Publications by R Views
How to Build a Shiny “Truck”!
Why is this about trucks? Last month, at the R/Pharma conference that took place on the Harvard Campus, I presented bioWARP, a large Shiny application containing more than 500,000 lines of code. Although several other Shiny apps were presented at the conference, I noticed that none of them came close to being as big as bioWARP. And I asked myself...
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GDP Data via API
Today, we will look at the GDP data that is released every quarter or so by the Bureau of Economic Analysis (BEA), and get familiar with the BEA API (see the documentation here). For a primer on GDP in general, BEA publishes this guide. To access the BEA API, we will need two packages, httr and jsonlite. library(tidyverse) library(tidyquant) libr...
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Interactive plots in Shiny
I wish this post existed when I was struggling to add interactive plots to my Shiny app. I was mainly focused on recreating functionality found in other “dashboarding” applications. When looking for options, I found that htmlwidgets were the closest to what companies usually expect. However, while they are great for client-side interactivity,...
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August 2018: Top 40 New Packages
Package developers relaxed a bit in August.; only 160 new packages went to CRAN that month. Here are my “Top 40” picks organized into seven categories: Data, Machine Learning, Science, Statistics, Time Series, Utilities, and Visualization. Data nsapi v0.1.1: Provides an interface to the Nederlandse Spoorwegen (Dutch Railways) API, allowing us...
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Some Thoughts on R / Pharma 2018
It’s no secret that there are few industries more competitive than the pharmaceutical industry. Big money placed on long-shot bets for block-buster drugs where being first makes all the difference means a constant struggle to gain a competitive edge. So, you might find it surprising that the inaugural R / Pharma Conference held this past August...
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September 2018: Top 40 New Packages
September was another relatively slow month for new package activity on CRAN: “only” 126 new packages by my count. My Top 40 list is heavy on what I characterize as “utilities”: packages that either extend R in some fashion or make it easier to do things in R. This month, the packages I selected fall into eight categories: Data, Finance, ...
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Serendipity at R / Medicine
We knew we were on to something important early on in the process of organizing R / Medicine 2018. Even during our initial attempts to articulate the differences between this conference and R / Pharma 2018, it became clear that the focus on the use of R and statistics in clinical settings was going to be a richer topic than just the design of cli...
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Searching for R Packages
Searching for R packages is a vexing problem for both new and experienced R users. With over 13,000 packages already on CRAN, and new packages arriving at a rate of almost 200 per month, it is impossible to keep up. Package names can be almost anything, and they are rarely informative, so searching by name is of little help. I make it a point to ...
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CRAN’s New Missing Data Task View
It is a relatively rare event, and cause for celebration, when CRAN gets a new Task View. This week the r-miss-tastic team: Julie Josse, Nicholas Tierney and Nathalie Vialaneix launched the Missing Data Task View. Even though I did some research on R packages for a post on missing values a couple of years ago, I was dumbfounded by the number of p...
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Reproducible Finance, the book! And a discount for our readers
I’m thrilled to announce the release of my new book Reproducible Finance with R: Code Flows and Shiny Apps for Portfolio Analysis, which originated as a series of R Views posts in this space. The first post was written way back in November of 2016 – thanks to all the readers who have supported us along the way! If you are familiar with the R ...
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