Radial Bar Chart

Introduction to Radial Bar Charts

The Radial Bar Chart (also known as Circular Bar Chart) is an affine transformation of a bar chart from Cartesian coordinate system to polar coordinate system. Its meaning and usage are similar to Bar Charts.

The Radial Bar Chart has a radius feedback effect. Since the radial bar chart uses angle to represent the size of each ring’s value, the angle is the determining factor. So, even if the value of the outer ring (larger radius) is smaller than the inner ring (smaller radius), each outer ring will appear relatively longer than the inner rings. This can cause visual misunderstanding.

Moreover, because our visual system is better at comparing straight lines, the Cartesian coordinate system is more suitable for comparing the numerical values of different categories. Therefore, from a practical perspective, radial bar charts are more of an aesthetic need.

Other Names: Circular Bar Chart

Components of a Radial Bar Chart

Chart Type	Radial Bar Chart
Suitable Data	List: one categorical data field, one continuous data field
Function	Display comparison of categorical data values in an aesthetic way
Data-Visual Mapping	Category field maps to circular position Value field maps to arc length (angle) Colors can distinguish different categories
Suitable Data Volume	No more than 15 data points

A complete radial bar chart contains the following elements:

Rings: Angle represents values
Text: Values and category names

Use Cases of Radial Bar Charts

Suitable Use Cases

Example 1: Displaying categorical data comparison (requires sorting)

The chart below shows the level of American public concern about different areas of US-China issues.

Issue	Attention Rate
Taiwan Relations	0.21
China’s Growing Military Power	0.47
China’s Impact on Global Environment	0.49
US Trade Deficit with China	0.52
China’s Human Rights Policy	0.53
Cyber Attacks from China	0.54
China Taking Away American Jobs	0.60
China Holding US Massive Debt	0.67

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

const chart = new Chart({
  container: 'container',
  theme: 'classic',
  width: 1000,
  height: 700,
});

chart.options({
  type: 'interval',
  data: [
    { question: 'Taiwan Relations', percent: 0.21, odd: 0 },
    { question: "China's Growing Military Power", percent: 0.47, odd: 1 },
    { question: "China's Impact on Global Environment", percent: 0.49, odd: 0 },
    { question: 'US Trade Deficit with China', percent: 0.52, odd: 1 },
    { question: "China's Human Rights Policy", percent: 0.53, odd: 0 },
    { question: 'Cyber Attacks from China', percent: 0.54, odd: 1 },
    { question: 'China Taking Away American Jobs', percent: 0.6, odd: 0 },
    { question: 'China Holding US Massive Debt', percent: 0.67, odd: 1 },
  ],
  coordinate: { type: 'radial', innerRadius: 0.2 },
  encode: {
    x: 'question',
    y: 'percent',
    color: 'odd',
  },
  scale: {
    color: {
      range: ['rgb(211,0,57)', 'rgb(224,74,116)'],
    },
    y: { domain: [0, 1] },
  },
  style: {
    radiusTopLeft: 4,
    radiusTopRight: 4,
  },
  label: {
    text: 'percent',
    position: 'inside',
    style: {
      fontWeight: 'bold',
      fill: 'white',
    },
  },
  axis: {
    x: {
      label: {
        autoRotate: true,
        autoEllipsis: true,
        style: {
          fontSize: 10,
        },
      },
    },
    y: {
      label: false,
      grid: false,
    },
  },
  interaction: [
    {
      type: 'elementHighlight',
      background: true,
    },
  ],
});

chart.render();

Example 2: Displaying country data comparison

The chart below shows the percentage of people in each country who think climate change is a serious problem.

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

const chart = new Chart({
  container: 'container',
  theme: 'classic',
  width: 1200,
  height: 800,
});

chart.options({
  type: 'interval',
  data: [
    { country: 'China', percent: 0.18, condition: 'Special' },
    { country: 'Russia', percent: 0.33, condition: 'Normal' },
    { country: 'UK', percent: 0.41, condition: 'Normal' },
    { country: 'USA', percent: 0.45, condition: 'Normal' },
    { country: 'South Korea', percent: 0.48, condition: 'Normal' },
    { country: 'Canada', percent: 0.51, condition: 'Normal' },
    { country: 'Germany', percent: 0.55, condition: 'Normal' },
    { country: 'Vietnam', percent: 0.69, condition: 'Normal' },
    { country: 'Brazil', percent: 0.86, condition: 'Normal' },
  ],
  coordinate: {
    type: 'radial',
    innerRadius: 0.3,
    startAngle: -Math.PI,
    endAngle: -0.25 * Math.PI,
  },
  encode: {
    x: 'country',
    y: 'percent',
    color: 'condition',
  },
  scale: {
    color: {
      range: ['#2370AE', '#A34265', '#505051'],
    },
  },
  style: {
    radiusTopLeft: 2,
    radiusTopRight: 2,
  },
  label: {
    text: 'percent',
    position: 'inside',
    style: {
      fontWeight: 'bold',
      fill: 'white',
      fontSize: 10,
    },
  },
  axis: {
    x: {
      label: {
        autoRotate: true,
        autoEllipsis: true,
        style: {
          fontSize: 12,
        },
      },
    },
    y: {
      label: false,
      grid: false,
    },
  },
  interaction: [
    {
      type: 'elementHighlight',
      background: true,
    },
  ],
});

chart.render();

Unsuitable Use Cases

Example 1: Unsorted data can be misleading

As mentioned in the introduction, radial bar charts have a radius feedback effect. Visually, rings with larger radius will appear bigger, while those with smaller radius appear smaller. This can cause misuse of radial bar charts. Therefore, we believe that radial bar charts must be sorted when used.

The following shows a comparison between incorrect and correct usage:

Incorrect Example (Unsorted):

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

const chart = new Chart({
  container: 'container',
  theme: 'classic',
  width: 1000,
  height: 700,
});

chart.options({
  type: 'interval',
  data: [
    { country: 'Brazil', percent: 0.86, condition: 'Normal' },
    { country: 'Vietnam', percent: 0.69, condition: 'Normal' },
    { country: 'Germany', percent: 0.55, condition: 'Normal' },
    { country: 'Canada', percent: 0.51, condition: 'Normal' },
    { country: 'South Korea', percent: 0.48, condition: 'Normal' },
    { country: 'USA', percent: 0.45, condition: 'Normal' },
    { country: 'UK', percent: 0.41, condition: 'Normal' },
    { country: 'Russia', percent: 0.33, condition: 'Normal' },
    { country: 'China', percent: 0.18, condition: 'Special' },
  ],
  coordinate: {
    type: 'radial',
    innerRadius: 0.2,
    startAngle: -Math.PI,
    endAngle: -0.25 * Math.PI,
  },
  encode: {
    x: 'country',
    y: 'percent',
    color: 'condition',
  },
  scale: {
    color: {
      range: ['#2370AE', '#A34265', '#505051'],
    },
  },
  style: {
    radiusTopLeft: 2,
    radiusTopRight: 2,
  },
  axis: {
    x: {
      label: {
        autoRotate: true,
        autoEllipsis: true,
        style: {
          fontSize: 10,
        },
      },
    },
    y: {
      label: false,
      grid: false,
    },
  },
  interaction: [
    {
      type: 'elementHighlight',
      background: true,
    },
  ],
});

chart.render();

In the incorrect example above, due to unsorted data, the outer ring Brazil (0.86) will visually appear much larger than the inner ring China (0.18), but this visual difference will be further amplified by the radius effect, causing misleading interpretations.

Extensions of Radial Bar Charts

Grouped Radial Bar Charts

You can use colors or grouping to display multi-dimensional data comparisons:

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

const chart = new Chart({
  container: 'container',
  theme: 'classic',
  width: 1000,
  height: 700,
});

chart.options({
  type: 'interval',
  data: [
    { category: 'Product A', value: 85, quarter: 'Q1' },
    { category: 'Product B', value: 75, quarter: 'Q1' },
    { category: 'Product C', value: 65, quarter: 'Q1' },
    { category: 'Product D', value: 55, quarter: 'Q1' },
    { category: 'Product E', value: 45, quarter: 'Q1' },
  ],
  coordinate: { type: 'radial', innerRadius: 0.2 },
  encode: {
    x: 'category',
    y: 'value',
    color: 'category',
  },
  scale: {
    y: { domain: [0, 100] },
  },
  style: {
    radiusTopLeft: 8,
    radiusTopRight: 8,
  },
  label: {
    text: 'value',
    position: 'inside',
    style: {
      fontWeight: 'bold',
      fill: 'white',
    },
  },
  axis: {
    x: {
      label: {
        autoRotate: true,
        autoEllipsis: true,
        style: {
          fontSize: 10,
        },
      },
    },
    y: {
      label: false,
      grid: false,
    },
  },
  interaction: [
    {
      type: 'elementHighlight',
      background: true,
    },
  ],
});

chart.render();

Comparing Radial Bar Charts to Other Charts

Radial Bar Charts and Bar Charts

Radial Bar Charts: Use polar coordinate system, represent values through arc length, more visually appealing, but have radius feedback effect with lower accuracy in data comparison
Bar Charts: Use Cartesian coordinate system, represent values through rectangle length, more accurate and intuitive for data comparison

Radial Bar Charts, Line Charts, and Pie Charts

Radial Bar Charts: Display absolute values of different categories
Pie Charts: Display proportional relationships of categories within the total
Line Charts: Display trends and changes over time or continuous variables

Radial Bar Charts and Nightingale Charts (Rose Diagrams)

Radial Bar Charts: Focus on single-dimension numerical comparison of categories
Nightingale Charts: Display comprehensive performance across multiple dimensions