NZ. Based on the common financial advice that you shouldn't spend more than 30% of your income on your housing. #rstats #rspatial pic.twitter.com/sUvLWT2QoJ

— Emma Vitz (@EmmaVitz) June 9, 2021

Oh, you write R code? Well how about I follow you and like all your tweets 😤

— Afton Leigh Coombs (@aftonsteps) June 11, 2021

It is what it is. #RStats #RStudio #poptwitter #dataviz #DataScience pic.twitter.com/bDLSEDm2LV

— Corina McCullough Vidal, M.S. (@demography101) June 8, 2021