@data-ui/radial-chart
demo at
williaster.github.io/data-ui
Overview
This package exports declarative react <RadialChart />
s implemented with
@vx which can be used to render both donut and pie
charts depending on props. As demonstrated in the demo, in combination with
@vx/legend and
@vx/scale
these can be used to create re-usable radial charts.
Usage
See the demo at
williaster.github.io/data-ui for
more example outputs.
import { scaleOrdinal } from '@vx/scale';
import { LegendOrdinal } from '@vx/legend';
import { color as colors } from '@data-ui/theme';
import { RadialChart, ArcSeries, ArcLabel } from '@data-ui/radial-chart';
const colorScale = scaleOrdinal({ range: colors.categories });
const data = [{ label: 'a', value: 200 }, { label: 'c', value: 150 }, { label: 'c', value: 21 }];
export default () => (
<div style={{ display: 'flex', alignItems: 'center' }}>
<RadialChart
ariaLabel="This is a radial-chart chart of..."
width={width}
height={height}
margin={{ top, right, bottom, left }}
renderTooltip={({ event, datum, data, fraction }) => (
<div>
<strong>{datum.label}</strong>
{datum.value} ({(fraction * 100).toFixed(2)}%)
</div>
)}
>
<ArcSeries
data={data}
pieValue={d => d.value}
fill={arc => colorScale(arc.data.label)}
stroke="#fff"
strokeWidth={1}
label{arc => `${(arc.data.value).toFixed(1)}%`}
labelComponent={<ArcLabel />}
innerRadius={radius => 0.35 * radius}
outerRadius={radius => 0.6 * radius}
labelRadius={radius => 0.75 * radius}
/>
</RadialChart>
<LegendOrdinal
direction="column"
scale={colorScale}
shape="rect"
fill={({ datum }) => colorScale(datum)}
labelFormat={label => label}
/>
</div>
);
Tooltips
The easiest way to use tooltips out of the box is by passing a renderTooltip
function to
<RadialChart />
. This function takes an object with the shape { event, datum, data, fraction }
as input and should return the inner contents of the tooltip (not the tooltip container!) as shown
above. If this function returns a falsy
value, a tooltip will not be rendered.
Under the covers this will wrap the <RadialChart />
component in the exported <WithTooltip />
HOC, which wraps the svg
in a <div />
and handles the positioning and rendering of an HTML-based
tooltip with the contents returned by renderTooltip()
. This tooltip is aware of the bounds of its
container and should position itself "smartly".
If you'd like more customizability over tooltip rendering you can do either of the following:
-
Roll your own tooltip positioning logic and pass onMouseMove
and onMouseLeave
functions to
RadialChart
. These functions are passed to the <ArcSeries />
children and are called with the
signature onMouseMove({ datum, event })
and onMouseLeave()
upon appropriate trigger.
-
Wrap <RadialChart />
in <WithTooltip />
yourself, which accepts props for additional
customization:
Name | Type | Default | Description |
---|
children | PropTypes.func or PropTypes.object | - | Child function (to call) or element (to clone) with onMouseMove, onMouseLeave, and tooltipData props/keys |
className | PropTypes.string | - | Class name to add to the <div> container wrapper |
renderTooltip | PropTypes.func.isRequired | - | Renders the contents of the tooltip, signature of ({ event, data, datum, fraction }) => node . If this function returns a falsy value, a tooltip will not be rendered. |
styles | PropTypes.object | {} | Styles to add to the <div> container wrapper |
TooltipComponent | PropTypes.func or PropTypes.object | @vx 's TooltipWithBounds | Component (not instance) to use as the tooltip container component. It is passed top and left numbers for positioning |
tooltipProps | PropTypes.object | - | Props that are passed to TooltipComponent |
tooltipTimeout | PropTypes.number | 200 | Timeout in ms for the tooltip to hide upon calling onMouseLeave |
Note that currently this is implemented with @vx/tooltips
's withTooltip
HOC, which adds an
additional div wrapper.
Roadmap
- more types of radial series
- animations / transitions
NOTE ‼️
Although pie 🍰 and donut 🍩 charts are frequently encountered, they are not the most effective
visualization for conveying quantitative information. With that caveat, when used well they can
effectively give an overview of population makeup which is an entirely reasonable use of these
charts. We don't recommend using >7 slices for user readability.