R is a free programming language and software environment for statistical computing and graphics. R has a wide variety of statistical linear and non-linear modeling and provides numerous graphical techniques.
Make HTTP requests and process their responses. A modern reimagining of httr.
R tools for healthcare machine learning
Tools for cleaning and normalizing text data
R client for the Elasticsearch HTTP API
Bindings to Tesseract OCR engine for R
✂️ Easy half-half geoms in ggplot2
A meta-analysis package for R
A fully Dockerized, self-hosted development environment for teams. Develop where you serve.
🗯️ Easily create pretty popup messages (modals) in Shiny
R interface to use GPU's
R package for automation of machine learning, forecasting, model evaluation, and model interpretation
:chart_with_upwards_trend: Estimate effects, contrasts and means based on statistical models
Landscape Metrics for Categorical Map Patterns 🗺️ in R
R tools for Eurostat data
Materials for GWU DNSC 6279 and DNSC 6290.
Some useful R-Ladies files :purple_heart: :earth_africa:
Provides easier interaction with Socrata open data portals http://dev.socrata.com. Users can provide a 'Socrata' data set resource URL, or a 'Socrata'...
Analytics & Machine Learning R Sidekick
Interface between R and the OpenStreetMap-based routing service OSRM
R Package for accessing and plotting Google Maps
Execute and Control Subprocesses from R
ADaM in R Asset Library
An R package to hold and facilitate interaction with natural earth map data :earth_africa:
Compare R Objects with a Diff
Supplementary material for Hands-On Machine Learning with R, an applied book covering the fundamentals of machine learning with R.
openxlsx - a fast way to read and write complex xslx files
Reporting tables with R
Analyzing and visualizing KEGG information using the grammar of graphics
Talk on code smells and feels and how to change that via refactoring
Facilitate citation of R packages
Quizzes & Assignment Solutions for Google Data Analytics Professional Certificate on Coursera. Also included a few resources on side that I found help...
Navigate to variable's definition with a click in JupyterLab (or with a few key strokes)
Fresh shiny themes
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
Thematic cartography with R
Minimalistic GitHub API client in R
Tidyverse design principles
R package to infer biological activities from omics data using a collection of methods.
Spatial data in R: using R as a GIS
An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
An Import Mechanism For R
Discrete-Event Simulation for R
🎨 A colour picker tool for Shiny and for selecting colours in plots (in R)
Extensible time series class that provides uniform handling of many R time series classes by extending zoo.
Bindings to libxml2
Sassy 'UML' Diagrams for R
R package for collaborative writing and editing of R Markdown (or Sweave) documents in Google Docs.
Download ⬇️ Qualtrics survey data directly into R!
R package to create "Table 1", description of baseline characteristics with or without propensity score weighting
Collection of stats, modeling, and data science tools in Python and R.