projthis is a new R-package, which offers a framework for analysis-based project workflows. You can use it to: (1) manage the dependencies among files in your workflows; projthis provides tools to support a directory structure and a naming convention. (2) manage your project’s package-dependencies; projthis helps you use a DESCRIPTION file. (3) automate the rendering of your workflow using GitHub Actions; projthis provides a template for an Action.
Here’s a couple examples of analysis projects built and automated (run daily) using projthis: covidStates, and covidIowa.
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ggplot2 is an excellent package that allows R users to create stunning data visualizations using the grammar of graphics. Over the years, the R community has developed numerous extensions to ggplot2 that extend ggplot2’s graphing capabilities and allow for creating advanced data visualizations with much ease. In this talk, I will introduce some of my most frequently used ggplot2 extensions and demonstrate their use cases using walk-through examples.
The slides for the talk can be found here github
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The R package bulletxtrctr provides many methods for analyzing bullet striations. And sometimes the results of these automated methods need some manual adjustments in order to be used in further analysis. To facilitate this process of manual adjustment and provide more insights into the data, we developed this interactive tool using Shiny. We also utilized Shiny Modules during the development of our app, which enables other developers to collaboratively extend the functionality of this app
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Central Processing Units (CPUs) or processors, are the workhorse of modern computing devices. For quite some time, processing manufacturers like Intel and AMD were racing to increase the clock speed (“Gigahertz”) of the processor. More recently, the race has been about increasing the concurrency - adding processor cores that perform tasks in parallel. While many of the lower level libraries in R take advantage of these cores, often there are “embarrassingly parallelizable” tasks we perform in a data analysis that can be drastically sped up via explicit parallelism.
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This will be a demonstration of the boxr package, which provides an R client to the Box file-sharing service. For example, you can upload and download files to/from your CyBox account using R functions. By far, the biggest hurdle to using boxr is the authentication. Guillermo Basulto will walk us through an authentication example using CyBox; if you will have boxr installed on your computer, you can get this step out of the way during the presentation.
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