General info

• Video connection details:
  • Zoom ID: 662 0907 5434
  • Zoom password: rse
  • Zoom invite link: https://uwasa.zoom.us/j/66209075434?pwd=VmRBaFRVOXNKNFRYb1NDRGY5SXZndz09
• Contact:
• Date and time: 2022-01-20, 13-14 CET convert to your timezone
• This page: https://hackmd.io/6XrmG5mTSpK5AXsLUa0kPg

Developing and distributing in-house R-packages

Slides: https://athanasiamo.github.io/talks/slides/2022.01.20-rse-pgk/#1

Ice breaker question : Have you used R before? If yes, for what?

• I have used very minimal R when teaching data visualization and trying to give people reproducible examples (but I am a Python person wanting to finally learn R)
• Yes when working with ecologists but I am still a novice!!!
• Yes! But I mainly just write scripts, which seems ineffective so I'm very keen to hear the talk :) (I also train other researchers in how to get started with data analysis in R)
• Barely, long ago. And not in really sophisticated ways, nowhere near packaging.
• Unfortunately not!

About the Nordic RSE

• Represents Research Software Engineers in the Nordics.
• Check out nordic-rse.org for other activities.
• Registereed as an association in Fall 2021.
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About the series

This is an event in the Nordic RSE seminar series.

• Reminder about starting recording
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  • Check https://nordic-rse.org/events/seminar-series/.
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• Suggest speakers:
  • on the Nordic RSE stream
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Speaker: Athanasia Monika Mowinckel

Athanasia Monika Mowinckel is a cognitive neuroscientist based in Oslo, Norway, and works at the Center for Lifespan Changes in Brain and Cognition. She's passionate about cognitive neuroscience, using R and teaching the world the wonders of R. Doing all she can to improve gender diversity and equity in the R-community though R-Ladies Oslo and on the R-Ladies Global Team.

Abstract

R is mainly a statistical programming language than has been around for more than 20 years. In recent years, it has seen a large resurge in popularity, especially amongst researchers, for its powerful statistical backbone and open source practice. But R can be unfamiliar and intimidating for researchers used to a purely GUI based statistical tool. This talk will center around how I have developed in-house R tools to clean and handle in-house data, and how I have distributed these to work on multiple platforms.

Ask your questions here

• is this a question?

  • yes, and this is an answer

• How much do you account for the fact that different people collect & organise their data slightly differently? And the fact that there can be silly little errors with data (e.g. what if one of the BDI_ columns was accidentally called DBI_)? Would that get caught automatically or would it be up to the user to notice that?

• I started thinking when you didn't have a dependency installed – Is there a fast way to install all dependencies of a package you're working on while you're working on it? Okay thanks!

• What advice would you give to RSEs that support communities where R is used to stay up to date (and for instance be aware of such new and awesome developments like R-universe rOpenSci)?