R

Making the web more beautiful, fast, and open through great typography

R Shiny app for iAtlas (new, 2020 version). Contribute to CRI-iAtlas/iatlas-app development by creating an account on GitHub.

Data Scientist. Shiny Developer. Tidyverse Denizen. Scheme Enthusiast.

Docking or containerization is a new method of distribute a software/tool. Beside providing only the source code for installing, we give the users the so-called container, which contains the whole environment to run the program, including the tool and its dependencies with the exact version and all the needed configurations. By delivering such a “container”, users are always able to “reuse” the tool and reproduce the results as we did.

Write an awesome description for your new site here. You can edit this line in _config.yml. It will appear in your document head meta (for Google search results) and in your feed.xml site description.

The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.

Easily Extracting Information About Your Data. Contribute to cosimameyer/overviewR development by creating an account on GitHub.

Makes it easy to display descriptive information on a data set. Getting an easy overview of a data set by displaying and visualizing sample information in different tables (e.g., time and scope conditions). The package also provides publishable LaTeX code to present the sample information.

Blog of the MZES Social Science Data Lab

This post provides a guide to effectively and securely scale your ShinyProxy deployment of shiny apps in production with Docker Swarm and Traefik

A workflow for refactoring one-time analyses to sustainable data products

A walkthrough of using the projmgr package for GitHub-based project management via R

Don't believe the documentation! Shiny modules aren't just for advanced users; they might just be a great entry point for development

Using controlled dictionaries for low-touch documentation, validation, and usability of tabular data

Using controlled vocabularies to encode contracts between data producers and consumers

Using the tidyverse's expressive data wrangling vocabulary as a preprocessor for elegant SQL scripts

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rocker/rbase docker image with a selection of packages preinstalled geared to support R-Shiny based webapp. - slink42/rbase_shiny

rocker/rbase docker image with a selection of packages preinstalled geared to support R-Shiny based webapp. - Artificially-Intelligent/shiny

This blogpost explains step by step how you can build your own Docker Image and include R scripts. With this you can have scripts running at every image's beginning.

Learn how to dockerize ShinyApps! Join our colleague Oliver on his journey toward deploying his work done in R with the help of neat Docker containers.

Help yourself to these free books, tutorials, packages, cheat sheets, and many more materials for R programming. There’s a separate overview for handy R programming tricks. If you have additi…

CRAN Task View: Empirical Finance. Contribute to eddelbuettel/ctv-finance development by creating an account on GitHub.