R Weekly 2020-41 package development topics, contributing to rOpenSci, learnr and shiny

12 Oct 2020

Release Date: 2020-10-12

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

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

Highlight

• Picking and researching blog topics about R package development

• Hacktober? Any Month is a Good Month to Contribute to rOpenSci

• Shiny Developer Series Episode 14 - Shining a Light on {learnr}

Insights

• Picking and researching blog topics about R package development

• The day after

• RStudio v1.4 Preview: Python Support

• 3.84 or: How to Detect BS (Fast)

• Using torch modules

• Hacktober? Any Month is a Good Month to Contribute to rOpenSci

• Le Monde puzzle [#1159]

R in the Real World

• Excess Deaths by Jurisdiction

• Excess Deaths by Cause

• RTutor: How do competition policy and industrial policy affect economic development?

• Open States data & the New Mexico State Senate

R in Organizations

• NHS-R Community Member Profile

• Using R to Drive Agility in Clinical Reporting: Questions and Answers

R in Academia

• Applying psychonetrics to Compare Psychometric Factor and Network Models

• Writing Data Science in Education Using R in the Open

Resources

• Scheduling R scripts

• From R to WordPress in two easy steps

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {SSHAARP} 1.0.1: Searching Shared HLA Amino Acid Residue Prevalence

• {T4transport} 0.1.0: Tools for Computational Optimal Transport

• {gglm} 0.1.0: Grammar of Graphics for Linear Model Diagnostic Plots

• {AirSensor} 1.0.2: Process and Display Data from Air Quality Sensors

• {spDates} 1.0: Analysis of Spatial Gradients in Radiocarbon Dates

• {quickerstats} 0.0.1: An ‘R’ Client for the ‘USDA NASS Quick Stats API’

• {MSGARCHelm} 0.1.0: Hybridization of MS-GARCH and ELM Model

• {dCUR} 1.0.0: Dimension Reduction with Dynamic CUR

• {EHR} 0.3-1: Electronic Health Record (EHR) Data Processing and Analysis Tool

• {LDheatmap} 1.0-4: Graphical Display of Pairwise Linkage Disequilibria Between SNPs

• {sketch} 1.0.3: Interactive Sketches

• {BIGDAWG} 2.3.1: Case-Control Analysis of Multi-Allelic Loci

• {TVMM} 3.2: Multivariate Tests for the Vector of Means

• {skynet} 1.4.0: Generates Networks from BTS Data

• {modeltime.ensemble} 0.2.0: Ensemble Algorithms for Time Series Forecasting with Modeltime

• {hdiVAR} 1.0.1: Statistical Inference for Noisy Vector Autoregression

• {fanovaGraph} 1.5: Building Kriging Models from FANOVA Graphs

• {satin} 1.0: Visualisation and Analysis of Ocean Data Derived from Satellites

• {quantdr} 1.0.0: Dimension Reduction Techniques for Conditional Quantiles

• {PVplr} 0.1.0: Performance Loss Rate Analysis Pipeline

• {Momocs} 1.3.2: Morphometrics using R

• {sivs} 0.2.2: Seed Independent Variable Selection

• {occCite} 0.3.0: Querying and Managing Large Biodiversity Occurrence Datasets

• {cmsafvis} 1.0.0: Visualize CM SAF NetCDF Data

• {suppdata} 1.1-4: Downloading Supplementary Data from Published Manuscripts

• {blink} 1.1.0: Record Linkage for Empirically Motivated Priors

• {treeducken} 1.0.0: Nested Phylogenetic Tree Simulator

• {FunWithNumbers} 1.0: Fun with Fractions and Number Sequences

• {CNAIM} 1.0.0: Common Network Asset Indices Methodology (CNAIM)

• {winch} 0.0.1: Portable Native and Joint Stack Traces

• {REPPlabShiny} 0.4.0: ‘REPPlab’ via a Shiny Application

• {pvldcurve} 1.2.6: Simplifies the Analysis of Pressure Volume and Leaf Drying Curves

• {mapboxapi} 0.2: R Interface to ‘Mapbox’ Web Services

• {animalEKF} 1.1: Extended Kalman Filters for Animal Movement

• {PairViz} 1.3.4: Visualization using Graph Traversal

• {gmGeostats} 0.10-7: Geostatistics for Compositional Analysis

• {zenplots} 1.0.2: Zigzag Expanded Navigation Plots

• {priceR} 0.1.5: Economics and Pricing Tools

• {collidr} 0.1.3: Check for Namespace Collisions Across Packages and Functions on CRAN

• {concreg} 0.7: Concordance Regression

• {stfit} 0.99.8: Spatio-Temporal Functional Imputation Tool

BioC

GitHub or Bitbucket

• {cspp}: A Package for The Correlates of State Policy Project Data

• {rockthemes}: R colour palettes based on classic (rock) albums

• Introducing devoutrgl - a 3d graphics device targetting rgl

Updated Packages

• {readr} 1.4.0

• RcppSimdJson 0.1.2: Upstream update

• littler 0.3.12: Exciting updates

• Robust covariance matrix estimation: sandwich 3.0-0, web page, JSS paper

• {wrGraph} 1.0.5: Graphics in the Context of Analyzing High-Throughput Data

• {stringdist} 0.9.6.3: Approximate String Matching, Fuzzy Text Search, and String Distance Functions

• {textshaping} 0.1.2: Bindings to the ‘HarfBuzz’ and ‘Fribidi’ Libraries for Text Shaping

• {callr} 3.5.0: Call R from R

• {analogsea} 0.9.0: Interface to ‘Digital Ocean’

• {waldo} 0.2.1: Find Differences Between R Objects

• {clipr} 0.7.1: Read and Write from the System Clipboard

• {sunburstR} 2.1.5: Sunburst ‘Htmlwidget’

• {dittodb} 0.1.2: A Test Environment for Database Requests

• {gert} 1.0.0: Simple Git Client for R

• {Tplyr} 0.1.3: A Grammar of Clinical Data Summary

• {tinytest} 1.2.3: Lightweight and Feature Complete Unit Testing Framework

• {bigrquery} 1.3.2: An Interface to Google’s ‘BigQuery’ ‘API’

• {readabs} 0.4.5: Download and Tidy Time Series Data from the Australian Bureau of Statistics

• {ggspectra} 0.3.7: Extensions to ‘ggplot2’ for Radiation Spectra

• {htmlwidgets} 1.5.2: HTML Widgets for R

• {shinyWidgets} 0.5.4: Custom Inputs Widgets for Shiny

Videos and Podcasts

• Sentiment Analysis in R with Custom Lexicon Dictionary using tidytext

• Shiny Developer Series Episode 14 - Shining a Light on {learnr}

• Modeling #TidyTuesday NCAA women’s basketball tournament seeds

Gist & Cookbook

• Side-by-side input widgets in Shiny

Shiny Apps

• {shinyMatrix} 0.4.0: Shiny Matrix Input Field

• {shinyML} 1.0.0: Compare Supervised Machine Learning Models Using Shiny App

• Building a (Hockey) Shot-Plotting App in Shiny

• I Generated a Sample Survey Product with Shiny

Tutorials

• Diagonal gridlines in 2 ways

• Expected Goals - Overachieving or just lucky?

• Spatial Data Analysis Using Artificial Neural Networks Part 1

• Simulation of dependent variables in ESGtoolkit

• Optimizers in torch

• Fake Survival Data for the Disease Progression Model

• Installing and switching to MKL on Fedora

• How to use %in% in R: 7 Example Uses of the Operator

• Tutorial on how to build a random forest model using ranger and DALEX as a first baseline in analysis.

• An R Pipeline for XGBoost Part I

• Hosting a {plumber} API with Kubernetes

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

Datasets

• Downloading food web databases and deriving basic structural metrics

• {pmlbr} 0.2.0: Interface to the Penn Machine Learning Benchmarks Data Repository

Call for Participation

• We Run for RLadies

• Glosario Sprint

Your support will keep R Weekly team moving! 💡

Quotes of the Week

How it started. How it’s going. pic.twitter.com/HOTHA1N9Bn

— Julia Silge (@juliasilge) October 9, 2020

Hacked something together: an R addin/shiny app to learn SQL using duckdb and built-in R datasets. Each exercise asks you to replicate a dplyr ordata.table statement in sql. https://t.co/bsc6ibbCIo

Just a proof of concept of a quick idea. Feedback welcome. #rstats pic.twitter.com/zIytjxFpOQ

— Dirk Schumacher🚲 (@dirk_sch) October 11, 2020

Hey #rstats, 📦 vembedr 1.4.0 now on CRAN 🎉

Embed videos from YouTube, Vimeo, and more in RMarkdown HTML documents!https://t.co/5wH54gAYlz pic.twitter.com/SEejZ60SoL

— Ian Lyttle (@ijlyttle) October 11, 2020