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rOpenSci - open tools for open science

rOpenSci - open tools for open science
Open Tools and R Packages for Open Science
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The rOpenSci suite of packages is mainly composed of packages contributed by the community through peer-review, but also includes some packages maintained by staff.Over time, the commitments and availability of the original developers of a package can change. This leads to some maintainers stepping down from their maintainer role, or other maintainers looking to lower their workload through more teamwork and therefore looking for co-maintainers.

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Why a Champions Program? Champion programs are designed to identify, recognize, and reward passionate community members. At rOpenSci, we recognize that there is a dismaying lack of diversity in the ecosystem of research software and open source communities. The R Community is no exception; its developers are overwhelmingly white, male, and from a handful of countries.

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This blog post is intended to help you get started in rOpenSci community by highlighting some key links and activities. If you have questions, please get in touch with our Community Manager, Yanina Bellini Saibene by email or schedule a meeting. We are here for you as you begin your journey with our community. Welcome!Where do I get started? Glad you asked!

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Author The rOpenSci Team

Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog.Now let’s dive into the activity at and around rOpenSci!rOpenSci HQ Coworking sessions resume! Join us for social coworking & office hours monthly on first Tuesdays!Hosted by Steffi LaZerte and various community hosts.Everyone welcome.No RSVP needed.Consult our Events page to find your local time and how to join.

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In the last post, we used the qualtRics 1 package to import survey data directly from Qualtrics accounts.I often use Qualtrics for survey data collected via Amazon’s Mechanical Turk, which is an automated system that connects online respondents to paid surveys.However, sometimes those data are not super useful because the quality of the data is poor.In the anonymous, large-scale market of online survey respondents, the financial

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Package yfR recently passed peer review at rOpenSci and is all about downloading stock price data from Yahoo Finance (YF). I wrote this package to solve a particular problem I had as a teacher: I needed a large volume of clean stock price data to use in my classes, either for explaining how financial markets work or for class exercises. While there are several R packages to import raw data from YF, none solved my problem.

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In this post I will provide some examples of what has changed between rtweet 0.7.0 and rtweet 1.0.2.I hope both the changes and this guide will help all users.I highlight the most important and interesting changes in this blog post, and for a full list of changes you can consult it on the NEWS. Big breaking changes More consistent output This is probably what will affect the most users.All functions that return data about