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?

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.

Release 1.4 of the magick package introducesa new feature called image convolution thatwas 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.

Just last week we organised the 2nd rOpenSci ozunconference, the sibling rOpenSci unconference, held in Australia. Last year it was held in Brisbane, this time around, the ozunconf was hosted in Melbourne, from October 26-27, 2017. At the ozunconf, we brought together 45 R-software users and developers, scientists, and open data enthusiasts from academia, industry, government, and non-profits.

A new rOpenSci package provides access to data to which users may already have directly contributed, and for which contribution is fun, keeps you fit, and helps make the world a better place. The data come from using public bicycle hire schemes, and the package is called bikedata.

KO: What is your name, job title, and how long have you been using R? DS: My name is David Smith. I work at Microsoft and my self-imposed title is ‘R Community Lead’. I’ve been working with R specifically for about 10 years, but I’d been working with S since the early 90s.

This week we released version 3.0 of the curl R package to CRAN. You may have never used this package directly, but curl provides the foundation for most HTTP infrastructure in R, including httr, rvest, and all packages that build on it. If R packages need to go online, chances are traffic is going via curl.

A growing community of scientists from a variety of disciplines is moving the norms of scientific research toward open practices. Supporters of open science hope to increase the quality and efficiency of research by enabling the widespread sharing of datasets, research software source code, publications, and other processes and products of research.

One of the greatest assets human beings possess is the power of speech and language, from which almost all our other accomplishments flow. To be able to analyse communication offers us a chance to gain a greater understanding of one another.

One of rOpenSci’s aims is to build capacity of software users and developers and foster a sense of pride in their work. What better way to do that than to encourage you to participate in Hacktoberfest, a month-long celebration of open source software! It doesn’t take much to get involved Beginners to experts. Contributors and package maintainers welcome.

What is rrricanes Why Write rrricanes? There is a tremendous amount of weather data available on the internet. Much of it is in raw format and not very easy to obtain. Hurricane data is no different. When one thinks of this data they may be inclined to think it is a bunch of map coordinates with some wind values and not much else. A deeper look will reveal structural and forecast data.