Front Matter · The Practice of Reproducible Research
Business Analytics with R - DRAFT
Business Analytics with R
Edit a table with Shiny and rhandsontable
Saturn Elephant - Useful callbacks for DT (in Shiny)
jienagu/DT-Editor: This is a DT Editor Shiny app
This is a DT Editor Shiny app. Contribute to jienagu/DT-Editor development by creating an account on GitHub.
Double-click to edit table cells
OneTab shared tabs
OneTab shared tabs
OneTab shared tabs
Github V2
GitHub
R
Productivity Misc V2
Productivity Misc
Code distribution • shinymeta
Productivityist
Highcharts JS API Reference
Interactive charts for your web pages.
Actuarial Data Science - Home
An initiative of the Swiss Association of Actuaries
Chapter 18 Test drive R Markdown | Happy Git and GitHub for the useR
Using Git and GitHub with R, Rstudio, and R Markdown
R Code Chunks
Turn your analyses into high quality documents, reports, presentations and dashboards with R Markdown. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output. Use multiple languages including R, Python, and SQL. R Markdown supports a reproducible workflow for dozens of static and dynamic output formats including HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles, websites, and more.
17.1 Template structure | R Markdown: The Definitive Guide
The first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.
NCEAS/recordr: Provenance tracking for R.
Provenance tracking for R. Contribute to NCEAS/recordr development by creating an account on GitHub.
Run Predictions Inside the Database • tidypredict
It parses a fitted R model object, and returns a formula in Tidy Eval code that calculates the predictions. It works with several databases back-ends because it leverages dplyr and dbplyr for the final SQL translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), earth(), xgb.Booster.complete(), cubist(), and ctree() models.
Explore and Visualize Your Data Interactively • esquisse
A shiny gadget to create ggplot2 charts interactively with drag-and-drop to map your variables. You can quickly visualize your data accordingly to their type, export to PNG or PowerPoint, and retrieve the code to reproduce the chart.
Super Solutions for Shiny Architecture 3/5: Softcoding Constants in the App - Appsilon Data Science | End to End Data Science Solutions
Two methods for keeping your Shiny app organized while avoiding hardcoding. Also, a tip for adding multiple languages (internationalization) for your app.
Introduction to renv • renv
renv
ls - how to make function in R to remove all objects from global environment except defaults and objects passed as arguments - Stack Overflow
I'm new to R (and programming in general), so I've been making various functions to warm myself up to it. I've been trying to figure out how to make an R function that will clear my global environ...
pridiltal/staplr: PDF Toolkit.
PDF Toolkit. :paperclip: :hammer: :wrench: :scissors: :bookmark_tabs: :file_folder::paperclip: :bookmark: :construction: :construction_worker: - pridiltal/staplr
WinVector/wrapr: Wrap R Functions for Debugging and Ease of Use
Wrap R for Sweet R Code. Contribute to WinVector/wrapr development by creating an account on GitHub.
krlmlr/fledge: Wings for your R packages: Streamline the process of versioning R packages and updating NEWS
Wings for your R packages: Streamline the process of versioning R packages and updating NEWS - krlmlr/fledge