No Clocks

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 ...

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.

Apps aren't everything. Despite the plethora of to-do apps and note-taking apps available, pen and paper can still be a valuable productivity tool. In fact, paper note-taking and task management systems have been experiencing a revival in recent years, as we grapple with technology taking over our lives and...

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

It's time to get sh*t done this year. ? Check out Frank's roundup of the best productivity apps of 2021. Up your productivity game with Frank's top picks.

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.

Looking for inspiration? Or a methodology to work around? Try these ten best business productivity books ready for your journey in 2019. From Seth Godin to Emma Gannon and plenty more.

shinytest

‎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…

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

As a high-performing leader, we know you love using productivity products like the Full Focus Planner™. But any new system can seem overwhelming at first. Honestly, our planner can seem that way at first. With so many features built in, it’s hard to know where to start. You may wonder if you’re actually getting the […]

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.

In the pursuit of getting more things done, how do you build a productivity system that works for you? These 3 important elements will help you get started.

When used correctly, Google Calendar can be one of the best productivity tools. Learn how to effectively plan out your workday & stay on schedule.

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...

When you're working from home, even just on a pet project, staying on task and knowing when to do what can be a real challenge. We've put together some of the very best productivity apps that will help you keep focused and get it done.

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.

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

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,

(Update 4: 2016-08-19) I made many significant updates / improvements to this deployment method which are documented in a more recent blog p...

Note: This article is now several years old. If you have RStudio Connect, there are more modern ways of updating data in a Shiny app. Shiny applications are often backed by fluid, changing data. Data updates can occur at different time scales: from scheduled daily updates to live streaming data and ad-hoc user inputs. This article describes best practices for handling data updates in Shiny, and discusses deployment strategies for automating data updates.

Transferring your Excel sheet to a Shiny app is perhaps the easiest way to create an enterprise ready dashboard. Shiny offers a comparable feature set to Excel as well as exciting new possibilities.

RStudio's webinars offer helpful perspective and advice to data scientists, data science leaders, DevOps engineers and IT Admins. Presenters come from companies around the globe, as well as the RStudio staff.

Below we list the tools and innovations from the RStudio Conference in Austin, Texas that we found the most useful and exciting. As with last year’s conference, the event is well organized an…

James Blair, RStudio Scalability is a hot word these days, and for good reason. As data continues to grow in...