Open source

Open-source R packages for everyday analysis

Free on CRAN, with the code on GitHub. Each package has its own documentation site with examples.

Browse all packages rsquaredacademy on GitHub

R packages

Regression and modelling

olsrr

Tools for building linear regression models.

Diagnostics, variable selection and influence measures for a fitted lm model.

What's inside

Comprehensive Regression Output
Variable Selection Procedures
Heteroskedasticity Tests
Collinearity Diagnostics
Model Fit Assessment
Measures of Influence
Residual Diagnostics

Docs CRAN GitHub

blorr

Tools for building binary logistic regression models.

Model fit, validation and collinearity for a fitted glm with a binary outcome.

What's inside

Bivariate Analysis
Model Fit Statistics
Model Validation
Variable Selection
Residual Diagnostics
Collinearity Diagnostics
Visualization

Docs CRAN GitHub

Statistics

descriptr

Tools for generating descriptive and summary statistics.

A quick way to screen a data frame before you model it.

What's inside

Data Screening
Summary Statistics
Frequency Tables
Cross Tables
Data Visualization

Docs CRAN GitHub

inferr

Tools for inferential statistics.

Hypothesis tests with plain R syntax, with no formulas to memorise.

What's inside

Binomial Test
Test of Proportion
t Test
Chi Square Test
Levene’s Test
Test of Variance
McNemar Test
Cochran Q Test
Runs Test

Docs CRAN GitHub

vistributions

Tools for visualizing probability distributions.

Plot the binomial, chi square, normal, F and t distributions.

What's inside

Binomial Distribution
Chi Square Distribution
Normal Distribution
F Distribution
t Distribution
Includes a Shiny app

Docs CRAN GitHub

rbin

Tools for binning data.

Turn continuous variables into factors, and create dummy variables from them.

What's inside

Manual Binning
Quantile Binning
Winsorized Binning
Equal Length Binning
Equal Width Binning
Factor Binning
Generate Dummy Variables
Includes RStudio add-ins

Docs CRAN GitHub

Analytics

rfm

Tools for RFM analysis.

Score and segment customers from transaction-level data.

What's inside

Generate RFM Scores
Handles Transaction or Customer Level Data
Visualization Tools
Segment Customers
Includes a Shiny app

Docs CRAN GitHub

xplorerr

Tools for interactive data analysis.

Descriptive, inferential and visual analysis behind a Shiny interface.

What's inside

Descriptive Statistics
Inferential Statistics
Visualize Probability Distributions
Data Visualization
RFM Analysis
Linear Regression
Logistic Regression

Docs CRAN GitHub

Utilities

yahoofinancer

Fetch data from the Yahoo Finance API.

Historical and near real-time data on stocks, indices and currencies.

What's inside

Historical Prices
Real-time Quotes
Financial Statements
Valuation Metrics
Currency Conversion
Market Indices
Market Summary
Trending Tickers
Multi-ticker Queries

Docs CRAN GitHub

standby

Alerts, notifications and loading screens in Shiny.

Add alerts, notifications, modals, info tips and loading screens to Shiny apps.

What's inside

Loading Screens for Shiny Outputs
Spinners and Loaders
Alerts and Modals
Notifications and Toasts
Tooltips
Preview Alerts and Spinners

Docs CRAN GitHub

Shiny apps

Point-and-click apps for exploring data, built on our packages. They come with xplorerr and run on your own computer.

App	Run it
Descriptive statistics	`xplorerr::app_descriptive()`
Probability distributions	`xplorerr::app_vistributions()`
Hypothesis testing	`xplorerr::app_inference()`
Linear regression	`xplorerr::app_linear_regression()`
Logistic regression	`xplorerr::app_logistic_regression()`
RFM analysis	`xplorerr::app_rfm_analysis()`
Data visualizer	`xplorerr::app_visualizer()`

Try one in R

> install.packages("xplorerr")
> xplorerr::app_linear_regression()

xplorerr documentation

Open learning material

Our eBooks and open course material are on GitHub too.

Open coursesFree course material for learning R, to read at your own pace.Read the open courses Open courses sourceThe source of the open course material.See it on GitHub eBook sourcesThe source of every eBook, from Introduction to R to R, Databases & SQL.See them on GitHub

Found a bug or have an idea?

Open an issue on the package's GitHub repository. Pull requests are welcome.

Go to GitHub