Publications by R Views
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 commun...
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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 busine...
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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 ...
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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 ...
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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 Ta...
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Databases using R
Current State Using databases is unavoidable for those who analyze data as part of their jobs. As R developers, our first instinct may be to approach databases the same way we do regular files. We may attempt to read the data either all at once or as few times as possible. The aim is to reduce the number of times we go back to the data ‘well’...
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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 f...
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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 ...
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Civic Data Wrangling: in R and on data.world
One of the most valuable things I have learned working on Data for Democracy’s Medicare drug spending project has been the value of collaborative tools. It has been my first in-depth experience using Github collaboratively, for one, but it has also introduced me to data.world. data.world is an intuitive way to store, organize, explore, and visu...
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April New Package Picks
Here are my picks for the “Top 40” new packages submitted to CRAN in April 2017. These selections, which were culled from 208 submissions, are organized into four categories: Data, Finance, Statistics and Utilities. The number of entries in the Data and Utilities categories reflect the initiatives of R developers to connect to external resour...
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