@develar/echarts
v5.0.2
Published
Apache ECharts is a powerful, interactive charting and data visualization library for browser
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Apache ECharts
Apache ECharts is a free, powerful charting and visualization library offering an easy way of adding 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.
Get Apache ECharts
You may choose one of the following methods:
- Download from Official Website in 中文下载页
- Download from Official Website in English
npm install echarts --save
- CDN: jsDelivr CDN
Docs
Get Help
- GitHub Issues for bug report and feature requests
- Email [email protected] for general questions
- Subscribe mailing list to get updated with the project
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.
npm run dev
# Check 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.
More custom build approaches can be checked in this tutorial: Create Custom Build of ECharts please.
Contribution
If you wish to debug locally or make pull requests, please refer to contributing document.
Resources
Awesome ECharts
https://github.com/ecomfe/awesome-echarts
Extensions
ECharts GL An extension pack of ECharts, which provides 3D plots, globe visualization, and WebGL acceleration.
Extension for Baidu Map 百度地图扩展 An extension provides a wrapper of Baidu Map Service SDK.
vue-echarts ECharts component for Vue.js
echarts-stat Statistics tool for ECharts
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.