R on the Web - List of Links¶
Useful links for people interested in R.
Online books¶
First, many websites are listed and hosted on https://bookdown.org/home/archive/.
One book rules them all! The big book of R lists many many books written in and for R!
– Data Science –
R for data science: THE reference. Must read, must have.
Introduction to Data Science: a huge book on many many topics in Data Science, by Rafael Irizarry, from Harvard.
Another Introduction to Data Science: a great alternative to the preceding monograph. Maybe slightly more accessible.
Data Science in Education Using R: Another great book, very didactic with lots of examples.
Modern R with the tidyverse: Great resource for beginners, really starts from scratch.
– Shiny –
Mastering Shiny: Hadley Wickham’s secrets on how to build Shiny apps.
The Shiny AWS book: a great tutorial that covers many topics beyond Shiny and AWS (ex: Docker & Git)
Outstanding User Interfaces with Shiny: An advanced book on Shiny’s html/JavaScript capabilities - and how to customize the layout of Shiny apps.
– Visualization –
Fundamentals of Data Visualization: An exhaustive book on visualization tools & tips.
R graphics cookbook: the way to go if you’re starting on ggplot().
– Machine Learning –
Hands on Machine Learning with R: a great (the?) reference for ML in R.
An Introduction to Machine Learning with R: introductory material on ML in R.
– Statistics –
Foundations in statistics: an incredibly didactic book on various topics in statistics: warmly recommended!
Statistical Inference via Data Science: a book on regressions & hypothesis testing.
Introduction to Econometrics with R: a great monograph on econometrics with lots of examples.
– Finance –
Machine learning for factor investing: a book on quantitative finance with lots of R code + a financial dataset.
Financial Engineering Analytics: a general purpose book on R & finance.
Technical Analysis with R: a book on technical analysis in finance.
Tidy Portfolio Management in R: Portfolio management with some packages in R (xts, PortfolioAnalytics, etc.).
– Misc. –
Rcpp for everyone: A book dedicated to the integration of C++ in R. Very useful to accelerate simple routines.
Advanced R: for well seasoned users.
Text mining with R: one reference book on the subject.
Twitter for R programmers: very useful for people who want to scrap data from Twitter.
Twitter for scientists: a book for people who want to get better at using Twitter - not R specific.
Curated lists of resources / packages¶
Machine Learning: by Joseph Misiti
List of cool packages I: by awesome R
List of cool packages II: by Garrett Grolemund (RStudio)
Learning / Pedagogy¶
Bradley Boehmke’s courses: Beginner, Intermediate and Expert: great material for all levels!
Josehp Larmarange’s wiki: Great overview of R (in French).
Julien Barnier’s intro: Great intro to R and the tidyverse (in French).
Florian Privé’s book/wiki: Good intro to R/RStudio (in French).
tidyverse snapshot: Impressive deck by Hadley Wickham.
More on tidy data: dplyr & tidyr by Julie Lowndes.
Data Science in a Box!: very large scope course on data science with lots of material.
Data Science repo: an aggregation of Data Science resources.
Interactive web-based data visualization with R, plotly, and shiny: exhaustive book on (online) visualization techniques.
Yan Holt’s intoduction to R tools: much focused on visualization.
Krista DeStasio’s best practices: tips on project & code organisation.
Kelly Bodwin’s course on statistics with R: more data science than pure stats in my opinion…
Machine learning¶
Keras for R: arguably the best solution for neural networks. Homepage here
The xgboost package: one of the best for boosted trees (with lightgbm).
The caret package: probably the most complete ML package. Book here
Erin LeDell’s large scale tutorial: an efficient overview of the main algorithms with lots of code chunks.
Christoph Molnar’s online book: a great resource for interpretability of ML models.
Tidymodels: a meta package dedicated to: preparing data, assessing models, exporting results, etc. Reference here
Visualisation¶
BBC cookbook for ggplot: recipes to create graphs like those of the BBC data crew!
Animated plots with gganimate: ggplot, only, in motion! Home repo here.
Generative art¶
Generative Art with R (1): amazing geometric plots.
Generative Art with R (2): amazing plots: the power of ggplot!
Mandalas in R: geometry & color combined.
Drawing fractals: fronkostin again!
Fractal flowers: ggplot + colourlovers!
Clifford attractors: large scale simulations!
Tridokus: Coloring sudokus.
aRt project: William Chase’s monthly productions.
Text mining¶
Basic text mining in R: a smooth introduction.
Scrapping & text mining tripadvisor: sentiment analysis.
Sentiment from news: nice flexible shiny app for sentiment in user-uploaded text.
Finance¶
Reproducible finance: amazing resources for portfolio management.
Portfolio volatility shiny app: tailor made vol plots.
The derivmkts pacakge: option pricing with R.
Miscellaneous¶
R Weekly: frequent updates in the R community.
Send tweets from R: one application of the Twitter API.
Most Starred R Packages on GitHub: Packages by popularity.
reticulate: combining Python & R.
Appendix: Links¶
Backlinks:
list from [[R on the Web - List of Links]] AND -"Changelog"