Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
resouRces
This content encompasses a comprehensive list of R-related educational materials, packages, tutorials, and datasets with projected dates ranging up to the year 2025. It includes various titles that focus on learning R programming, data analysis, data visualization, geospatial mapping, and statistical methods. Significant emphasis is placed on resources for learning R, such as introductions to R, books, courses, and video tutorials. Additionally, specific packages for data wrangling, statistical modeling, and visualization are mentioned, indicating the evolution and specialization of R's ecosystem to cater to diverse data science needs.
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shinymcp
shinymcp is a package that adapts Shiny applications for integration with AI chat interfaces such as Claude Desktop. It enables the creation of MCP Apps, which feature interactive UIs that run directly within chat conversations. To accomplish this, it restructures the traditional reactive programming model of Shiny into discrete tool functions that respond to user input changes. The package provides utilities for both manual and automatic conversion of existing Shiny applications. Developers can leverage familiar Shiny components, with the shinymcp bridge automatically detecting the connection between UI components and R code tools.
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The best R packages for data visualization
The best R packages for data visualization provide a comprehensive suite of tools for creating all types of charts and graphs. Core to R's visualization capabilities is the package ggplot2, which offers a versatile grammar of graphics. Extensions of ggplot2 and other packages expand these functionalities, allowing for interactive charts, improved aesthetics, specialized geospatial analysis, and managing complex data structures like networks. Packages like plotly, rmarkdown, patchwork, and hrbrthemes enhance the user experience and presentation. Additionally, there are packages dedicated to managing colors, creating tables, and supporting specific chart types like word clouds and streamgraphs.
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Time-aware isochrones for accessibility mapping with R and Mapbox tools
This article discusses creating time-aware isochrones to analyze accessibility at different times of the day using R and Mapbox tools. It demonstrates how to work with traffic data and visualize the impact of traffic using Mapbox's predicted traffic data. The tutorial includes step-by-step instructions and code snippets for generating isochrones for specific addresses at different times, and visualizing them interactively on a map with a comparison slider to highlight the accessibility differences at noon versus rush hour. The tools discussed are the R packages mapboxapi and mapgl.
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Use SAS, R, and quarto Together • sasquatch
sasquatch is an R package that enables the integration of SAS, R, and Quarto for creating reproducible multilingual reports. It utilizes SASPy and reticulate to run SAS code blocks within R, transfer data between SAS and R, perform SAS client file management, and render SAS output in quarto documents. The package includes installation instructions for development version, Python, and SASPy. It offers functionality such as interactive execution of SAS code, data conversion between R and SAS, and rendering quarto documents with SAS output, distinguishing it from similar packages like sasr, configSAS, and SASmarkdown.
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