
Chart | Data shape | Use when |
|---|---|---|
Matrix value triples. | Use it for SRE and operations dashboards. | |
Date/value pairs. | Use it for engineering operations. | |
Matrix value triples. | Use it for relationship strength matrices. | |
Date/value pairs. | Use it for reliability and support reporting. | |
Dense matrix value triples. | Use it for activity grids with many columns. | |
Date/value pairs. | Use it for contribution and activity patterns. | |
Matrix value triples. | Use it for capacity and utilization panels. | |
Date/value pairs. | Use it for habit and retention surfaces. | |
Matrix value triples. | Use it for risk and priority matrices. | |
Matrix value triples. | Use it for dashboards with limited space. | |
HeatmapSeries plus VisualMap. | Use it when color needs a visible numeric range. | |
x index, y index, value triples. | Use it for operational intensity matrices. |
use fission::prelude::*;
use fission::charts::{Axis, Chart, LineSeries};
pub struct HeatmapAndCalendarChart;
impl From<HeatmapAndCalendarChart> for Widget {
fn from(_: HeatmapAndCalendarChart) -> Widget {
Chart::new()
.title("Heatmap and calendar")
.x_axis(Axis::category(vec!["A", "B", "C"]))
.y_axis(Axis::value())
.series(vec![LineSeries::new("Series").data(vec![1.0, 2.0, 3.0]).into()])
.into()
}
}
Area | What to decide | How to verify |
|---|---|---|
Data shape | Keep source rows in typed Rust structs, then map them into the series type shown in the example. | Unit test the mapping separately from rendering. |
Options | Choose axes, legends, labels, animation, and interaction based on the user's task. | Add a screenshot test when changing visual behavior. |
Accessibility | Provide a clear title and adjacent summary text for important trends or outliers. | Inspect the generated semantics and make sure the chart is understandable without color alone. |
Failure handling | Render an empty, loading, or error state before constructing the chart if data is unavailable. | Test empty data, partial data, and failed fetches. |
Performance | Prefer summarized or windowed data for very large datasets; keep full raw history in the data layer. | Profile frame time and interaction latency with representative data volumes. |