文件列表:

code_of_conduct.md (3355, 2023-04-14)
contributing.md (1299, 2023-04-14)
license (7048, 2023-04-14)

> The `Awesome R Learning Resources` repository is meant to help users from all skill levels and backgrounds deepen their understanding of `R`, which is a programming language and environment for statistical computing and graphics.
> The `R` `Discord` server is a friendly and dedicated community for `R` enthusiasts, programmers, statisticians, data scientists, and students. Whether you are looking to connect with fellow useRs, have awesome data viz to share, or just needed help with your stats assignment, you are at the right place!
## **Contents** - [Topic Areas](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#topic-areas) - [Blogs](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#blogs) - [Books](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#books) - [Communities of Practice](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#communities-of-practice) - [Podcasts](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#podcasts) - [YouTube](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/#youtube) ## Topic Areas ### Comprehensive R Tutorials - [Data Flair](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://data-flair.training/blogs/r-tutorials-home/) - The tutorials are grouped by skill level (beginner, intermediate, expert). - [Intro to R course by Fabio Votta - part 1](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://colab.research.google.com/drive/1dLsdGbkvgn1JbWgsy9Z-pFmPd_2MG4Xu?usp=sharing#scrollTo=vGnW7giO9AeD) - A fun introduction to R programming grouped into categories (operators, objects, functions, exercises, and data frames). - [Intro to R course by Fabio Votta - part 2](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://colab.research.google.com/drive/14CRElnKewnp5MnlxhqVu6OOcIXd-Bkaj?usp=sharing) - A fun introduction to R programming grouped into categories (data manipulation and cleaning featuring the janitor, tidyr, and dplyr packages). - [Introduction to Data Analysis with R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://jmbuhr.de/dataIntro20/) - This is a lecture series with videos, scripts and exercises introducing R and the tidyverse as well as statistical concepts. - [R CODER](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://r-coder.com) - The tutorials are grouped into categories (introduction, data structures, data wrangling, programming, import & export, graphics) that cover in-depth all the basic needs for someone starting learning the R programming language. - [Tutorials Point](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.tutorialspoint.com/r/index.htm) - The tutorials are grouped into categories (R tutorial, R Data Interfaces, R Charts & Graphs, R Statistics Examples, R Useful Resources) that cover in-depth all the basic needs for someone starting learning the R programming language. ### Functions - [stat.berkeley - Introduction to Functions](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.stat.berkeley.edu/~statcur/Workshop2/Presentations/functions.pdf) - An introduction to functions in the R language by the organizers of Integrating Computing into the Statistics Curricula (U.C. Berkeley). ### Generative Art - [12 Months of aRt](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.williamrchase.com/work/art/) - In 2019, William Chase began a project to make a new series of artwork every month made entirely with R. In this project, he explored different techniques, developed algorithms, and provided detailed posts detailing the development process for each month. ### Joining Data - [Joining Data in R with dplyr](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://rpubs.com/williamsurles/293454) - Course notes from the Joining Data in R with dplyr course on DataCamp. Topics include mutating joins, filtering joins and set operations, assembling data, advanced joining. Author: William Surles. ### Math - [Descriptive Statistics](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://rcompanion.org/handbook/C_02.html) - A tutorial of descriptive statistics which are used to summarize data in a way that provides insight into the information contained in the data. Author: Salvatore S. Mangiafico. - [Descriptive statistics in R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://statsandr.com/blog/descriptive-statistics-in-r/) - This article explains how to compute the main descriptive statistics in R and how to present them graphically. Author - Antoine Soetewey. - [Essential Math for Data Science](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://medium.com/s/story/essential-math-for-data-science-why-and-how-e88271367fbd) - An article discussing the key mathematical topics to master to become a better data scientist. Author: Tirthajyoti Sarkar. - [Gallery of Statistical Distributions](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.itl.nist.gov/div8***/handbook/eda/section3/eda366.htm) - Author: NIST/SEMATECH. - [Plotting distributions (ggplot2)](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/http://www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)/) - A tutorial for plotting a distribution of data. Author: Winston Chang. ### Shiny - [Awesome R Shiny](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://github.com/grabear/awesome-rshiny) - A curated list of resources for R Shiny. Author: Rob Gilmore. - [Building Shiny Applications with R Tutorial (Deprecated)](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://rstudio.github.io/shiny/tutorial/#) - Introductory tutorial to Shiny. Note, this tutorial is deprecated. Author: RStudio. - [Building Shiny apps - an interactive tutorial](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://deanattali.com/blog/building-shiny-apps-tutorial/) - This tutorial is a hands-on activity complement to a set of [presentation slides](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://docs.google.com/presentation/d/1dXhqqsD7dPOOdcC5Y7RW--dEU7UfU52qlb0YD3kKeLw/edit) for learning how to build Shiny apps. Author: Dean Attali. - [How to Start with Shiny](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://vimeo.com/rstudioinc/review/131218530/212d8a5a7a) - Detailed introductory video tutorial. Author: Garrett Grolemund. - [Learn Shiny](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://shiny.rstudio.com/tutorial/) - The video and written tutorials on this page are primarily designed for users who are new to Shiny and want a guided introduction. Author: RStudio. - [Shiny Articles](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://shiny.rstudio.com/articles/) - Various articles covering individual Shiny topics at a more advanced level. Author: RStudio. ### Spatial - [An Introduction to Choropleth maps in R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://rstudio-pubs-static.s3.amazonaws.com/324400_69a673183ba449e9af4011b1eeb456b9.html) - Author: Henry Cann. - [Getting latitude & longitude for any address](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://discourse.looker.com/t/get-latitude-longitude-for-any-location-through-google-sheets-and-plot-these-in-looker/5402) - Author: Brecht Vermeire. - [Map Plots Created With R And Ggmap](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.littlemissdata.com/blog/maps) - Author: Laura Ellis. - [Plot Spatial Data / Shapefiles in R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.youtube.com/watch?v=uZtto0cYjZM) - From the "math et al" YouTube channel. ### Viz - [A ggplot2 Tutorial for Beautiful Plotting in R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://cedricscherer.netlify.app/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/) - A comprehensive and easy to follow tutorial that covers working with axes, titles, legends, backgrounds, grid lines, margins, multi-panel plots, colors, themes, lines, text, coordinates, chart types, ribbons, smoothings, and interactive plots. Author: Cedric Scherer. - [Awesome ggplot2](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://github.com/erikgahner/awesome-ggplot2) - A curated list of awesome ggplot2 tutorials, packages etc. Author: Erik Gahner Larsen. - [Chart Suggestions — A thought-starter on choosing the way to show your data](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://extremepresentation.typepad.com/files/choosing-a-good-chart-09.pdf) - Author: Andrew Abela, Ph.D. - [Color Hex Color Codes](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.color-hex.com/) - Author: Color-Hex. - [Combine Multiple GGPlots into a Figure](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.datanovia.com/en/lessons/combine-multiple-ggplots-into-a-figure/) - Author: Alboukadel Kassambara. - [Coolors](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://coolors.co/) - The super fast color schemes generator! Create the perfect palette or get inspired by thousands of beautiful color schemes. Features include color picker, pick palette from photo, create a collage, make your own gradient palette, create a gradient, contrast checker, etc. - [From Data to Viz](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.data-to-viz.com/) - From Data to Viz leads you to the most appropriate graph for your data. Author: Yan Holtz. - [ggplot2 extensions - gallery](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://exts.ggplot2.tidyverse.org/gallery/) - Maintained by Daniel Emaasit. - [ggplot2 - Modify components of a theme](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://ggplot2.tidyverse.org/reference/theme.html) - How to modify components of a theme in ggplot2. Author: the developers of Tidyverse. - [Graphics in R with ggplot2](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.statsandr.com/blog/graphics-in-r-with-ggplot2/) - A detailed guide for the use of graphics within ggplot2. Author: Antoine Soetewey. - [htmlwidgets for R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.htmlwidgets.org/) - Showcase and gallery of the various interactive web visualizations you can build using R. - [r-color-palettes](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://github.com/EmilHvitfeldt/r-color-palettes) - Comprehensive list of color palettes available in r. Author: Emil Hvitfeldt. - [The Data Visualization Catalogue](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://datavizcatalogue.com/index.html) - The Data Visualization Catalogue is a project developed by Severino Ribecca to create a library of different information visualization types. - [The Graphic Continuum](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.informationisbeautifulawards.com/showcase/611-the-graphic-continuum) - The Graphic Continuum shows the many different types of visualizations available to us when we encode and present data. Authors: Jonathan Schwabish, and Severino Ribecca. - [The R Graph Gallery](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.r-graph-gallery.com/) - A collection of charts made with the R programming language. Author: Yan Holtz. - [Time Based Heatmaps in R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.littlemissdata.com/blog/heatmaps) - Author: Laura Ellis. - [Top 50 ggplot2 Visualizations - The Master List (With Full R Code)](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html) - This tutorial helps you choose the right type of chart for your specific objectives and how to implement it in R using ggplot2. Author: Selva Prabhakaran. ### Web Scraping - [Web Scraping Reference: Cheat Sheet for Web Scraping using R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://github.com/yusuzech/r-web-scraping-cheat-sheet) - Guide, reference and cheatsheet on web scraping using rvest, httr and Rselenium. Author: [yifyan et al.](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://github.com/yusuzech) ### Wrangling - [Data Wrangling Part 1: Basic to Advanced Ways to Select Columns](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://suzan.rbind.io/2018/01/dplyr-tutorial-1/) - Author: Suzan Baert. - [Data Wrangling Part 2: Transforming your columns into the right shape](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://suzan.rbind.io/2018/02/dplyr-tutorial-2/) - Author: Suzan Baert. - [Data Wrangling Part 3: Basic and more advanced ways to filter rows](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://suzan.rbind.io/2018/02/dplyr-tutorial-3/) - Author: Suzan Baert. - [Data Wrangling Part 4: Summarizing and slicing your data](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://suzan.rbind.io/2018/04/dplyr-tutorial-4/) - Author: Suzan Baert. ### Uncategorized - [Data.Table and Dplyr Tour](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://atrebas.github.io/post/2019-03-03-datatable-dplyr/#reshape-data) - A detailed comparison of R packages data.table and dplyr. Author: Atrebas. - [data.table: A gentle introduction](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://atrebas.github.io/post/2020-06-17-datatable-introduction/) - A quick introduction to data.table. The main objective is to present the data.table syntax, showing how to perform basic, but essential, data wrangling tasks. Author: Atrebas. - [Fakir - Create Fake Data in R for Tutorials](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://thinkr-open.github.io/fakir/) - Author: Colin Fay. - [From base R to stringr](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://stringr.tidyverse.org/articles/from-base.html) - This vignette compares stringr functions to their base R equivalents to help users transitioning from using base R to stringr. Author: Sara Stoudt. - [Help me help you: creating reproducible examples](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.youtube.com/watch?v=5gqksthQ0cM) - Making a great reprex is both an art and a science and this webinar will cover both aspects. A reprex makes a conversation about code more efficient and pleasant for all. This comes up whenever you ask someone for help, report a bug in software, or propose a new feature. The reprex package (https://reprex.Tidyverse.org) makes it especially easy to prepare R code as a reprex, in order to share on sites such as https://community.rstudio.com, https://github.com, or https://stackoverflow.com. Author: Jenny Bryan. - [R - discoRd server](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://discord.gg/88uG5UVyE2) - Dedicated discoRd server with the following topic-based channels: `R-Main` for more general discussions, `R-Share` for showing off your data visuals, `General R Help` for asking questions and sharing learning resources, and `Topical Help/Discussion` for issues dealing with statistics, dbi, tidymodels, shiny, natural-science, social-science, bayesians, gis, and finance. - [Subreddit - r/Rlanguage - R Programming Language](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.reddit.com/r/Rlanguage/new/) - A Reddit subreddit focused on implementing the R programming language for statistics and data science. - [Subreddit - r/programming - The R Project for Statistical Computing](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.reddit.com/r/rprogramming/) - A Reddit subreddit focused on using R for statistical computing. - [Syntax equivalents: base R vs Tidyverse](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://tavareshugo.github.io/data_carpentry_extras/base-r_tidyverse_equivalents/base-r_tidyverse_equivalents.html) - A detailed comparison of base R and tidyverse. Author: Hugo Tavares. - [The ultimate R data.table cheat sheet](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.infoworld.com/article/3575086/the-ultimate-r-datatable-cheat-sheet.html) - Find code for dozens of data tasks in this searchable cheat sheet of R data.table and Tidyverse code. Author: Sharon Machlis. ## Blogs - [Alex Cookson](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.alexcookson.com/) - Alex Cookson loves making beautiful visualizations and easy-to-read walkthroughs of R concepts. He's particularly interested in data about media, like books, movies, and musicals. - [Avery Robbins](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.avery-robbins.com) - Avery Robbins loves to learn and to share useful or awesome things that have benefited him personally. This website is a tool for him to actively do just that: share knowledge, ideas, and tips that are helpful. - [Tony ElHabr](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://tonyelhabr.rbind.io/) - Tony ElHabr is passionate mostly about energy markets and sports analytics. His blog provides detailed tutorials, project explanations, and presentations. - [Cedric Scherer](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://cedricscherer.netlify.app/) - Cedric Scherer is a graduated computational ecologist and freelance data visualization expert who has created visualizations across all disciplines, purposes, and styles and regularly teaches data visualization principles, R, and ggplot2. - [Data Imaginist](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.data-imaginist.com/) - Thomas Lin Pedersen is a data scientist turned software engineer who focuses on improving researchers’ interactions with the data they produce. - [Data meets Narrative](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/http://www.rebeccabarter.com/blog/) - Rebecca Barter enjoys making sense of complex, messy and sometimes nonsensical datasets, such as electronic health records, and insurance claims. Her dual passions are explaining “seemingly complicated” concepts to others in plain English, and exploring and uncovering the stories that underlie complex datasets. - [HighlandR](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://johnmackintosh.net/) - John Mackintosh's blog is a place for him to showcase demonstrations or workshops, notes he's learned at work, chart makeovers, and techniques and technology that he doesn't currently use in his role. - [Julia Silge](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://juliasilge.com/blog/) - Julia Silge is a data scientist and software engineer at RStudio where she work on open source modeling tools. She is passionate about making beautiful charts, the statistical programming language R, Jane Austen, black coffee, and red wine. - [Musings on R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://martinctc.github.io/blog/) - A blog on all things R and Data Science by Martin Chan. Topics covered include comparing dplyr and data.table, Shiny apps, ggplot, data cleaning, using RStudio, interviews with other R users/data scientists, and web scraping. - [rweekly](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://rweekly.org/about) - Weekly Updates from the Entire R Community by Bruce Zhao, Colin Fay, Eric Nantz, Hao Zhu, Jon Calder, Jonathan Carroll, Maelle Salmon, Ryo Nakagawara, and Wolfram Qin. - [r-bloggers](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.r-bloggers.com/) - R-Bloggers.com was created by Tal Galili and is a blog aggregator of content contributed by bloggers who write about R (in English). The site helps R bloggers and users to connect and follow the R blogosphere. - [Ryo Nakagawara](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://ryo-n7.github.io/) - Ryo Nakagawara is a Data Scientist and has been doing work as both a reporting analyst and a software developer in R and SQL to improve ACDI and VOCA data pipelines, create R packages, reproducible reports, dashboards, and Shiny apps to communicate how his projects worldwide are progressing. - [Statistics Globe](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://statisticsglobe.com/) - Joachim Schork started this platform to share his statistical know-how and to improve his own statistical skills by discussing with other statisticians and programmers. - [Stats and R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://www.statsandr.com/) - Through his blog, Antoine Soetewey (PhD in statistics) aims at helping academics and professionals working with data to grasp important statistical concepts, and shows how to apply them in R. ## Books - [A Sufficient Introduction to R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://dereksonderegger.github.io/570L/) - This book is intended to guide people that are completely new to programming along a path towards a useful skill level using R. Author: Derek L. Sonderegger. - [An Introduction to Statistical Learning](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/http://faculty.marshall.usc.edu/gareth-james/ISL/ISLR%20Seventh%20Printing.pdf) - This book provides an introduction to statistical learning methods. Authors: Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. - [Advanced R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://adv-r.hadley.nz/introduction.html) - This book is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. [Exercise Solutions](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://advanced-r-solutions.rbind.io/) Author: Hadley Wickham. - [An Introduction to R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf) - This introduction to R is derived from an original set of notes describing the S and S-Plus environments written in 1990–2 by Bill Venables and David M. Smith when at the University of Adelaide. - [An Introduction to R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://intro2r.com/) - The aim of this book is to introduce you to using R, a powerful and flexible interactive environment for statistical computing and research. Authors: Alex Douglas, Deon Roos, Francesca Mancini, Ana Couto & David Lusseau - [Answering Questions with Data](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://crumplab.github.io/statistics/) - This is a free textbook teaching introductory statistics for undergraduates in Psychology. The textbook was written with math-phobia in mind and attempts to reduce the phobia associated with arithmetic computations. Author: Matthew J. C. Crump. - [Data Science in a Box](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://datasciencebox.org/index.html) - The core content of the course focuses on data acquisition and wrangling, exploratory data analysis, data visualization, inference, modelling, and effective communication of results. - [Data Science in Education Using R](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://datascienceineducation.com/) - This book is primarily about learning to use R as a tool for data science in education. Authors: Ryan A. Estrellado, Emily A. Bovee, Jesse Mostipak, Joshua M. Rosenberg, and Isabella C. Velasquez. - [Efficient R programming](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://csgillespie.github.io/efficientR/) - Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency. Authors: Colin Gillespie, Robin Lovelace. - [Engineering Production-Grade Shiny Apps](https://github.com/iamericfletcher/awesome-r-learning-resources/blob/master/https://engineering-shiny.org/) - This book covers the process of building a Shiny application that will later be sent to production. Authors: Colin Fay, Sebas ... ...

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