Inspired by R and our community
Analyze and explore
The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying philosophy and common APIs.
ggplot2 is an enhanced data visualization package for R. Create stunning multi-layered graphics with ease.
dplyr is the next iteration of plyr, focussing on only data frames. dplyr is faster and has a more consistent API.
tidyr makes it easy to “tidy” your data. Tidy data is data that’s easy to work with: it’s easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R’s hundreds of modelling packages).
purrr enhances R’s functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors.
A consistent, simple and easy-to-use set of wrappers around the fantastic 'stringi' package.
Communicate and interact
Shiny makes it incredibly easy to build interactive web applications with R. Shiny has automatic “reactive” binding between inputs and outputs and extensive pre-built widgets
Use Quarto to develop your code and ideas in a reproducible document. Knit plots, tables, and results together with narrative text, and create analyses ready to be shared.
Use flexdashboard to publish groups of related data visualizations as a dashboard.
Model and predict
The tidymodels framework is a collection of packages for modeling and machine learning using tidyverse principles.
Sparklyr provides bindings to Spark’s distributed machine learning library. Together with sparklyr’s dplyr interface, you can easily create and tune machine learning workflows on Spark, orchestrated entirely within R.
TensorFlow is an open-source software library for Machine Intelligence. The R interface to TensorFlow lets you work productively using the high-level Keras and Estimator APIs and the core TensorFlow API.