Running Python inside the RStudio Server IDE

A great many R users will have to run some python code from time to time, and this short video from our Head of Data Engineering, Mark Sellors outlines one approach you can take that doesn’t mean leaving the RStudio IDE. Related To leave a comment for the author, please follow the link and comment on their blog: Mango Solutions. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more… If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook…
Original Post: Running Python inside the RStudio Server IDE

Effectively scaling Shiny in enterprise

James Blair, RStudio Scalability is a hot word these days, and for good reason. As data continues to grow in volume and importance, the ability to reliably access and reason about that data increases in importance. Enterprises expect data analysis and reporting solutions that are robust and allow several hundred, even thousands, of concurrent users while offering up-to-date security options. Shiny is a highly flexible and widely used framework for creating web applications using R. It enables data scientists and analysts to create dynamic content that provides straightforward access to their work for those with no working knowledge of R. While Shiny has been around for quite some time, recent introductions to the Shiny ecosystem make Shiny simpler and safer to deploy in an enterprise environment where security and scalability are paramount. These new tools in connection with RStudio Connect…
Original Post: Effectively scaling Shiny in enterprise

Another Prediction for the FIFA World Cup 2018

Ava Yang, Data Scientist Given that the UEFA Champion League final a few weeks ago between Real Madrid and Liverpool is the only match I’ve watched properly in over ten years, how dare I presume I can guess that Brazil is going to lift the trophy in the 2018 FIFA World Cup? Well, here goes… By the way, if you find the below dry to read, it is because of my limited natural language on the subject matter…data science tricks to the rescue! This blogpost is largely based on the prediction framework from an eRum 2018 talk by Claus Thorn Ekstrøm. For first hand materials please take a look at the slides, video and code. The idea is that in each simulation run of a tournament, we find team winner, runners-up, third and fourth etc. N times of simulation runs…
Original Post: Another Prediction for the FIFA World Cup 2018

Top Tip: Don’t keep your data prep in the same project as your Shiny app

Mark Sellors, Head of Data Engineering If you use RStudio Connect to publish your Shiny app (and even if you don’t) take care with how your arrange your projects. If you have a single project that includes both your data prep and your Shiny app, packrat (which RSConnect uses to resolve package dependencies for your project) will assume the packages you used for both parts are required on the RSConnect server and will try to install them all. This means that if your Shiny app uses three packages and your data prep uses six, packrat and RSconnect will attempt to install all nine on the server. This can be time consuming as packages are often built from source in Connect-based environments, so this will increase the deployment time considerably. Furthermore, some packages may require your server admin to resolve system-level…
Original Post: Top Tip: Don’t keep your data prep in the same project as your Shiny app

Why Bother with Shiny?

Aimée Gott, Education Practice Lead For the last week we’ve been talking on the blog and Twitter about some of the functionality in Shiny and how you can learn it. But, if you haven’t already made the leap and started using Shiny, why should you? What is the challenge to be solved? At Mango we define data science as the proactive use of data and advanced analytics to drive better decision making. We all know about the power of R for solving analytic challenges. It is, without a doubt, one of the most powerful analytic tools available to us as data scientists, providing the ability to solve modelling challenges using a range of traditional and modern analytic approaches. However, the reality is that we can fit the best models and write the best code, but unless someone in the business…
Original Post: Why Bother with Shiny?

Database bulk update and inline editing in a Shiny Application

Ava Yang, Data Scientist There are times when it costs more than it should to leverage javascript, database, html, models and algorithms in one language. Now maybe is time for connecting some dots, without stretching too much. If you have been developing shiny apps, consider letting it sit on one live database instead of manipulating data I/O by hand? If you use DT to display tables in shiny apps, care to unleash the power of interactivity to its full? If you struggle with constructing SQL queries in R, so did we. Inspired (mainly) by the exciting new inline editing feature of DT, we created a minimal shiny app demo to show how you can update multiple values from DT and send the edits to database at a time. As seen in the screenshot, after double clicking on a cell and…
Original Post: Database bulk update and inline editing in a Shiny Application

Praise you like I should: Shiny Appreciation Month

Aimée Gott, Education Practice Lead Back in the summer of 2012 I was meant to be focusing on one thing: finishing my thesis. But, unfortunately for me, a friend and former colleague came back from a conference (JSM) and told me all about a new package that she had seen demoed. “You should sign up for the beta testing and try it out,” she said. So, I did. That package was Shiny and after just a couple of hours of playing around I was hooked. I was desperate to find a way to incorporate it into my thesis, but never managed to; largely due to the fact it wasn’t available on CRAN until a few months after I had submitted and because, at the time, it was quite limited in its functionality. However, I could see the potential – I…
Original Post: Praise you like I should: Shiny Appreciation Month

EARL Boston 2018 Keynote Speaker announcement: Bob Rudis

Mango Solutions are delighted to announce our Keynote Speaker for the EARL Boston Conference: Bob Rudis, [Master] Chief Data Scientist at Rapid7. Bob has more than 20 years’experience using data to help defend global Fortune 100 companies and in his current role at Rapid7, he specializes in research on internet-scale exposure. He was formerly a Security Data Scientist and Managing Principal at Verizon, overseeing the team that produces the annual Data Breach Investigations Report. If you’re on Twitter, you’ll know Bob as a serial tweeter (he’s even got the blue tick) – if you don’t already follow him, you can find him at @hrbrmstr. He’s also an avid blogger at rud.is, author (Data-Driven Security) and speaker. As a prominent and avuncular participant of the twitter #rstats conversation and prolific package author, Bob is a respected and valued member of the…
Original Post: EARL Boston 2018 Keynote Speaker announcement: Bob Rudis

EARL London 2018 – Agenda announced

The EARL London 2018 agenda is now available. Explore the schedule of keynotes, presentations, and lightning talks that cover a huge range of topics, including the best uses of Shiny, R in healthcare, using R for good, and R in finance. The brilliant lineup of speakers-who represent a wide range of industries-is sure to provide inspiration for all R users of all levels. We have surveyed the Mango team to find out what talks they are most looking forward to: Lung cancer detection with deep learning in R – David Smith, MicrosoftDavid will be taking us through an end-to-end example of building a deep learning model to predict lung cancer from image data. Anything that helps to improve healthcare is a fascinating subject. Using network analysis of colleague relationships to find interesting new investment managers – Robin Penfold, Willis Towers…
Original Post: EARL London 2018 – Agenda announced

eRum 2018 highlights

Aimée Gott, Education Practice Lead I always find it difficult to pick highlights from a conference and the eRum 2018 team did a fantastic job of making it difficult for me once again, so here goes… Day One The first day offered a huge choice in workshops, but teaching one of them meant we didn’t make it to any of the others. However, everyone we spoke to had great things to say about them all. In fact, we were overwhelmed by the turnout for our own workshop on the keras package (and we have to give a shout out to Mark Sellors for setting up and monitoring the server for us). By the way, if you missed out, you can sign up for the workshop at EARL London in September. Day Two Tuesday might have been a rainy start outside…
Original Post: eRum 2018 highlights