Blog Archives

The Value of Welcome, part 2: How to prepare 40 new community members for an unconference

The Value of Welcome, part 2: How to prepare 40 new community members for an unconference

I’ve raved about the value of extending a personalized welcome to new community members and I recently shared six tips for running a successful hackathon-flavoured unconference. Building on these, I’d like to share the specific approach and (free!) tools I used to help prepare new rOpenSci community members to be productive at our unconference. My approach was inspired directly...

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Announcing a New rOpenSci Software Review Collaboration

rOpenSci is pleased to announce a new collaboration with the Methods and Ecology and Evolution (MEE), a journal of the British Ecological Society, published by Wiley press 1. Publications destined for MEE that include the development of a scientific R package will now have the option of a joint review process whereby the R package is reviewed by rOpenSci,...

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changes: easy Git-based version control from R

changes: easy Git-based version control from R

Are you new to version control and always running into trouble with Git? Or are you a seasoned user, haunted by the traumas of learning Git and reliving them whilst trying to teach it to others? Yeah, us too. Git is a version control tool designed for software development, and it is extraordinarily powerful. It didn’t actually dawn on me quite how...

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ochRe – Australia themed colour palettes

ochRe – Australia themed colour palettes

The second rOpenSci OzUnConf was held in Melbourne Australia a few weeks ago. A diverse range of scientists, developers and general good-eggs came together to make some R-magic happen and also learn a lot along the way. Before the conference began, a huge stack of projects were suggested on the unconf GitHub repo. For six data-visualisation enthusiasts, one...

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Six tips for running a successful unconference

Six tips for running a successful unconference

Attendees at the May 2017 rOpenSci unconference. Photo credit: Nistara Randhawa In May 2017, I helped run a wildly successful “unconference” that had a huge positive impact on the community I serve. rOpenSci is a non-profit in...

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2017 rOpenSci ozunconf :: Reflections and the realtime Package

2017 rOpenSci ozunconf :: Reflections and the realtime Package

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...

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.rprofile: Mara Averick

.rprofile: Mara Averick

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...

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solrium 1.0: Working with Solr from 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...

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Using Magick with RMarkdown and Shiny

Using Magick with RMarkdown and Shiny

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...

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Image Convolution in R using Magick

Image Convolution in R using Magick

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...

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