Working together to push science forward
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This year’s rOpenSci ozunconf was held in Melbourne, bringing together over 45 R enthusiasts from around the country and beyond. As is customary, ideas for projects were discussed in GitHub Issues (41 of them by the time the unconf rolled around!) and there was no shortage of enthusiasm, interesting concepts, and varied experience. I’ve been to a few unconfs now and I treasure the time I get to spend with new people, new ideas, new backgrounds, new approaches, and new insights....
Mara Averick, Data Nerd At Large Mara Averick is a non-profit data nerd, NBA stats junkie, and most recently, tidyverse developer advocate at RStudio. She is the voice behind two very popular Twitter accounts, @dataandme and @batpigandme. Mara and I discussed sports analytics, how attending a cool conference can change the approach to your career, and how she uses Twitter as a mechanism for self-imposed forced learning. KO: What is your name, job title, and how long have you been using R?...
Nearly 4 years ago I wrote on this blog about an R package solr for working with the database Solr. Since then we’ve created a refresh of that package in the solrium package. Since solrium first hit CRAN about two years ago, users have raised a number of issues that required breaking changes. Thus, this blog post is about a major version bump in solrium. 🔗 What is Solr? Solr is a “search platform” - a NoSQL database - data is organized by so called documents that are xml/json/etc blobs of text....
This week magick 1.5 appeared on CRAN. The latest update adds support for using images in knitr documents and shiny apps. In this post we show how this nicely ties together a reproducible image workflow in R, from source image or plot directly into your report or application. library(magick) stopifnot(packageVersion('magick') >= 1.5) Also the magick intro vignette has been updated in this version to cover the latest features available in the package....
Release 1.4 of the magick package introduces a new feature called image convolution that was requested by Thomas L. Pedersen. In this post we explain what this is all about. 🔗 Kernel Matrix The new image_convolve() function applies a kernel over the image. Kernel convolution means that each pixel value is recalculated using the weighted neighborhood sum defined in the kernel matrix. For example lets look at this simple kernel:...
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