RStudio
45 packages on CRAN
3 packages on GitHub
Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports both 'Bootstrap' 3 and 4 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.
Key-value stores with automatic pruning. Caches can limit either their total size or the age of the oldest object (or both), automatically pruning objects to maintain the constraints.
Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/ml-engine>, which provides cloud tools for training machine learning models.
Provides building blocks for allowing HTML widgets to communicate with each other, with Shiny or without (i.e. static .html files). Currently supports linked brushing and filtering.
An R interface to the 'dygraphs' JavaScript charting library (a copy of which is included in the package). Provides rich facilities for charting time-series data in R, including highly configurable series- and axis-display and interactive features like zoom/pan and series/point highlighting.
Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.
An implementation of an interactive grammar of graphics, taking the best parts of 'ggplot2', combining them with the reactive framework of 'shiny' and drawing web graphics using 'vega'.
A framework for creating HTML widgets that render in various contexts including the R console, 'R Markdown' documents, and 'Shiny' web applications.
Obtain any major version of 'jQuery' (<https://code.jquery.com/>) and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown'). Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.
Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied. The functions are scheduled in an event loop.
Provides R bindings to the 'Sundown' Markdown rendering library (<https://github.com/vmg/sundown>). Markdown is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See <http://en.wikipedia.org/wiki/Markdown> for more information about Markdown.
Provides UI widget and layout functions for writing Shiny apps that work well on small screens.
R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
A tool for drawing sassy 'UML' diagrams based on a simple syntax, see <https://www.nomnoml.com>. Supports styling, R Markdown and exporting diagrams in the PNG format.
Pin remote resources into a local cache to work offline, improve speed and avoid recomputing; discover and share resources in local folders, 'GitHub', 'Kaggle' or 'RStudio Connect'. Resources can be anything from 'CSV', 'JSON', or image files to arbitrary R objects.
Provides tools to show and draw image pixels using 'HTML' widgets and 'Shiny' applications. It can be used to visualize the 'MNIST' dataset for handwritten digit recognition or to create new image recognition datasets.
Gives the ability to automatically generate and serve an HTTP API from R functions using the annotations in the R documentation around your functions.
Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are 'DBI' connections.
High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.
A collection of 'shiny' applications for the R package 'Luminescence'. These mainly, but not exclusively, include applications for plotting chronometric data from e.g. luminescence or radiocarbon dating. It further provides access to bootstraps tooltip and popover functionality and contains the 'jscolor.js' library with a custom 'shiny' output binding.
'R' 'Markdown' format for 'shower' presentations, see <https://github.com/shower/shower>.
A set of RStudio Addins to help interactively test and build regular expressions. Provides a Shiny gadget interface for interactively constructing the regular expression and viewing the results from common string-searching functions. The gadget interface includes a helpful regex syntax reference sheet and a library of common patterns.
Embeds the 'SQLite' database engine in R and provides an interface compliant with the 'DBI' package. The source for the 'SQLite' engine is included.
Access the RStudio API (if available) and provide informative error messages when it's not.
A suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.
An 'SCSS' compiler, powered by the 'LibSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the 'Sass CSS' extension language, which is stable, powerful, and CSS compatible.
Functions for working with the scrypt key derivation functions originally described by Colin Percival <https://www.tarsnap.com/scrypt/scrypt.pdf> and in Percival and Josefsson (2016) <doi:10.17487/RFC7914>. Scrypt is a password-based key derivation function created by Colin Percival. The algorithm was specifically designed to make it costly to perform large-scale custom hardware attacks by requiring large amounts of memory.
Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.
Create dashboards with 'Shiny'. This package provides a theme on top of 'Shiny', making it easy to create attractive dashboards.
Themes for use with Shiny. Includes several Bootstrap themes from <https://bootswatch.com/>, which are packaged for use with Shiny applications.
R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
A collection of 'HTML', 'JavaScript', and 'CSS' assets that dynamically generate beautiful documentation from a 'Swagger' compliant API: <https://swagger.io/specification/>.
Implements the 'TabNet' model by Sercan O. Arik et al (2019) <arXiv:1908.07442> and provides a consistent interface for fitting and creating predictions. It's also fully compatible with the 'tidymodels' ecosystem.
Interface to 'TensorFlow' <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more 'CPUs' or 'GPUs' in a desktop, server, or mobile device with a single 'API'. 'TensorFlow' was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Tools to deploy 'TensorFlow' <https://www.tensorflow.org/> models across multiple services. Currently, it provides a local server for testing 'cloudml' compatible services.
Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow' that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU'). 'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers, variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.
Create and manage unique directories for each 'TensorFlow' training run. Provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.
Theme 'ggplot2', 'lattice', and 'base' graphics based on a few choices, including foreground color, background color, accent color, and font family. Fonts that aren't available on the system, but are available via download on 'Google Fonts', can be automatically downloaded, cached, and registered for use with the 'showtext' and 'ragg' packages.
Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
Provides datasets in a format that can be easily consumed by torch 'dataloaders'. Handles data downloading from multiple sources, caching and pre-processing so users can focus only on their model implementations.
Provides access to datasets, models and preprocessing facilities for deep learning with images. Integrates seamlessly with the 'torch' package and it's 'API' borrows heavily from 'PyTorch' vision package.
Provides a 'WebSocket' client interface for R. 'WebSocket' is a protocol for low-overhead real-time communication: <https://en.wikipedia.org/wiki/WebSocket>.
Provides functions that make it easier to construct Shiny apps that can dynamically construct reproducible R scripts.