Getting Started with glyph

Every plot on this page is built by the code above it and drawn by glyph’s D3 renderer. They are live, so you can hover, click, brush and zoom them. All the examples use mtcars, which means you can paste them into R and get the same result.

1. Tooltips and hover

interact() adds behaviour to the plot. Here it turns on tooltips and makes a point grow when the mouse is over it. titles() adds a title in the same pipeline.

glyph(mtcars, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  interact(tooltip = TRUE, hover = "enlarge") |>
  titles(title = "Motor Trend Cars")

Move the mouse over a point to enlarge it, and rest on it to see the tooltip.

2. Animated bars

animate() describes how marks enter the plot. With stagger, each bar starts a little after the one before, so they draw in sequence.

glyph(mtcars, x = cyl, y = mpg) |>
  mark_bar() |>
  animate(transition = "slide", stagger = 50)

Reload the page, or run the chunk again in R, to watch the bars slide in.

3. A dark theme

theme_tokens() sets the look of a plot from a few values. This example uses the "dark" preset. You can also set single tokens such as bg, font or accent. Text, grid and title colours are worked out from the background so they stay readable.

glyph(mtcars, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  interact(tooltip = TRUE) |>
  theme_tokens(preset = "dark") |>
  titles(title = "Dark Theme Example")

4. Labels that avoid each other

mark_text() draws one label per row. With smart_repel = TRUE, labels that overlap are nudged apart. mtcars keeps the car names in its row names, so the first line copies them into a column.

mtcars_named <- data.frame(model = rownames(mtcars), mtcars, row.names = NULL)

glyph(mtcars_named, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  mark_text(label = model, smart_repel = TRUE)

5. Linked panels

compose() places several plots in one widget. Both panels below allow brushing, and linked_selections = TRUE connects them. Rows you select in one panel are highlighted in the other.

p1 <- glyph(mtcars, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  interact(brush = TRUE)

p2 <- glyph(mtcars, x = hp, y = mpg) |>
  mark_point(color = cyl) |>
  interact(brush = TRUE)

compose(p1, p2, type = "hstack", linked_selections = TRUE)

Drag a rectangle over a few points in either panel. The same cars light up in both.

6. Small multiples

facet() splits a plot into one panel per value of a variable. You can facet by rows, by columns or by both.

glyph(mtcars, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  facet(cols = cyl)

7. Marginal distributions

marginals() draws the distribution of each axis along its edge. The choices are "histogram", "density" and "boxplot".

glyph(mtcars, x = wt, y = mpg) |>
  mark_point(color = cyl) |>
  marginals(x = "histogram", y = "density")

8. Inset plots

inset() puts a smaller plot inside a corner of the main one. It works well for a detail view or a second breakdown of the same data.

main_plot <- glyph(mtcars, x = wt, y = mpg) |> mark_point(color = cyl)
detail_plot <- glyph(mtcars, x = cyl, y = mpg) |> mark_bar()

inset(main_plot, detail_plot, position = "top-right")

9. Moving between groups

animate(by = ..., transition = "morph") shows one group of the data at a time. When the group changes, each mark moves to its new position.

glyph(mtcars, x = wt, y = mpg) |>
  mark_point(size = hp, color = cyl) |>
  animate(by = gear, transition = "morph", duration = 800)

Use the play/pause button to step through the gear groups.

10. Boxplots

mark_boxplot() summarises a numeric variable for each group. The box runs from the first to the third quartile and the line across it is the median. Values beyond the whiskers are drawn as separate points.

glyph(mtcars, x = factor(cyl), y = mpg) |>
  mark_boxplot() |>
  interact(tooltip = TRUE, hover = "outline")

Rest the pointer on a box to read its quartiles.

11. Violins

mark_violin() draws each group’s distribution as a mirrored density curve. Every violin uses the same density scale, so a wide section means many cars with similar values.

glyph(mtcars, x = factor(gear), y = mpg) |>
  mark_violin(color = factor(gear)) |>
  interact(tooltip = TRUE)

12. Sina points

mark_sina() draws one point per row and spreads the points sideways by how common their value is. They fill the same outline a violin would, but each point is still a car, so you can brush across them.

glyph(mtcars, x = factor(cyl), y = mpg) |>
  mark_violin(style = list(opacity = 0.2)) |>
  mark_sina() |>
  interact(tooltip = TRUE, brush = TRUE)

Drag across a group to select the cars in it.

13. Histograms

mark_histogram() counts the rows that fall in each bin of a numeric variable. Mapping colour stacks the counts for each group within a bin.

glyph(mtcars, x = mpg) |>
  mark_histogram(binwidth = 2.5, color = factor(am)) |>
  interact(tooltip = TRUE)

14. Polygons

mark_polygon() draws closed shapes from x/y vertices, one shape per value of group. Here each shape is the convex hull of a cylinder group, found with chull(), and drawn under the cars it encloses.

hulls <- do.call(rbind, lapply(split(mtcars, mtcars$cyl), function(d) {
  d[chull(d$wt, d$mpg), ]
}))

glyph(mtcars, x = wt, y = mpg) |>
  mark_polygon(data = hulls, group = factor(cyl), color = factor(cyl),
               style = list(opacity = 0.2)) |>
  mark_point(color = factor(cyl)) |>
  interact(tooltip = TRUE)