Hi Ton,
We do not support adding text to the X and Y axis corners.
However, by using multilevel labels, we can bring the "DIMENSIONS"
little closer to the X and Y axis corners in the HeatMap component. Please see
the code snippet, screenshot, and sample below.
Code Snippet:
<HeatMapComponent
id="heatmap"
xAxis={{
opposedPosition: true,
multiLevelLabels: [
{
border: { type:
'WithoutBorder' },
textStyle: {
color: 'black',
fontWeight: 'Bold',
},
categories: [{ start:
-1.3, end: 0, text: 'DIMENSIONS' }],
},
]
}}
>
<Inject services={[Legend, Tooltip]} />
</HeatMapComponent>
|
You can find the sample in the below link.
https://stackblitz.com/edit/react-jrano4-sjotgt?file=index.js
![](data:image/png;base64,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)
Meanwhile, we support axis label border properties like "color",
"type", and "width". Other properties are not supported
by the HeatMap component. Please see the following documentation link for the
supported axis label border properties:
https://helpej2.syncfusion.com/react/documentation/api/heatmap/axisLabelBorderModel/
Could you please tell us what properties you
require for your scenario? We will then consider this as a feature request to
improve the border properties for the axis in the HeatMap component.