knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
ggVennDiagram has a series of set operation functions, and this can be used as the Venn calculator.
library(ggVennDiagram) set.seed(20231225) y = list( A = sample(letters, 8) |> sort(), B = sample(letters, 8) |> sort(), C = sample(letters, 8) |> sort(), D = sample(letters, 8) |> sort()) y
First of all, we need to construct a Venn class object with this list. If you print this object, it will give meta information of the object.
venn_y = Venn(y) venn_y
r
overlap(venn_y, 1:2) # members in both the first two sets
overlap(venn_y) # members in all the sets
r
discern(venn_y, 1) # members in set 1, but not in the resting sets
discern(venn_y, c("A","B"), 3) # members in set A & B, but not in the 3rd set
r
discern_overlap(venn_y, 1) # specific items in set 1
discern_overlap(venn_y, 1:2) # specific items in set 1 and set 2
r
unite(venn_y, 1:2) # union of set 1 and 2
unite(venn_y, "all") # union of all four sets
unite(venn_y, c("A", "B", "C"))
Combined results were provided as VennPlotData object.
r
pd = process_data(venn_y)
pd
venn_set(): get set data from the object. r
venn_set(pd)
venn_region(): get subsets data from the object.r
venn_region(pd)
Please note in order to keep the result concise, the containing items are nested. You may use the following methods to further process it.
r
venn_region(pd) |> tidyr::unnest(item)
r
venn_region(pd) |> dplyr::rowwise() |> dplyr::mutate(item = paste0(item, collapse = ", "))
Some of these above-mentioned functions are originally developed by Turgut Yigit Akyol in RVenn.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.