R Weekly 2021-W07 Installing Packages, {distill}, {shiny} App Stories

This article is originally published at

Hello and welcome to this new issue!

Release Date: 2021-02-15

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

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

Highlight

• The Comprehensive Guide to Installing R Packages from CRAN, Bioconductor, GitHub and Co.
• Distill it down
• Introducing Shiny App Stories

Insights

• Some general thoughts on Partial Dependence Plots with correlated covariates
• Little useless-useful R functions – Use pipe %>% in ggplot2
• New activation functions in mlsauce’s LSBoost
• Introducing Shiny App Stories

• Understand your models with #TidyTuesday inequality in student debt
• The Comprehensive Guide to Installing R Packages from CRAN, Bioconductor, GitHub and Co.
• Target: monitoring a running goal in R
• Painful Package Management
• torch, tidymodels, and high-energy physics
• Distances to Golda Ice-Cream Locations in Israel - see here for scripts/data

• Microsoft365R: an R interface to the Microsoft 365 suite
• How to be Successful! The Role of Risk-taking: A Simulation Study
• Teaching Quantitative Social Science in Times of COVID-19: How to Generate and Distribute Individualized Exams with R and RMarkdown
• coder Makes Medical Coding less Messy
• Little useless-useful R functions – Useless R poem for Valentine

• Distill it down
• Fully Native M1/Apple Silicon R Setup
• Getting a Handle on macOS App Entitlements with R
• It Has Always Been Wrong to Call order on a data.frame
• Causal effect of Elon Musk tweets on Dogecoin price
• Understanding Variance Explained in PCA – Algebraic interpretation
• Feel like the cat that got the cream with {forcats}. Tame your categorical data using the {forcats} package.

R in the Real World

• Decoding Case Data Through the COVID-19 Data Hub

R in Organizations

• {microsoft365r}: R SDK for interacting with Microsoft 365 APIs

R in Academia

• Nowosad, J. Motif: an open-source R tool for pattern-based spatial analysis. Landscape Ecol 36, 29–43 (2021). https://doi.org/10.1007/s10980-020-01135-0

Resources

• Introductory R/exams Course by Andrew Zammit-Mangion

• Using the flextable R package

New Packages

???? Go Live for More New Pkgs ????

CRAN

• td 0.0.1 on CRAN: New Finance Data Package
• {coder}: Deterministic Categorization of Items Based on External Code Data.
• {visStatistics} 0.1.1: Automated Visualization of Statistical Tests
• {ggprism} 1.0.1: A ‘ggplot2’ Extension Inspired by ‘GraphPad Prism’
• {folio} 1.0.0: Datasets for Teaching Archaeology and Paleontology
• {httpproblems} 1.0.0: Report Errors in Web Applications with ‘Problem Details’ (RFC 7807)
• {box} 1.0.0: Write Reusable, Composable and Modular R Code
• {wordpiece} 1.0.2: R Implementation of Wordpiece Tokenization
• {ROCket} 1.0.0: Simple and Fast ROC Curves
• {osmextract} 0.2.0: Download and Read OpenStreetMap Data Extracts
• {astrochron} 1.0: A Computational Tool for Astrochronology
• {ggh4x} 0.1.2.1: Hacks for ‘ggplot2’
• {covidprobability} 0.1.0: Estimate the Unit-Wide Probability of COVID-19
• {ORTSC} 1.0.0: Connects to Google Cloud API for Label Detection
• {blaster} 1.0: Native R Implementation of an Efficient BLAST-Like Algorithm
• {ontologyPlot} 1.6: Visualising Sets of Ontological Terms
• {tastypie} 0.0.2: Easy Pie Charts
• {omsvg} 0.1.0: Build and Transform ‘SVG’ Objects
• {ggstar} 1.0.1: Star Layer for ‘ggplot2’
• {bsTools} 0.1.0: Create HTML Content with Bootstrap 5 Classes and Layouts
• {quarto} 0.1: R Interface to ‘Quarto’ Markdown Publishing System
• {multidplyr} 0.1.0: A Multi-Process ‘dplyr’ Backend
• {patentr} 0.1.0: Access USPTO Bulk Data in Tidy Rectangular Format
• {detectR} 0.1.0: Change Point Detection
• {Rwtss} 0.8.0: Client for Web Time-Series Service
• {cronologia} 0.1.0: Create an HTML Vertical Timeline from a Data Frame in ‘rmarkdown’ and ‘shiny’
• {benford} 0.1.0: Benford’s Analysis on Large Data Sets

Updated Packages

• RcppSimdJson 0.1.4 on CRAN: New Improvements
• RcppSMC 0.2.3 on CRAN: Updated Snapshot
• RcppArmadillo 0.10.2.1.0: New Upstream Release
• {mime} 0.10: Map Filenames to MIME Types
• {cachem} 1.0.4: Cache R Objects with Automatic Pruning
• {RVA} 0.0.4: RNAseq Visualization Automation
• {fulltext} 1.7.0: Full Text of ‘Scholarly’ Articles Across Many Data Sources
• {RcppSimdJson} 0.1.4: ‘Rcpp’ Bindings for the ‘simdjson’ Header-Only Library fo ‘JSON’ Parsing
• {resumer} 0.0.5: Build Resumes with R
• {MASS} 7.3-53.1: Support Functions and Datasets for Venables and Ripley’s MASS
• {promises} 1.2.0.1: Abstractions for Promise-Based Asynchronous Programming
• {wordpressr} 0.2.1: An API Wrapper for WordPress Site APIs
• {Tplyr} 0.4.0: A Grammar of Clinical Data Summary
• {shinyloadtest} 1.1.0: Load Test Shiny Applications
• {waldo} 0.2.4: Find Differences Between R Objects
• {billboarder} 0.3.0: Create Interactive Chart with the JavaScript ‘Billboard’ Library
• {websocket} 1.3.2: ‘WebSocket’ Client Library
• {xfun} 0.21: Miscellaneous Functions by ‘Yihui Xie’
• {rfishbase} 3.1.6: R Interface to ‘FishBase’
• {RcppSMC} 0.2.3: Rcpp Bindings for Sequential Monte Carlo
• {prettyB} 0.2.2: Pretty Base Graphics
• {usethis} 2.0.1: Automate Package and Project Setup
• {stopwords} 2.2: Multilingual Stopword Lists
• {RcppArmadillo} 0.10.2.1.0: ‘Rcpp’ Integration for the ‘Armadillo’ Templated Linear Algebra Library
• {systemfonts} 1.0.1: System Native Font Finding
• {AzureGraph} 1.2.1: Simple Interface to ‘Microsoft Graph’
• {survivalmodels} 0.1.6: Models for Survival Analysis
• {readabs} 0.4.8: Download and Tidy Time Series Data from the Australian Bureau of Statistics
• {fabricatr} 0.14.0: Imagine Your Data Before You Collect It
• {crayon} 1.4.1: Colored Terminal Output
• {qs} 0.23.6: Quick Serialization of R Objects

Videos and Podcasts

• TidyX Episode 48: NBA Game Simulation, purrr, and base R distribution functions

• Shiny Developer Series: Inside the most over-the-top Shiny apps for a virtual racing league!

• Upcoming Why R Webinar - Interpretation of single-cell RNA-seq trajectories

• Why R Webinar: brms: Bayesian Regression Models using Stan

Tutorials

• Spatially-constrained clustering and regionalization in R

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

Jobs

• Data Librarian/Analyst - EcoHealth Alliance

Call for Participation

• 28th Feb: Upcoming Why R Webinar - Efficient computation with R

• 15th Mar: useR2021 Call for Abstracts

• 31st Mar: EARL 2021 Call for Abstracts

Your support will keep R Weekly team moving! ????

Quotes of the Week

@emilyriederer's blog post on "Building a team of internal R packages" mentions rOpenSci's dev Guide (https://t.co/H8YnkzHZoU) as a resource on package design, and with special reference to function naming. https://t.co/fVF3eBFbh7

— rOpenSci (@rOpenSci) February 10, 2021

A nice new feature in RStudio as it's now possible to track Memory Usage interactively

PS: it's only available in the daily builds.#RStats pic.twitter.com/IleaWXqgGY

— Ihaddaden M. EL Fodil, Ph.D (@moh_fodil) February 10, 2021

If you use #rstats {tidyverse} and {MASS}, this will save you a lot of grief. h/t @thomas_neitmann pic.twitter.com/5cb3fqIt3U

— Ed Hagen (@ed_hagen) February 10, 2021

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