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@xdatav/echarts

v5.4.3-ffa.1

Published

Apache ECharts is a powerful, interactive charting and data visualization library for browser

Downloads

7

Readme

Apache ECharts

Apache ECharts is a free, powerful charting and visualization library offering easy ways to add intuitive, interactive, and highly customizable charts to your commercial products. It is written in pure JavaScript and based on zrender, which is a whole new lightweight canvas library.

中文官网 | ENGLISH HOMEPAGE

License Latest npm release NPM downloads Contributors

Build Status

Get Apache ECharts

You may choose one of the following methods:

Extra Features

1. Minimize echarts size

By ignoring *.map files in .npmignore, the size of echarts is reduced from the official 41.7M to 19M (Unpack Size).

1. Enable brush back for data zoom back

Just set enableBrushBack to true in dataZoom toolbox.

// ...
toolbox: {
    feature: {
        dataZoom: {
            enableBrushBack: true,
        }
    }
}
// ...

Docs

Get Help

Build

Build echarts source code:

Execute the instructions in the root directory of the echarts: (Node.js is required)

# Install the dependencies from NPM:
npm install

# Rebuild source code immediately in watch mode when changing the source code.
# It opens the `./test` directory, and you may open `-cases.html` to get the list
# of all test cases.
# If you wish to create a test case, run `npm run mktest:help` to learn more.
npm run dev

# Check the correctness of TypeScript code.
npm run checktype

# If intending to build and get all types of the "production" files:
npm run release

Then the "production" files are generated in the dist directory.

Contribution

Please refer to the contributing document if you wish to debug locally or make pull requests.

Resources

Awesome ECharts

https://github.com/ecomfe/awesome-echarts

Extensions

License

ECharts is available under the Apache License V2.

Code of Conduct

Please refer to Apache Code of Conduct.

Paper

Deqing Li, Honghui Mei, Yi Shen, Shuang Su, Wenli Zhang, Junting Wang, Ming Zu, Wei Chen. ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. Visual Informatics, 2018.