Growth of DataFest over the years

In a previous post, I introduced DataFest and how one can streamline the organization of this event using Google Forms and tools from the tidyverse. In this post, I’ll walk through building a Shiny app that demonstrates the growth of DataFest over the years, both in terms of host locations and participating institutions, as well as in terms of the number of students who participated in each event.

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Review of Efficient R Programming

In the crowded market space of data science and R language books, Lovelace and Gillespie’s Efficient R Programming (2016) stands out from the crowd. Over the course of ten comprehensive chapters, the authors address the primary tenets of developing efficient R programs. Unless you happen to be a member of the R core development team, you will find this book useful whether you are a novice R programmer or an established data scientist and engineer.

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Databases using R

As R developers, our first instinct may be to approach databases the same way we do regular files. We start by reading all of the data into memory and then proceed to data exploration. But what if there is a better way…

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Looking Forward to R/Finance 2017

R / Finance 2017 starts next Friday, and once again, I am excited about going. It’s true that there are quite a few fun and informative R gatherings these days, but R / Finance is a “big deal” because it is the “real deal”. Finance has been, and remains, one of the driving applications underlying the R language. (A glance at the CRAN Task Views for Finance and Time Series will give you an idea of the depth and extent of the work done in this area since the early days of R.

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Mapping Quandl Macroeconomic Data

In previous posts, we built a map to access global ETFs and a simple Shiny app to import and forecast commodities data from Quandl. Today, we will begin a project that combines those previous apps. Our end goal is to build an interactive map to access macroeconomic data via Quandl, allowing the user to choose an economic indicator and click on a country to access that indicator’s time series.

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How to Establish a Web Presence as an R User and Why It's Important

If you are a developer using the R environment to do your programming work, you are probably feeling left out and a bit segregated from the rest of the programming industry. It’s true that not many people know about the R language and what its uses are; however, things have been getting better in the past couple of years as more and more businesses are starting to implement R into their processes.

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Shiny in Medicine

Shiny Apps are becoming ubiquitous as a way for data scientists to present the results of an analysis, and also to engage with information consumers who may not be coders. The trend I see is that the greater the variety of skills and interests of the information consumers for any particular project, the more valued are interactive visualizations that can be integrated into enterprise-wide communication workflows. So, it is not surprising to see Shiny apps popping up in all manner of healthcare and medical applications.

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NY R Conference

The 2017 New York R Conference was held last weekend in Manhattan. For the third consecutive year, the organizers - a partnership including Lander Analytics, The New York Meetup and Work-Bench - pulled off a spectacular event. There was a wide range of outstanding talks, some technical and others more philosophical, a palpable sense of community and inclusiveness, great food, beer and Bloody Marys. Fortunately, the talks were recorded. While watching the videos (which I imagine will be available in a couple of weeks) will be no substitute for the experience, I expect that the extended R community will find the talks valuable.

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A Shiny App for Importing and Forecasting Commodities Prices from Quandl

an interactive Shiny app that lets the user choose a commodity, run a forecast and graph the results

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R for Enterprise: Understanding R’s Startup

R’s startup behavior is incredibly powerful. R sets environment variables, loads base packages, and understands whether you’re running a script, an interactive session, or even a build command. Most R users will never have to worry about changing R’s startup process. In fact, for portability and reproducibility of code, we recommend that users do not modify R’s startup profile. But, for system administrators, package developers, and R enthusiasts, customizing the launch process can provide a powerful tool and help avoid common gotchas.

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