- R Shiny Br
- Shiny Rendertext
- Shiny Cheat Sheets
- Rstudio Shiny Cheat Sheet
Jul 22, 2014 - This Pin was discovered by Oren Bochman. Discover (and save!) your own Pins on Pinterest. Www.DataStrategyWithJonathan.comIn this series, we'll be learning the most effective way to build interactive R Shiny web dashboards with R Studio and Flexda.
2014-10-02Yihui Xie
Shiny v0.10.2 has been released to CRAN. To install it:install.packages('shiny') This version of Shiny requires R 3.0.0 or higher (note the current version of R is 3.1.1). R 2.15.x is no longer supported.Here are the most prominent changes: File uploading via fileInput() now works for Internet Explorer 8 and 9. Note, however, that IE 8⁄9 do not support multiple files from a single file input. If you need to upload multiple files, you must use one file input for each file. Read more →
Some of the most innovative Shiny apps share data across user sessions. Some apps share the results of one session to use in future sessions, others track user characteristics over time and make them available as part of the app.This level of sophistication creates tricky design choices when you host your app on a server. A nimble server will open new instances of your app to speed up performance, or relaunch your app on a bigger server when it becomes popular. Read more →
Want to see who is using your Shiny apps and what they are doing while they are there?Google Analytics is a popular way to track traffic to your website. With Google Analytics, you can see what sort of person comes to your website, where they arrive from, and what they do while they are there.Since Shiny apps are web pages, you can also use Google Analytics to keep an eye on who visits your app and how they use it. Read more →
2014-08-01Yihui Xie
Shiny v0.10.1 has been released to CRAN. You can either install it from a CRAN mirror, or update it if you have installed a previous version.install.packages('shiny', repos = 'http://cran.rstudio.com') # or update your installed packages # update.packages(ask = FALSE, repos = 'http://cran.rstudio.com') The most prominent change in this patch release is that we added full Unicode support on Windows. Shiny apps running on Windows must use the UTF-8 encoding for ui. Read more →
RStudio is very pleased to announce the general availability of Shiny Server Pro 1.2.Download a free 45 day evaluation of Shiny Server Pro 1.2Shiny Server Pro 1.2 adds support for R Markdown Interactive Documents in addition to Shiny applications. Learn more about Interactive Documents by registering for the Reproducible Reporting webinar August 13 and Interactive Reporting webinar September 3.We are excited about the new ways in which you can now share your data analysis in Shiny Server Pro along with the security, management and performance tuning capabilities you and your IT teams need to scale. Read more →
2014-07-21Garrett Grolemund
We’ve added a new section of articles to the Shiny Development Center. These articles explain how to create interactive documents with Shiny and R Markdown.You’ll learn how to Use R Markdown to create reproducible, dynamic reports. R Markdown offers one of the most efficient workflows for writing up your R results. Create interactive documents and slideshows by embedding Shiny elements into an R Markdown report. The Shiny + R Markdown combo does more than just enhance your reports; R Markdown provides one of the quickest ways to make light weight Shiny apps. Read more →
The RStudio team recently rolled out new capabilities in RStudio, shiny, ggvis, dplyr, knitr, R Markdown, and packrat. The “Essential Tools for Data Science with R” free webinar series is the perfect place to learn more about the power of these R packages from the authors themselves.Click to learn more and register for one or more webinar sessions. You must register for each separately. If you miss a live webinar or want to review them, recorded versions will be available to registrants within 30 days. Read more →
2014-07-08Garrett Grolemund
RStudio will teach the new essentials for doing data science in R at this year’s Strata NYC conference, Oct 15 2014.R Day at Strata is a full day of tutorials that will cover some of the most useful topics in R. You’ll learn how to manipulate and visualize data with R, as well as how to write reproducible, interactive reports that foster collaboration. Topics include:9:00am – 10:30am A Grammar of Data Manipulation with dplyr Speaker: Hadley Wickham Read more →
2014-06-30Garrett Grolemund
Shiny v0.10 comes with a quick, handy guide. Use the Shiny cheat sheet as a quick reference for building Shiny apps. The cheat sheet will guide you from structuring your app, to writing a reactive foundation with server.R, to laying out and deploying your app.You can find the Shiny cheat sheet along with many more resources for using Shiny at the Shiny Dev Center, shiny.rstudio.com.(p.s. Visit the RStudio booth at useR! Read more →
Our first public release of ggvis, version 0.3, is now available on CRAN. What is ggvis? It’s a new package for data visualization. Like ggplot2, it is built on concepts from the grammar of graphics, but it also adds interactivity, a new data pipeline, and it renders in a web browser. Our goal is to make an interface that’s flexible, so that you can compose new kinds of visualizations, yet simple, so that it’s accessible to all R users. Read more →
Search
News & Events
Upcoming webinars ↪
Categories
- Company News & Events (7)
- Data Science Leadership (41)
- Data visualization (1)
- Education (6)
- Events (9)
- Featured (41)
- Internships (3)
- News (116)
- Packages (175)
- R Markdown (26)
- RStudio (1)
- RStudio Cloud (3)
- RStudio Connect (38)
- RStudio IDE (82)
- RStudio Launcher Plugin SDK (1)
- RStudio Package Manager (12)
- RStudio Server Pro (1)
- Shiny (75)
- Training (49)
- packages (1)
- r-markdown (1)
- rstudio::conf (23)
- rstudio::global (2)
- shinyapps.io (10)
- tidyverse (35)
About RStudio
In a previous post, I described how I was captivated by the virtual landscape imagined by the RStudio education team while looking for resources on the RStudio website. In this post, I’ll take a look atCheatsheets another amazing resource hiding in plain sight.
R Shiny Br
Apparently, some time ago when I wasn’t paying much attention, cheat sheets evolved from the home made study notes of students with highly refined visual cognitive skills, but a relatively poor grasp of algebra or history or whatever to an essential software learning tool. I don’t know how this happened in general, but master cheat sheet artist Garrett Grolemund has passed along some of the lore of the cheat sheet at RStudio. Garrett writes:
One day I put two and two together and realized that our Winston Chang, who I had known for a couple of years, was the same “W Chang” that made the LaTex cheatsheet that I’d used throughout grad school. It inspired me to do something similarly useful, so I tried my hand at making a cheatsheet for Winston and Joe’s Shiny package. The Shiny cheatsheet ended up being the first of many. A funny thing about the first cheatsheet is that I was working next to Hadley at a co-working space when I made it. In the time it took me to put together the cheatsheet, he wrote the entire first version of the tidyr package from scratch.
It is now hard to imagine getting by without cheat sheets. It seems as if they are becoming expected adjunct to the documentation. But, as Garret explains in the README for the cheat sheets GitHub repository, they are not documentation!
RStudio cheat sheets are not meant to be text or documentation! They are scannable visual aids that use layout and visual mnemonics to help people zoom to the functions they need. … Cheat sheets fall squarely on the human-facing side of software design.
Shiny Rendertext
Cheat sheets live in the space where human factors engineering gets a boost from artistic design. If R packages were airplanes then pilots would want cheat sheets to help them master the controls.
Shiny Cheat Sheets
The RStudio site contains sixteen RStudio produced cheat sheets and nearly forty contributed efforts, some of which are displayed in the graphic above. The Data Transformation cheat sheet is a classic example of a straightforward mnemonic tool.It is likely that even someone who just beginning to work with dplyr will immediately grok that it organizes functions that manipulate tidy data. The cognitive load then is to remember how functions are grouped by task. The cheat sheet offers a canonical set of classes: “manipulate cases”, “manipulate variables” etc. to facilitate the process. Users that work with dplyr on a regular basis will probably just need to glance at the cheat sheet after a relatively short time.
The Shiny cheat sheet is little more ambitious. It works on multiple levels and goes beyond categories to also suggest process and workflow.
The Apply functions cheat sheet takes on an even more difficult task. For most of us, internally visualizing multi-level data structures is difficult enough, imaging how data elements flow under transformations is a serious cognitive load. I for one, really appreciate the help.
Cheat sheets are immensely popular. And even in this ebook age where nearly everything you can look at is online, and conference attending digital natives travel light, the cheat sheets as artifacts retain considerable appeal. Not only are they useful tools and geek art (Take a look at cartography) for decorating a workplace, my guess is that they are perceived as runes of power enabling the cognoscenti to grasp essential knowledge and project it in the world.
Rstudio Shiny Cheat Sheet
When in-person conferences resume again, I fully expect the heavy paper copies to disappear soon after we put them out at the RStudio booth.