G2

groupY is a variant of the group function family, specifically designed for grouping discrete y channels and aggregating channels according to specified Reducers. It is equivalent to group with channels = ['y']. The usage and configuration options are the same as the group function. Below, we explain the use cases and configuration options specific to the groupY function.

Options

Property	Description	Type	Default
[channel]	Aggregation method for channel data output to specific mark	Reducer

For detailed information about Reducer, please refer to the configuration options of the group function.

Examples

For example, in corresponding marks, you can use the transform method to apply data transformations. We can use groupY to group and aggregate data. In the example below, we will group the y channel and calculate the minimum and maximum values for each group.

import * as G2 from '@antv/g2';

const { Chart } = G2;
const chart = new Chart({
  container: 'container',
});
chart.options({
  type: 'view',
  height: 180,
  paddingLeft: 80,
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/penguins.json',
    transform: [
      {
        type: 'map',
        callback: (d) => ({
          ...d,
          body_mass_g: +d.body_mass_g,
        }),
      },
    ],
  },
  children: [
    {
      type: 'point',
      encode: { x: 'body_mass_g', y: 'species' },
      style: { stroke: '#000' },
    },
    {
      type: 'link',
      encode: { x: 'body_mass_g', y: 'species' },
      transform: [{ type: 'groupY', x: 'min', x1: 'max' }],
      style: { stroke: '#000' },
    },
    {
      type: 'point',
      encode: { y: 'species', x: 'body_mass_g', shape: 'line', size: 12 },
      transform: [{ type: 'groupY', x: 'median' }],
      style: { stroke: 'red' },
    },
  ],
});

chart.render();

Explanation:

1. In this example, we first define a set of penguin data data, containing penguin body mass and species;
2. In the code above, the transform method uses a groupY type data transformation to group data by the y channel;
3. After grouping, the data is aggregated according to the values of the y channel, calculating the minimum and maximum values of body_mass_g for each species;
4. Finally, through the encode method, the grouped data is mapped to the chart’s x and y axis for rendering.

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