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ggrain - a ggplot2 extension for raincloud plots

Judd, N.; vanLangen, J.; Poggiali, D.; Whitaker, K.; Rhys Marshall, T.; Allen, M.; Kievit, R.

2024-12-17 scientific communication and education
10.1101/2024.12.13.628294 bioRxiv
Show abstract

Clear data visualization is essential to effectively communicate empirical findings across various research fields. Raincloud plots fill this need by offering a transparent and statistically robust approach to data visualization. This is achieved by combining three plots in an aesthetically pleasing fashion. First, a dot plot displays raw data with minimal distortion, allowing a fast glance at the sample size and outlier identification. Next, a box plot displays key distributional summary statistics such as the median and interquartile range. Lastly, a violin plot transparently displays the underlying distribution of the data. Despite the widespread use of raincloud plots, an R-package in alignment with the grammar of graphics was lacking. `ggrain` fills this need by offering one easy-to-use function (`geom_rain`) allowing the quick and seamless plotting of rainclouds in the R ecosystem. Further, it enables more complex plotting features such as factorial grouping, mapping with a secondary (continuous) covariate, and connecting observations longitudinally across multiple waves.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
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2
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Top 23%
5.4%
50% of probability mass above
7
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Top 20%
4.7%
8
PLOS ONE
● 5266 papers in training set
Top 33%
3.9%
9
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10
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Top 0.3%
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11
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Top 0.1%
2.6%
13
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○ 993 papers in training set
Top 12%
1.9%
14
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● 439 papers in training set
Top 4%
1.9%
15
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○ 30 papers in training set
Top 0.3%
1.7%
16
Nature Biotechnology
○ 172 papers in training set
Top 3%
1.6%
17
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◐ 212 papers in training set
Top 3%
1.1%
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Ecology and Evolution
○ 267 papers in training set
Top 5%
1.1%
19
PeerJ
◐ 308 papers in training set
Top 8%
1.1%
20
iScience
○ 1154 papers in training set
Top 28%
1.1%
21
Proceedings of the Royal Society B: Biological Sciences
● 393 papers in training set
Top 6%
0.8%
22
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○ 165 papers in training set
Top 4%
0.8%
23
Nature Communications
○ 5641 papers in training set
Top 57%
0.8%
24
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● 25 papers in training set
Top 0.5%
0.6%
25
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● 242 papers in training set
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0.6%
26
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27
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.