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‎.nojekyll

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‎CNAME

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pyecharts.org

‎README.md

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# Website
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pyecharts.org website source

‎_coverpage.md

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![logo](https://user-images.githubusercontent.com/19553554/34926690-2bac6002-f9ec-11e7-8b30-aceef8a814e3.png)
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# pyecharts
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> A Python Echarts Plotting Library.
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* Chart: 30+ kinds of charts
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* Map: 300+ Chinese cities / 200+ countries and regions
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* Platforms: Pure Python / Jupyter Notebook / Web Framework
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[GitHub](https://github.com/pyecharts/pyecharts/)
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[Get Started](zh-cn/prepare)

‎_navbar.md

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- [主页](/)
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- 生态系统
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- [pyecharts](https://github.com/pyecharts/pyecharts)
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- [pyecharts-javascripthon](https://github.com/pyecharts/pyecharts-javascripthon)
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- [pyecharts-snapshot](https://github.com/pyecharts/pyecharts-snapshot)
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- [jupyter-echarts-pypkg](https://github.com/pyecharts/jupyter-echarts-pypkg)
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- [团队](zh-cn/team)
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- [捐赠](zh-cn/donate)
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- Language
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- [中文](/zh-cn/)
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- [English](/en-us/)

‎_sidebar.md

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pyecharts 是一个用于生成 Echarts 图表的类库。Echarts 是百度开源的一个数据可视化 JS 库。用 Echarts 生成的图可视化效果非常棒，pyecharts 是为了与 Python 进行对接，方便在 Python 中直接使用数据生成图。
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- 基本使用
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- [渲染图表](zh-cn/prepare)
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- [图表配置](zh-cn/charts)
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- 高级话题
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- [图表 API](zh-cn/api)
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- [自定义地图](zh-cn/customize_map)
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- [回调函数和事件处理](zh-cn/advanced)
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- [语言翻译扩展](zh-cn/translator)
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- 平台支持
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- [Jupyter Notebook](zh-cn/jupyter_notebook)
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- [Flask](zh-cn/flask)
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- [Django](zh-cn/django)
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- [web 框架整合](zh-cn/web_integration)
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- 其他资源
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- [地理地图数据](zh-cn/datasets)
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- 项目发布
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- [版本日志](zh-cn/changelog)
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- [发布日志](zh-cn/release-note/)
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- 项目开发
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- [技术文档](zh-cn/technical)
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- [开发团队](zh-cn/team)
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- [赞助者名单](zh-cn/donors)
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- [FAQ](zh-cn/faq)
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‎class-relationship-diagram.uml

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@startuml
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Base <|-- Chart
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Base <|-- Timeline
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Base <|-- Grid
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Base <|-- Overlap
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Chart <|-- Bar
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Chart <|-- Boxplot
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Chart <|-- EffectScatter
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Chart <|-- Funnel
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Chart <|-- Geo
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Chart <|-- Graph
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Chart <|-- HeapMap
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Chart <|-- KLine
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Chart <|-- Line
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Chart <|-- Liquid
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Chart <|-- Map
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Chart <|-- Parallel
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Chart <|-- Pie
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Chart <|-- Polar
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Chart <|-- Radar
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Chart <|-- Sankey
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Chart <|-- Scatter
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Chart <|-- ThemeRiver
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Chart <|-- TreeMap
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Chart <|-- WorldCould
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Chart <|-- Chart3D
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Chart3D <|-- Bar3D
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Chart3D <|-- Line3D
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Chart3D <|-- Scatter3D
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Geo <|-- GeoLines
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@enduml

‎en-us/README.md

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# pyecharts Document
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[![Build Status](https://travis-ci.org/pyecharts/pyecharts.svg?branch=master)](https://travis-ci.org/pyecharts/pyecharts) [![Build status](https://ci.appveyor.com/api/projects/status/81cbsfjpfryv1cl8?svg=true)](https://ci.appveyor.com/project/chenjiandongx/pyecharts) [![codecov](https://codecov.io/gh/pyecharts/pyecharts/branch/master/graph/badge.svg)](https://codecov.io/gh/pyecharts/pyecharts) [![PyPI version](https://badge.fury.io/py/pyecharts.svg)](https://badge.fury.io/py/pyecharts) [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
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[Echarts](https://github.com/ecomfe/echarts) is an open source library from Baidu for data visualization in javascript. It has awesome demo pages so I started to look out for an interface library so that I could use it in Python. I ended up with [echarts-python](https://github.com/yufeiminds/echarts-python) on github but it lacks of documentation and was not updated for a while. Just like many other Python projects, I started my own project, pyecharts, referencing echarts-python and another library [pygal](https://github.com/Kozea/pygal).
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**Basic Usage**
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[Get started](en-us/prepare) | [Chart Configuration](en-us/charts_configure) | [Basic Charts](en-us/charts_base) | [Custom Charts](en-us/charts_custom) | [Chart Style](en-us/charts_style) | [Data Analysis and Import](en-us/data_import)
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**Advanced Topics**
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[Chart API](en-us/api) | [Themes Customization](en-us/themes) | [Map Customization](en-us/customize_map) | [Callback Function & Event Handler](en-us/advanced) | [Language Translator Extension](en-us/translator)
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**Platform Support**
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[Jupyter Notebook](en-us/jupyter_notebook) | [Flask](en-us/flask) | [Django](en-us/django) | [Web Integration](en-us/web_integration)
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**Other Resources**
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[Demo Projects](https://github.com/pyecharts/pyecharts-users-cases) | [Geography & Map](en-us/datasets)
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**Project Release**
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[Changelog](zh-cn/changelog) | [Release Note](zh-cn/release-note)
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**Project Development**
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[Developer Guide](en-us/for_pyechart_developer) | [Technical Documents](en-us/technical) | [Team](en-us/team) | [Donors List](zh-cn/donors) | [FAQ](en-us/faq)

‎en-us/_sidebar.md

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pyecharts is a class library for generating ECharts charts. ECharts is a data visualization JS library of Baidu Open Source. The graphics generated with ECharts are very visual, and pyecharts is designed to interface with Python, making it easy to use data generation diagrams directly in Python.
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- Basic Usage
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- [Chart Render](en-us/prepare)
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- [Chart Configuration](en-us/charts_configure)
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- [Chart Basic](en-us/charts_base)
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- [Chart Customization](en-us/charts_custom)
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- [Chart Style](en-us/charts_style)
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- [Data Analysis and Import](en-us/data_import)
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- Advance Topics
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- [Chart API](en-us/api)
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- [Themes Customization](en-us/themes)
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- [Map Customization](en-us/customize_map)
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- [Callback Function & Event Handler](en-us/advanced)
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- [Language Translator Extension](en-us/translator)
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- Platform Support
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- [Jupyter Notebook](en-us/jupyter_notebook)
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- [Flask](en-us/flask)
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- [Django](en-us/django)
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- [Web Integration](en-us/web_integration)
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- Other Resources
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- [Demo Projects](https://github.com/pyecharts/pyecharts-users-cases)
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- [Geography & Map](en-us/datasets)
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- Project Release
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- [Changelog](zh-cn/changelog)
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- [Release Note](zh-cn/release-note/)
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- Project Development
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- [Developer Guide](en-us/for_pyechart_developer)
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- [Technical Documents](en-us/technical)
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- [Team](en-us/team)
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- [Donors List](zh-cn/donors)
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- [FAQ](en-us/faq)

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