---
title: "groupX"
description: "groupX"
language: "en"
canonical: "https://g2.antv.antgroup.com/en/manual/core/transform/group-x/"
version: "5.4.8"
---

`groupX` is a variant of the `group` function family, specifically designed for grouping discrete `x` channels and aggregating channels according to specified Reducers. It is equivalent to [group](/en/manual/core/transform/group/) with `channels = ['x']`. The usage and configuration options are the same as the group function. Below, we explain the use cases and configuration options specific to the `groupX` 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](/en/manual/core/transform/group/) function.

## Examples

Below, we demonstrate the age distribution of different population groups. We use the `groupX` function to group the data and aggregate the `x` channel, calculating the line length and distribution of `population` for each `state`. Note that the corresponding mark has transform methods available for data transformation.



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

const { Chart } = G2;
const chart = new Chart({
  container: 'container',
});

chart.options({
  type: 'view',
  coordinate: { transform: [{ type: 'transpose' }] },
  data: {
    type: 'fetch',
    value:
      'https://gw.alipayobjects.com/os/bmw-prod/b6f2ff26-b232-447d-a613-0df5e30104a0.csv',
  },
  children: [
    {
      type: 'link',
      transform: [{ type: 'groupX', y: 'min', y1: 'max' }],
      encode: { x: 'state', y: 'population' },
      style: { stroke: '#000' },
      scale: { y: { formatter: '.0%' } },
    },
    {
      type: 'point',
      encode: { x: 'state', y: 'population', shape: 'point', color: 'age' },
      scale: { color: { palette: 'spectral' } },
    },
  ],
});

chart.render();
```



Explanation:

1. In this example, we first define a set of sales data `data`, including region, age, and population;
2. In the above code, the `transform` method uses a `groupX` type data transformation, grouping data by the `x` channel, with 'y' and 'y1' taking the minimum and maximum values respectively;
3. After grouping, the data is aggregated according to the values of the `x` channel, calculating the line length of `population` for each `state`;
4. Finally, the `encode` method maps the grouped data to the chart's `x` and `y` axis for point rendering.