{"id":3743,"date":"2026-05-28T13:13:55","date_gmt":"2026-05-28T17:13:55","guid":{"rendered":"https:\/\/blogs.mathworks.com\/graphics-and-apps\/?p=3743"},"modified":"2026-05-28T13:13:55","modified_gmt":"2026-05-28T17:13:55","slug":"raincloudplot-cloudy-with-a-chance-of-observations","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/graphics-and-apps\/2026\/05\/28\/raincloudplot-cloudy-with-a-chance-of-observations\/","title":{"rendered":"raincloudplot: Cloudy With A Chance of Observations"},"content":{"rendered":"\r\n\r\n\r\n
\"\"<\/td>\r\nGuest Writer: Baldvin Einarsson<\/a>\r\n<\/strong>\r\n
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Baldvin is a software engineer in the Statistics and Machine Learning Toolbox. His journey with MATLAB began in the early 2000s during his college years in Iceland, where he first discovered his passion for scientific computing and visualizations. Before joining MathWorks, Baldvin's mathematical research interests included modeling growth and migration patterns of pelagic fish, coupled oscillators and dynamical systems, and biofilm growth. Baldvin then spent nearly 9 years at a natural catastrophe risk modeling firm in Boston before his dream of joining MathWorks became true in 2022. Outside of work, Baldvin enjoys fly tying, knitting, woodworking, and playing the piano.<\/div>\r\n<\/div>\r\n<\/div><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
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It's raining data visualizations in MATLAB! In this article, we introduce the <\/span>raincloudplot<\/span><\/a>, a convenient way to show both distributions <\/span>and<\/span> individual observations in a single chart. A bit of history first: in R2024b we introduced the <\/span>violinplot<\/span><\/a>, and in R2025a <\/span>scatter<\/span><\/a> objects gained new properties to control the direction of jittered points, such as <\/span>YJitterDirection<\/span>. Together, these features made it possible to combine violins and scatter points to create rain cloud plots. But, doing so required careful coordination and styling across multiple objects. With the new <\/span>raincloudplot<\/span> function, all of that comes together in one place. Creating, modifying, and styling rain cloud plots is now as easy as predicting yesterday\u2019s weather.<\/span><\/div>\r\n

The Perfect Storm<\/span><\/h2>\r\n
The top part of a rain cloud is the \"cloud\" (the violin plot), followed by the \"rain\" (the scatter). Let's use the same data we used in the <\/span>violin plot blog post<\/span><\/a>:<\/span><\/div>\r\n
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rng(42);<\/div>\r\n<\/div>\r\n
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nPts=24;<\/div>\r\n<\/div>\r\n
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cloudData = [1.2*randn(1,6*nPts), 0.5*randn(1,4*nPts) + 6, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a06+8*rand([1,nPts]), 8*rand([1,nPts])];<\/div>\r\n<\/div>\r\n
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loc = ones(size(cloudData));<\/div>\r\n<\/div>\r\n<\/div>\r\n
Compare creating the two parts individually and with <\/span>raincloudplot:<\/span><\/div>\r\n<\/div>\r\n
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v = violinplot(loc, cloudData, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0Orientation=\"horizontal\"<\/span>, DensityDirection=\"positive\"<\/span>, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0DisplayName=\"The Cloud\"<\/span>);<\/div>\r\n<\/div>\r\n
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hold on<\/span><\/div>\r\n<\/div>\r\n
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scatter(cloudData,loc, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0'filled'<\/span>, MarkerFaceAlpha=v.FaceAlpha, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0MarkerEdgeColor=\"flat\"<\/span>, MarkerEdgeAlpha=1, ....<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0YJitter=\"density\"<\/span>, YJitterDirection=\"negative\"<\/span>,...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0SeriesIndex=v.SeriesIndex, ...<\/div>\r\n<\/div>\r\n
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\u00a0\u00a0\u00a0\u00a0DisplayName=\"The Rain\"<\/span>);<\/div>\r\n<\/div>\r\n
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hold off<\/div>\r\n<\/div>\r\n
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legend<\/div>\r\n<\/div>\r\n<\/div>\r\n