G2

Overview

The boxplot mark is used to draw boxplots (also known as box-and-whisker plots), which are statistical charts used to display the distribution of a dataset. Boxplots typically contain the following key statistical values:

Minimum: The smallest value in the dataset (excluding outliers)
Lower Quartile (Q1): The value at the 25th percentile of the dataset
Median (Q2): The value at the 50th percentile of the dataset
Upper Quartile (Q3): The value at the 75th percentile of the dataset
Maximum: The largest value in the dataset (excluding outliers)
Outliers: Data points that fall outside the normal range

Both boxplot and box marks can be used to draw boxplots, but they have the following differences:

boxplot is a high-level mark with built-in data grouping and statistical aggregation functionality
box is an atomic mark that requires developers to manually specify data for the 5 points

Therefore, boxplot is more suitable for frontend data exploration and analysis, while box is more suitable for visualization after backend computation and statistics on large datasets.

Configuration

Property	Description	Type	Default Value	Required
encode	Configure visual channels for the `boxplot` mark, including `x`, `y`, `color`, `shape`, etc.	encode	-	✓
style	Configure the graphic style of the `boxplot` mark	style	-
point	Whether to show outliers	`boolean`	`true`

encode

Configure visual channels for the boxplot mark.

Property	Description	Type	Default Value	Required
x	Bind the `x` property channel for the `boxplot` mark, usually a categorical field	encode	-	✓
y	Bind the `y` property channel for the `boxplot` mark, usually a numeric field used to calculate boxplot statistical values	encode	-	✓
color	Bind the `color` property channel for the `boxplot` mark, used to distinguish boxplots of different categories	encode	-
shape	Bind the `shape` property channel for the `boxplot` mark, available values are `box`, `violin`	`'box'` \| `'violin'`	`'box'`
series	Bind the `series` property channel for the `boxplot` mark, used for grouped display of boxplots	encode	-

style

Configure the graphic style of the boxplot mark. The boxplot consists of two parts: the box and the outlier points. Therefore, style configuration is also divided into two parts, prefixed with box and point respectively.

Box Style

Property	Description	Type	Default Value
boxFill	Fill color of the box	`string` \| `(datum, index, data, column) => string`	-
boxFillOpacity	Fill opacity of the box	`number` \| `(datum, index, data, column) => number`	`0.95`
boxStroke	Stroke color of the box	`string` \| `(datum, index, data, column) => string`	`#000`
boxLineWidth	Width of the box stroke	`number` \| `(datum, index, data, column) => number`	`1`
boxLineDash	Dash pattern for box stroke, first value is length of each dash segment, second is gap between dashes	`[number,number]` \| `(datum, index, data, column) => [number, number]`	-
boxLineOpacity	Opacity of the box stroke	`number` \| `(datum, index, data, column) => number`	-
boxOpacity	Overall opacity of the box	`number` \| `(datum, index, data, column) => number`	-
boxShadowColor	Shadow color of the box	`string` \| `(datum, index, data, column) => string`	-
boxShadowBlur	Gaussian blur coefficient for the box shadow	`number` \| `(datum, index, data, column) => number`	-
boxShadowOffsetX	Horizontal distance of shadow from box	`number` \| `(datum, index, data, column) => number`	-
boxShadowOffsetY	Vertical distance of shadow from box	`number` \| `(datum, index, data, column) => number`	-
boxCursor	Mouse cursor style. Same as CSS cursor style	`string` \| `(datum, index, data, column) => string`	`'default'`

Outlier Point Style

Property	Description	Type	Default Value
pointFill	Fill color of outlier points	`string` \| `(datum, index, data, column) => string`	-
pointFillOpacity	Fill opacity of outlier points	`number` \| `(datum, index, data, column) => number`	-
pointStroke	Stroke color of outlier points	`string` \| `(datum, index, data, column) => string`	-
pointLineWidth	Width of outlier point stroke	`number` \| `(datum, index, data, column) => number`	-
pointLineDash	Dash pattern for outlier point stroke	`[number,number]` \| `(datum, index, data, column) => [number, number]`	-
pointStrokeOpacity	Stroke opacity of outlier points	`number` \| `(datum, index, data, column) => number`	-
pointOpacity	Overall opacity of outlier points	`number` \| `(datum, index, data, column) => number`	-
pointShadowColor	Shadow color of outlier points	`string` \| `(datum, index, data, column) => string`	-
pointShadowBlur	Gaussian blur coefficient for point shadow	`number` \| `(datum, index, data, column) => number`	-
pointShadowOffsetX	Horizontal distance of shadow from point	`number` \| `(datum, index, data, column) => number`	-
pointShadowOffsetY	Vertical distance of shadow from point	`number` \| `(datum, index, data, column) => number`	-
pointCursor	Mouse cursor style. Same as CSS cursor style	`string` \| `(datum, index, data, column) => string`	`'default'`

Examples

Basic Boxplot

Use the boxplot mark to quickly create a boxplot with automatic calculation of statistical values.

import { Chart } from '@antv/g2';

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

chart.options({
  type: 'boxplot',
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/morley.json',
  },
  encode: {
    x: 'Expt',
    y: 'Speed',
  },
  style: {
    boxFill: '#aaa',
    pointStroke: '#000',
  },
});

chart.render();

Boxplot Without Outliers

Set point: false to hide outliers and show only the box portion.

import { Chart } from '@antv/g2';

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

chart.options({
  type: 'boxplot',
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/morley.json',
  },
  encode: {
    x: 'Expt',
    y: 'Speed',
  },
  style: {
    point: false,
  },
});

chart.render();

Grouped Boxplot

Use the color and series channels to create grouped boxplots.

import { Chart } from '@antv/g2';

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

chart.options({
  type: 'boxplot',
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/penguins.json',
  },
  encode: {
    x: 'species',
    y: 'flipper_length_mm',
    color: 'sex',
    series: 'sex',
  },
});

chart.render();

Horizontal Boxplot

Create a horizontal boxplot by transposing the coordinate system.

import { Chart } from '@antv/g2';

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

chart.options({
  type: 'boxplot',
  coordinate: { transform: [{ type: 'transpose' }] },
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/morley.json',
    transform: [{ type: 'filter', callback: (d) => d.Expt === 1 }],
  },
  encode: {
    y: 'Speed',
  },
  style: {
    boxFill: '#aaa',
    pointStroke: '#000',
  },
});

chart.render();

Violin Plot

Create a violin-shaped boxplot by setting shape: 'violin'.

import { Chart } from '@antv/g2';

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

chart.options({
  type: 'boxplot',
  data: {
    type: 'fetch',
    value: 'https://assets.antv.antgroup.com/g2/penguins.json',
  },
  encode: {
    x: 'species',
    y: 'flipper_length_mm',
    color: 'species',
    shape: 'violin',
  },
  style: {
    opacity: 0.5,
    strokeOpacity: 0.5,
    point: false,
  },
});

chart.render();

FAQ

How to draw boxplots with large datasets?

When dealing with large datasets, you can compute outliers and quartile points on the server side, then use the box mark to draw boxplots. In this case, using the box mark is more efficient than the boxplot mark because the box mark doesn't require statistical calculations on the frontend.

For detailed usage, please refer to the box mark documentation.