### Strip Plot
The following example uses tick marks to show the distribution of sepal width in the Iris dataset. By adding a y field (categorical data), a strip plot is created to show the distribution of sepal width across different species.
```rust
{{#include ../../../examples/strip.rs}}
```
<img src="../images/strip.svg" width="500">
When there only one category or color encoding is absent, it degeneates to a "rug" of lines along the bottom.
You can precisely control the visual weight of the ticks using configure_tick. This is useful for balancing the "density" look of the chart.
```rust
let df = load_dataset("iris")?;
let chart = Chart::build(&df)?
.mark_tick()?
.encode((
x("sepal_width"),
y("species"),
color("species")
))?
.configure_tick(|m| {
m.with_thickness(2.0) // Sets the tick width
.with_band_size(10.0) // Sets the height of the tick
.with_color("blue")
});
chart.save("custom_tick.svg")?;
```
### Significance and Usage
- Significance: Unlike a `point`, a `tick` emphasizes positional density. Because of its linear shape, overlapping ticks create a "barcode" effect that intuitively reveals where data points are most concentrated.
- Common Use Cases:
1. Rug Plots: Often placed at the edges of scatter plots or histograms to show marginal distributions.
2. Strip Plots: Used as an alternative to box plots when the dataset is small to medium-sized, allowing every individual data point to be seen.
3. High-Performance Rendering: In Rust-based engines like `charton`, rendering simple quads (ticks) is extremely efficient for visualizing millions of data points compared to complex shapes.