Raincloudplots Workshops

Repository about the upcoming 'raincloudplots' workshops which are part of our NWO 'Open Science' funded project: raincloudplots 2.0 by Rogier Kievit and Jordy van Langen.

You can find additional info about our funded project here: https://www.nwo.nl/en/projects/203001011

What are raincloudplots?

Raincloud plots were created and developed by Micah Allen, Davide Poggiali, Kirstie Whitaker, Tom Rhys Marshall, Jordy van Langen and Rogier Kievit.

"Across scientific disciplines, there is a rapidly growing recognition of the need for more statistically robust, transparent approaches to data visualization. Complementary to this, many scientists have called for plotting tools that accurately and transparently convey key aspects of statistical effects and raw data with minimal distortion. Previously common approaches, such as plotting conditional mean or median barplots together with error-bars have been criticized for distorting effect size, hiding underlying patterns in the raw data, and obscuring the assumptions upon which the most commonly used statistical tests are based. We describe a data visualization approach which overcomes these issues, providing maximal statistical information while preserving the desired ‘inference at a glance’ nature of barplots and other similar visualization devices. These “raincloud plots” can visualize raw data, probability density, and key summary statistics such as median, mean, and relevant confidence intervals in an appealing and flexible format with minimal redundancy. We created and shared our open-source code for raincloudplots implementation in R, Python and Matlab https://github.com/RainCloudPlots/RainCloudPlots."

For an extensive overview about raincloudplots, please read our paper or try out our R-package 'raincloudplots'.

Paper

- Allen, M., Poggiali, D., Whitaker, K., Marshall, T. R., van Langen, J., & Kievit, R. A.
    Raincloud plots: a multi-platform tool for robust data visualization [version 2; peer review: 2 approved] 
    Wellcome Open Research 2021, 4:63. https://doi.org/10.12688/wellcomeopenres.15191.2

R-package: 'raincloudplots'

How to install:

if (!require(remotes)) {
    install.packages("remotes")
}
remotes::install_github('jorvlan/raincloudplots')

library(raincloudplots)

R-package: 'ggrain'

How to install:

if (!require(remotes)) {
	install.packages("remotes")
}
remotes::install_github('njudd/ggrain')

library(ggrain)

Our plan

With these workshops, we hope to educate & showcase 'raincloudplots' to the wider academic community. We will host three online workshops in which we will present step-by-step tutorials for experts, who are already familiar with 'raincloudplots', but also to those who find using code (unnecessarily) daunting. The free workshops will entail plenary walk-throughs and smaller break-out-rooms.

When?

The workshops will take place on the following dates:

11-nov-2022 (online, worldwide)
- 14:00-16:00 CET
- Languages: R/Python/MATLAB/JASP
- Break-out rooms
17-feb-2023 (online, worldwide)
- 14:00-16:00 CET
- Languages: R/Python/MATLAB/JASP
- Break-out rooms

Interested in attending?

Please read the following documentation about each workshop.

Duration: Max. 2 hours
Outline:
- What are raincloudplots?
- What are alternatives?
- How to plot: from simple to advanced
- JASP Statistics
- Community input: what would you like to be improved/see?
- raincloudplots: ShinyApp demo
- Break-out rooms: (Python/Matlab/R/JASP)
  - Bring Your Own Data!
Please indicate whether you want to learn about Python/Matlab/R/JASP, which is necessary information for the subsequent Zoom break-out rooms in which we will answer any questions you have, but most importantly, give you the opportunity to Bring Your Own Data (BYOD) to co-develop & fine-tune your amazing plots!
There will be a maximum amount of 100 attendees for each workshop.

Sign-up

You can register your attendance here: https://docs.google.com/forms/d/e/1FAIpQLSeTykveO8tJl2zP-7QgNOfM3vMTbkEe5RtqxMKbE5AiVDzb1A/viewform

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