Live theme switcher for R Shinydashboard applications - nik01010/dashboardThemeSwitcher

This R Shiny Tutorial will provide you with a detailed and comprehensive knowledge of R Shiny and how to create interactive Web Applications.

shiny.info is an open source package for R Shiny that allows developers to display diagnostic information in a div located in the corner of a Shiny app.

Getting started with web development can be strenuous and confusing. There’s so much to learn and you have so many different options for languages,

In this list, I’m going to go over 19 different tools that will help designers and developers stay organized. I tried hard to make sure to gather

Recommended Packages Many useful R function come in packages, free libraries of code written by R's active user community. To install an R package, open an R session and type at the command line in...

Add & Validate forms in your Shiny App! Contribute to piotrbajger/shinyreforms development by creating an account on GitHub.

Shiny app for building charts with a point-and-click interface - sicarul/shiny-chart-builder

HTTPS to Secure Your RStudio + Shiny App Work Environment Click any link in list below to jump to topic Creating a Friendly URL Route 53 to Host Domain and Create Subdomains AWS Certificate Manager for SSL keys AWS Elastic Load Balancers: HTTPS Redirection Installing Nginx & Creating Configuration Files I wanted to create this post as an addition to my previous post Running R on AWS EC2 and Logging into RStudio from Anywhere to show how to secure your AWS environment.

Creating a Shiny application to scrape data from IMDB's top movies.

Now I am become death, destroyer of groups.... Contribute to MilesMcBain/wisegroup development by creating an account on GitHub.

Data science is characterized among other things using open source tools. An advantage when working with open source languages such as R or Python is the large package world. This provides tools for numerous use cases and problems through the development within huge communities. The packages are organized in digital ...

R is a free software environment for statistical computing and graphics, available from The R Project for Statistical Computing. At Indiana University, R is ...

This is a guide on how to conduct Meta-Analyses in R.

To help you land your ideal data science job, we've come up with Python interview questions you should be prepared to answer.

A curated list of awesome ETL frameworks, libraries, and software. - pawl/awesome-etl

Shiny 1.0.4 is now available on CRAN. To install it, run: install.packages("shiny") For most Shiny users, the most exciting news is that file inputs now support dragging and dropping: It is now possible to add and remove tabs from a tabPanel, with the new functions insertTab(), appendTab(), prependTab(), and removeTab(). It is also possible to hide and show tabs with hideTab() and showTab(). Shiny also has a new a function, onStop(), which registers a callback function that will execute when the application exits.

shinytest

Learn how to use Chrome DevTools to find and fix JavaScript bugs.

‎Write R code directly on your iPhone, iPad and iPod Touch! This app is ideal for learning and testing code snippets! R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used am…

Introduction Data visualization is an important aspect of the data science work flow. This app enables the analyst to understand the data in question. In this post, we will build an application whi…

Today we are excited to announce the pins package is available on CRAN! pins allows you to pin, discover and share remote resources, locally or in remote storage. If you find yourself using download.file() or asking others to download files before running your R code, use pin() to achieve fast, simple and reliable reproducible research over remote resources. Pins You can use the pins package to: Pin remote resources locally to work offline and cache results with ease, pin() stores resources in boards which you can then retrieve with pin_get().

Describes the best practices for setting automated test architecture for R Shiny apps. Automate and test early and often with unit tests, user interface tests, and performance tests.

Producing an API that serves model results or a Shiny app that displays the results of an analysis requires a collection of intermediate datasets and model objects, all of which need to be saved. Depending on the project, they might need to be reused in another project later, shared with a colleague, used to shortcut computationally intensive steps, or safely stored for QA and auditing. Some of these should be saved in a data warehouse, data lake, or database, but write access to an appropriate database isn’t always available.

"How do you get so much done?" This is a question I receive several times a week. And up until today...

config package for R. Contribute to rstudio/config development by creating an account on GitHub.

Three methods for using javascript code in Shiny applications to build faster apps, avoid unnecessary re-rendering, and add components beyond Shiny's limits. Part 2 of a 5 part series on super solutions for Shiny architecture.

Learn Both SQL Server & PostgreSQL By Doing. Enhance Your Data Analytics Career With Real World Data Science Exercises

hello, How can I clean the R environment both using RStudio and the R console? Thanks,

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