All posts (Page 102 of 130)
Most of us who work in R just want to Get Stuff Done™. We want a minimum amount of friction between ourselves and the data we need to wrangle, analyze, and visualize. We’re focused on solving a problem or gaining insights into a new area of research. We rely on a rich, community-driven ecosystem of packages to help get our work done and likely make an unconscious assumption that there is a safety net out there, protecting us from harm....
In my training as a AAAS Community Engagement Fellow, I hear repeatedly about the value of extending a personal welcome to your community members. This seems intuitive, but recently I put this to the test. Let me tell you about my experience creating and maintaining a #welcome channel in a community Slack group.
Welcome by Nathan under CC BY-SA 2.0
I listen in on and occasionally participate in a Slack group for R-Ladies community organizers (R-Ladies is a global organization with local meetup chapters around the world, for women who do/want to do programming in R). Their Slack is incredibly well-organized and has a #welcome channel where new joiners are invited to introduce themselves in a couple of sentences. The leaders regularly jump in to add a wave emoji and ask people to introduce themselves if they have not already.
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Like every R user who uses summary statistics (so, everyone), our team has to rely on some combination of summary functions beyond summary() and str(). But we found them all lacking in some way because they can be generic, they don’t always provide easy-to-operate-on data structures, and they are not pipeable. What we wanted was a frictionless approach for quickly skimming useful and tidy summary statistics as part of a pipeline. And so at rOpenSci #unconf17, we developed skimr....
rOpenSci’s mission is to promote a culture of open, transparent, and reproducible research across various research domains. Everything we do, from developing high-quality open-source software for data science and, software review, to building community through events like our community calls and annual unconference are all geared toward lowering barriers to reproducible, open science.
The rOpenSci Fellowship presents a unique opportunity for researchers who are engaged in open source to have a bigger voice in their communities. These fellowships are designed to support individual researchers and collaborative efforts to help them do better science, build community around projects or best practices, or develop some tools as part of ongoing research that could impact one or more research domains. Two areas that are of particular interest to us are:
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We, Alicia Schep and Miles
McBain, drove the webrockets project
at #runconf17.
To make progress we solicited code, advice, and entertaining anecdotes
from a host of other attendees, whom we humbly thank for helping to make
our project possible.
This post is divided into two sections: First up we’ll relate our
experiences, prompted by some questions we wrote for
one another. Second, we’ll put the webrockets
package into context and walk you
through a fun example where you can live plot streaming sensor data from
a mobile device.
