Sorry about this. That post is old and the arguments have changed.

Try this instead

fit2 <- euler(c(A = 16971, B = 218, C = 215, 
                "A&B" = 112, "A&C" = 112, "B&C"= 51,"A&B&C" = 23))
plot(fit2,
     fills = c("dodgerblue4", "darkgoldenrod1", "cornsilk4"),
     edges = FALSE,
     fontsize = 8,
     quantities = list(fontsize = 8))

The plot method for euler objects uses grid::grid.legend() to plot the legend. You can specify any of grid.legend's arguments in the legend argument to plot (which really calls plot.euler). To get a horizontal legend, use

plot(fit1,
     quantities = TRUE,
     fills = list(fill = col, alpha = 0.8),
     edges = "black",
     main = list(label = "test", cex = 0.9),
     legend = list(side = "bottom", nrow = 1, ncol = 3))

Since you are in R, consider using the UpsetR library. It doesn't make Venn diagrams but it helps to visualize overlaps between any number of groups.

http://gehlenborglab.org/research/projects/upsetr/#:~:text=UpSetR%20is%20an%20R%20package,based%20on%20groupings%20and%20queries.

As explained in the comments, you will not be able to express an arbitrary set of relationships for more than 3 sets with circles. The package eulerr uses ellipses to get more combinations and also make the result somewhat proportional to the number of elements in each region. I made a different package called nVennR that uses circles for the regions instead of the sets. The sets are then drawn around those circles:

> library(nVennR)
> myT <- read.table('clipboard', header = T)
> lol <- as.list(myT)
> myV <- plotVenn(lol)
> myV <- plotVenn(nVennObj = myV)
> myV <- plotVenn(nVennObj = myV)
> myV <- plotVenn(nVennObj = myV)
> myV <- plotVenn(nVennObj = myV)
> myV <- plotVenn(nVennObj = myV)
> myV <- showSVG(nVennObj = myV, opacity = 0.2)

Repeating the command myV <- plotVenn(nVennObj = myV) is necessary to get a compact shape. If you try it, you will see that it takes a couple of minutes, as it needs to perform several simulations. The package can take any number of sets, but things get really slow above 9 sets. The result:

You can save, edit and improve the picture to better show the information, but it is not trivial. You can find more information in the vignette.

Regarding how to fix the issue, it depends on the level of precission you want. From the nVenn algorithm, I authored the nVennR package to create quasi-proportional Euler diagrams. With the caveats mentioned in the link, you can represent larger numbers of sets and show the relative size of each region. In your example,

library(nVennR)
myV <- createVennObj(nSets = 4, sNames = c('A', 'B', 'C', 'D'), sSizes = c(0, 26, 53, 7, 22, 5, 16, 3, 54, 10, 29, 4, 20, 5, 14, 3))
myV <- plotVenn(nVennObj = myV)

And the result would be:

Depending on your requirements, this may not be satisfactory. The proportionality is in the area of the circles, not the regions (you can see that the region 1, 2, 3, 4 - A&B&C&D - has empty space. However, this strategy overcomes the limitations of regular shapes in these representations mentioned by Johan Larsson. If you are interested, there are more details in the vignette.

This is one approach to adjusting the label and quantity sizes and providing a "margin".

Check out the documentation under plot.euler for other formatting options.

As eulerr is based on grid you can provide margins in effect by adjusting the size of the viewport used for plotting. The answer shows a plot reduced to 80% of the original height and width.

Although I noticed that the relative positions of the venn diagram elements changes as you rerun the code I never found that the circles straying outside the canvas margin.

set.seed() did not seem to change anything.

library(eulerr)
library(grid)

my_dt <- data.frame(
  value = c(1:8), 
  A = c(TRUE,  TRUE, FALSE, TRUE,  TRUE, FALSE, FALSE, TRUE),
  B = c(TRUE,  FALSE,  TRUE, TRUE, FALSE, FALSE, TRUE,  TRUE),
  C = c(FALSE, FALSE, FALSE, FALSE, TRUE,  TRUE,  TRUE, FALSE)
)

p <- plot(euler(my_dt[, c("A", "B", "C")]), 
     quantities = list(cex = 2),
     labels = list(cex = 2))

# edit the viewport dimensions

p$vp$width <- unit(0.8, "npc")
p$vp$height <- unit(0.8, "npc")


p

^{Created on 2023-06-30 with reprex v2.0.2}