The inspiration for this came from awesome-ggplot2 and awesome-R, both of which are curated lists of r packages and tools. However, these lists can be very long, of broad scope and often intimidating to new users. This is why I've listed the following open source r learning resources that I've found useful and think do a reasonable job of introducing an r novice to the functionalities of the software.
| Name | Notes |
|---|---|
| R for Data Science | Basic operations, data wrangling, model building and graphing |
| Databases using R | Work with databases in R |
| Bayesian Data Analysis | Basics of Bayesian statistics and demos in R |
| R Cookbook | Comprehensive R review covering most basic operations, general stats, graphics, time series analysis and markdown |
| Data science for economists | Another comprehensive R review covering version control, web scrapping, spatial analysis, and other tools like Docker, Google Compute Engine, SQL and Spark |
| Applied Causal Analysis (with R) | Introduces concepts such as ATT, ATE, SUTVA and tools for causal analysis (DiD, matching, RDD) |
| Statistical Rethinking 2 with Stan and R | Replicates models in Richard McElreath's Statistical Rethinking (2nd ed.) book using Stan, R, rstan, tidybayes, and ggplot2 |
| Finmetrics | Quantitative analysis of financial data |
| Computational Economics | Introduction to computational approaches for solving economic models |
| Tidy Portfoliomanagement in R | Quantitative analysis of financial data and portfolio management |
| Econometrics II | Advanced undergrad econometrics with focus on empirical research covering topics such as causal inference, panel, nonlinear methods and time series |
| Data Science: Theories, Models, Algorithms, and Analytics | Machine learning in R covering mathematical and statistical operations, text analytics, networks, discriminant analysis, clustering, neural networks, finance models |
| Happy Git and GitHub for the useR | Working with Git, GitHub in the shell and RStudio |
| STAT 545 | Intro to data wrangling and visualization, also deals with making packages, web scrapping and Shiny |
| Geocomputation with R | Geographic data analysis, visualization and modeling |
| R Markdown: The Definitive Guide | Comprehensive guide to R Markdown (document format) |
| Mastering Spark with R | Apache Spark with R in large scale data science |
| Forecasting: Principles and Practice | Concepts of and introduction to forecasting methods |
| Advanced R | Advanced concepts in R useful for understanding why R works the way it does |
| Text Mining with R | Analyzing text-heavy and unstructured data |
| Fundamentals of Data Visualization | Data visualization |
| Computing for the Social Sciences | Covers a wide range of topics including text analysis, Shiny, Markdown, webscrapping, geospatial visualization, exploratory data analysis and Spark |
| Interactive web-based data visualization with R, plotly, and shiny | Teaches practical skills for creating interactive and dynamic web graphics for data analysis from R |
| Congressional Data in R | Overview of Congessional datasets and R packages for joining/merging, cleaning, visualization, and modeling |
| Name | Notes |
|---|---|
| Project-oriented workflow | What's wrong with setwd() and rm(list = ls()) |
| Best practice to handle out-of-memory data | Techniques, workflows, and best practices to handle out-of-memory data in R |
| Name | Notes |
|---|---|
| swirl Other swirl courses | Repository for introductiory econometrics course |
| Awesome Exploratory Data Analysis (EDA) | R and python packages for exploratory data analysis |
| Reactable | Interactive data tables in R |
| tidycensus | R interface to the decennial US Census, American Community Survey APIs and the US Census Bureau's geographic boundary files |
| disk.frame | Helps with dealing with large out-of-memory data |
| dbplyr | Database backend for dplyr that allows you to perform operations in remote database tables |
| MonetDBLite | SQL database backend with dplyr commands (not available in CRAN so requires compilers) |
| sergeant | Apache Drill backend with dplyr |
| Name | Notes |
|---|---|
| Derivatives research | Resources and research to expand derivatives knowledge |
| Open courses | Courses on machine learning, deep learning and artificial intelligence |