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G2 is a visualization grammar, a data-driven visual language with a high level of usability and scalability. It provides a set of grammars, takes users beyond a limited set of charts to an almost unlimited world of graphical forms. With G2, you can describe the visual appearance and interactive behavior of a visualization just by one statement, and generate web-based views using Canvas or SVG.

• 💯Stable grammar of graphics: enable to draw all kinds of charts by mapping data to graphics.
• 🤩New grammar of interaction: interaction behaviors combined with Trigger and Action mechanisms are used to exploring data.
• 🦍Advanced View module: with the ability to develop customized multi-dimension data analysis graphics.
• 👬Dual-engine rendering: with the ability to switch Canvas and SVG freely.
• 💄Visual components: interaction-oriented, elegant experience.
• 🛡Fully embrace TypeScript: Complete type definition files are provided.

$ npm install @antv/g2

Before drawing we need to prepare a DOM container for G2:

<div id="c1"></div>

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

const data = [
  { genre: 'Sports', sold: 275 },
  { genre: 'Strategy', sold: 115 },
  { genre: 'Action', sold: 120 },
  { genre: 'Shooter', sold: 350 },
  { genre: 'Other', sold: 150 },
];

// Step 1: Create a Chart instance.
const chart = new Chart({
  container: 'c1', // Specify chart container ID
  width: 600, // Specify chart width
  height: 300, // Specify chart height
});

// Step 2: Load the data.
chart.data(data);

// Step 3: Declare the grammar of graphics, draw column chart.
chart.interval().position('genre*sold');

// Step 4: Render chart.
chart.render();

# Install dependencies
$ npm install

# Run test cases
$ npm run test

# Open electron to run test cases and listen to file changes
$ npm run test-live

# Run CI
$ npm run ci

# Run website
$ npm start

• v3.5.x: https://github.com/antvis/G2/tree/v3.5.x
• v4.0.x: https://github.com/antvis/G2/tree/v4.0.x

You can also use G2Plot which is an interactive and responsive charting library based on G2. You can easily make superior statistical plots through a few lines of code.

Please let us know how can we help. Do check out issues for bug reports or suggestions first.

To become a contributor, please follow our contributing guide.

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