📈 R Data Science Digest August 2021
A list of the most popular posts featured on R Posts you might have missed! in July 2021. All of the most exciting R resources in visualisation, data analysis and lots more!
📱 {shinyMobile} • Develop outstanding {shiny} apps for iOS, Android, desktop as well as beautiful {shiny} gadgets. {shinyMobile} is built on top of the latest Framework7 template by David Granjon, Victor Perrier and Isabelle Rudolf.
If you can code shiny, you can write an app! Easily create great looking and full-screen mobile applications using the power of shiny! Check out the cheatsheet here.
🗺️ {mapsf}, a new package for thematic mapping by Timothée Giraud.
Up your mapping game with {mapsf}, a new package to easily make thematic maps with a variety of powerful layers, and options for theming, layouts, creating insets and a lot more!
☁️ How to automate an R script on Google Cloud by Ander Fernández Jauregui.
Get up to speed with Google Cloud to run your code for you! It can be a daunting task to learn how to use GCP to schedule your code to run in the cloud. This article runs through the main steps required to set up and use Cloud Build and Cloud Scheduler to get you started.
📊 Visualisation
📦 BBC Visual and Data Journalism cookbook for R graphics • How to create BBC style graphics by BBC Open Source.
✍️ Data-driven flowcharts in R using {DiagrammeR} by Michael Harper.
✍️ The Brewer palettes by Jose M. Sallan.
📦{camcorder} • Record plots generated during an R session and replay as a gif! by Ellis Hughes.
✍️ Improving a Visualization by Jonathan Carroll.
✍️ Making a Circular Plot • R Graphics Cookbook, 2nd edition by Winston Chang.
✍️ A Quick How-to on Labelling Bar Graphs in {ggplot2} by Cédric Scherer.
✍️ Alternatives to Simple Color Legends in {ggplot2} by Meghan Hall.
✍️ Line chart with labels at end of lines – the R Graph Gallery by Cédric Scherer, Yan Holtz and Tomas Capretto.
📚 Data visualisation using R, for researchers who don’t use R by Emily Nordmann, Phil McAleer, Wilhelmiina Toivo, Helena Paterson and Lisa DeBruine.
📦{ggtrack} • ggtrack, add a tracking banner to your plots by Matt Johnson.
🌐 Spatial analysis
✍️ GIS and mapping by Robin Lovelace and Jakub Nowosad.
✍️ ️ Average colors of the world by Erin Davis.
📦 {sfnetworks}: Tidy Geospatial Networks in R by Luuk van der Meer and Lorena Abad.
✍️ Creating a figure of map layers in R • Urban Demographics by Rafael H.M. Pereira.
✍️ Introduction to GIS with R • Spatial data with the {sp} and {sf} packages by Jesse Sadler.
📚 Spatial Microsimulation with R by Robin Lovelace and Morgane Dumont.
📦 {exactextractr} • Fast Extraction from Raster Datasets using Polygons by Daniel Baston.
🔢 Statistics
📦 {modelsummary} • creates tables and plots to summarize statistical models and data in R by Vincent Arel-Bundock.
📦 {supernova} • An R package for teaching statistics from a modeling perspective by Adam Blake, Jeff Chrabaszcz, Ji Son and Jim Stigler.
Teaching and Learning Bayesian Statistics with {bayesrules} by Mine Dogucu.
✍️ Efficient simulations in R by Grant McDermott.
✍️ The Grammar of Experimental Design by Emi Tanaka.
📚 Regression Modeling in People Analytics: Survival Analysis by Keith McNulty.
🎓 Learning resources
🎓 RBootcamp · A free online course about the basics of the tidyverse by Ted Laderas and Jessica Minnier.
📦 awesome-r-learning-resources • A curated collection of free resources to help deepen your understanding of the R programming language by Eric Fletcher.
✍️ Beginner’s Guide to Creating an R Shiny App: A step-by-step tutorial of creating an R Shiny app from scratch by Yasmine Hejazi.
A fun Intro to R Programming by Fabio Votta.
✍️ 10 new books added to Big Book of R by Oscar Baruffa.
✍️ Digging deeper: online resources for intermediate to advanced R users by Edouard Mathieu.
🎓 lecturenotes • My lecture notes Rmd template by Grant McDermott.
🔧 Data manipulation
📦 {multidplyr} • A dplyr backend that partitions a data frame over multiple processes by Hadley Wickham.
✍️ Learn to purrr by Rebecca Barter.
✍️ Five things you never knew you could do with dplyr by Keith McNulty.
✍️ A {data.table} and {dplyr} tour by Atrebas.
🤖 Machine learning
📚 Hands-On Machine Learning with R by Bradley Boehmke & Brandon Greenwell.
✍️ Tired: PCA + kmeans, Wired: UMAP + GMM • An Alternative to the Classic Approach to Dimension Reduction + Clustering by Tony ElHabr.
✍️ Advanced Data Science in R: Interpretable Machine Learning by Lisa Lendway.
✍️ Deploying a simple ML model with Plumber 101 • Computer Science Notes by Harpo MAxx.
🛠️ Tools and utilities
📦 {textme} • Send text messages from R to your cell phone to notify you when long-running jobs complete by Rich Pauloo.
✍️ Using SQL in RStudio by Irene Steves.
📦 {openxlsx} • openxlsx • a fast way to read and write complex xslx files by Philipp Schauberger and Alex Walker.
📦 {gt} • Easily generate information-rich, publication-quality tables from R by Richard Iannone, Joe Cheng and Barret Schloerke.
✍️ Automate PowerPoint Production Using R by Joe Noonan.
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