Monthly Archives: June 2018

(Unit) Testing Shiny apps using testthat

June 26, 2018
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(Unit) Testing Shiny apps using testthat

This blog post explains how to test a Shiny app using shinytest and testthat packages. Basic knowledge about Shiny apps and the principle of unit testing using testthat is useful, but not required here. Example of a Shiny app The packages shiny (current version: 1.1.0), testthat (2.0.0) and shinytest (1.3.0) are required for the test

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Models are about what changes, and what doesn’t

June 25, 2018
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Models are about what changes, and what doesn’t

How do you build a model from first principles? Here is a step by step guide. Following on from last week’s post on Principled Bayesian Workflow I want to reflect on how to motivate a model. The purpose of most models is to understand change, and yet, considering what doesn’t change and should be kept constant can be equally important. I will...

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Storrrify #satRdayCDF 2018

On Saturday I was at my second satRday conference this year, lucky me! I got to attend satRday Cardiff which was a great experience. I gave a talk about rOpenSci onboarding system of packages, find my slidedeck here and other slidedecks at this address. A lot of R goodness! As I did in March for satRday Cape Town, I’ll use...

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A package for tidying nested lists

A package for tidying nested lists

Data == knowledge! Much of the data we use, whether it be from government repositories, social media, GitHub, or e-commerce sites comes from public-facing APIs. The quantity of data available is truly staggering, but munging JSON output into a format that is easily analyzable in R is an equally staggering undertaking. When JSON is turned into an R object, it usually becomes a deeply...

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May 2018: “Top 40” New Packages

June 25, 2018
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May 2018: “Top 40” New Packages

While looking over the 215 or so new packages that made it to CRAN in May, I was delighted to find several packages devoted to subjects a little bit out of the ordinary; for instance, bioacoustics analyzes audio recordings, freegroup looks at some abstract mathematics, RQEntangle computes quantum entanglement, stemmatology analyzes textual musical traditions, and treedater estimates clock rates...

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Shiny 1.1.0: Scaling Shiny with async

June 25, 2018
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Shiny 1.1.0: Scaling Shiny with async

This is a significant release for Shiny, with a major new feature that was nearly a year in the making: support for asynchronous operations! Without this capability, when Shiny performs long-running calculations or tasks on behalf of one user, it stalls progress for all other Shiny users that are connected to the same process. Therefore, Shiny apps that feature long-running...

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Models are about what changes, and what doesn’t

June 25, 2018
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Following on from last week’s post on Principled Bayesian Workflow I want to reflect on how to motivate a model. The purpose of most models is to understand change, and yet, considering what doesn’t change and should be kept constant can be equally important. I will go through a couple of models in this post to illustrate this idea. The purpose...

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Re-referencing factor levels to estimate standard errors when there is interaction turns out to be a really simple solution

June 25, 2018
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Re-referencing factor levels to estimate standard errors when there is interaction turns out to be a really simple solution

Maybe this should be filed under topics that are so obvious that it is not worth writing about. But, I hate to let a good simulation just sit on my computer. I was recently working on a paper investigating the relationship of emotion knowledge (EK) in very young kids with academic performance a year or two later. The idea...

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Running Python inside the RStudio Server IDE

June 25, 2018
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A great many R users will have to run some python...

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Rollercoaster III: yet more on Google Scholar

June 25, 2018
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Rollercoaster III: yet more on Google Scholar

In a previous post I made a little R script to crunch Google Scholar data for a given scientist. The graphics were done in base R and looked a bit ropey. I thought I’d give the code a spring clean – it’s available here. The script is called ggScholar.R (rather than gScholar.R). Feel free to

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