Data from Public Bicycle Hire Systems

Mark Padgham OCTOBER 17, 2017

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. Public bicycle hire systems operate in many cities throughout the world, and most systems collect (generally anonymous) data, minimally consisting of the times and locations at which every single bicycle trip starts and ends.

googleLanguageR - Analysing language through the Google Cloud Machine Learning APIs

Mark Edmondson OCTOBER 3, 2017

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. To help you with this, googleLanguageR is an R package that allows you to perform speech-to-text transcription, neural net translation and natural language processing via the Google Cloud machine learning services.

rrricanes to Access Tropical Cyclone Data

Tim Trice SEPTEMBER 27, 2017

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.

rOpenSci Software Review: Always Improving

Scott Chamberlain Maƫlle Salmon Noam Ross Karthik Ram SEPTEMBER 11, 2017

The R package ecosystem now contains more than 10K packages, and several flagship packages belong under the rOpenSci suite. Some of these are: magick for image manipulation, plotly for interactive plots, and git2r for interacting with git. rOpenSci is a community of people making software to facilitate open and reproducible science/research. While the rOpenSci team continues to develop and maintain core infrastructure packages, an increasing number of packages in our suite are contributed by members of the extended R community.

Experiences as a first time rOpenSci package reviewer

Verena Haunschmid SEPTEMBER 8, 2017

It all started January 26th this year when I signed up to volunteer as a reviewer for R packages submitted to rOpenSci. My main motivation for wanting to volunteer was to learn something new and to contribute to the R open source community. If you are wondering why the people behind rOpenSci are doing this, you can read How rOpenSci uses Code Review to Promote Reproducible Science. Three months later I was contacted by Maelle Salmon asking whether I was interested in reviewing the R package patentsview for rOpenSci.

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