The density of dots and the “fatness” of the band present the frequency of a particular value in Y-axis. In the R help mailing list, there was recently a question asked on this topic (which had led me to writing this post) asking for:Ī band of dots on the plot are the data point. In a followup post, Ken posted of some suggestions he received from his readers on how to make the plot better (through other functions, and also on ggplot2 implementations) With(female,boxpoints2(pcs, homeless, "PCS", "Homeless")) # plotting. He wrapped his code and it can be run using the following command: source("") # getting the boxplonts3 function In his blog “ SAS and R“, Ken Kleinman has wrote about the creation of a dot-box-plot about half a year ago. In the R web-ecosystem, several people have written and asked about this. But the main focus of this post will (expectedly) be R. I’ve noticed that GGobi has a “texture” 1D plot, which is a very similar implementation of this plot. Implementations in Free Open-Source statistical packages I imagine there is also something similar in the “big” packages (SAS, JMP, SPSS etc…), but I could not yet find an example. (My thanks goes to nico for finding this examples) GraphPad implements this graph under the name “ column scatter plot” (with line drawn at the mean) made from the “Frequency distribution” sample data. Implementations in commercial statistical packages And if you know of an implementation I’ve missed please tell me about it in the comments. This plot has been implemented in various statistical packages, in this post I will list the few I came by so far. The plot can be superimposed with a boxplot to give a very rich description of the underlaying distribution. This “Scatter Dot Beeswarm Box Violin – plot” (in the lack of an agreed upon term) is a one-dimensional scatter plot which is like “stripchart”, but with closely-packed, non-overlapping points the positions of the points are corresponding to the frequency in a similar way as the violin-plot. The above plot is implemented under different names in different softwares. (The image above is called a “Beeswarm Boxplot”, the code for producing this image is provided at the end of this post) In summary, “beeswarm” plots are not recommended as they often create visual artifacts that distracts from the estimated density of the observations. Update: I strongly recommend reading the comment by Leland Wilkinson.
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