README.md

pyecharts

pyecharts is a library to generate charts using Echarts. It simply provides the interface of 28+ kinds of charts between Echarts and Python.

Introduction

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 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.

Installation

Python Compatibility

pyecharts works on Python2.7 and Python3.4+.

pyecharts handles all strings and files with unicode encoding and you MUST use unicode string on Python 2.

#coding=utf-8
from __future__ import unicode_literals

pyecharts

You can install it via pip

$ pip install pyecharts

or clone it and install it

$ git clone https://github.com/pyecharts/pyecharts.git
$ cd pyecharts
$ pip install -r requirements.txt
$ python setup.py install

Please note: since version 0.3.2, NO LONGER pyecharts comes with any map files. Please read next section for more informations.

map extensions

Here is a list of map extensions from pyecharts dev team:

1. World countries include China map and World map: echarts-countries-pypkg (1.9MB)
2. Chinese provinces and regions: echarts-china-provinces-pypkg (730KB)
3. Chinese cities: echarts-china-cities-pypkg (3.8MB)

In order to install them, you can try one of them or all:

$ pip install echarts-countries-pypkg
$ pip install echarts-china-provinces-pypkg
$ pip install echarts-china-cities-pypkg

Basic Usage

Render to Local Html File

from pyecharts import Bar

attr = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
bar = Bar("Bar chart", "precipitation and evaporation one year")
bar.add("precipitation", attr, v1, mark_line=["average"], mark_point=["max", "min"])
bar.add("evaporation", attr, v2, mark_line=["average"], mark_point=["max", "min"])
bar.render()

It will create a file named render.html in the root directory, open file with your borwser.

Export as Images or Pdf

pyecharts-snapshot is a library which renders the output of pyecharts as a png, jpeg, gif image or a pdf file at command line or in your code.

See more detail at the repositoty.

Platform Support

pyecharts exposes chart API and template API so that it can work on some common platforms.

Work on Jupyter Notebook

In the Notebook cell ,you can simply call the instance itself to diplay the chart.

All chart classes in pyecharts implement the _repr_html_ interface about IPython Rich Display .

In the case of online jshost mode,you can also download as some file formats (ipynb/py/html/pdf) and run without jupyter notebook enviromnment.

Integrate With Web Framework

With the help of pyecharts API,it is easy to integrate pyecharts to your web projects, such as Flask and Django.

Demo

Advance Topics

Cusom Template FIles and Layout

pyecharts exposes engine API so that you can use your own template file and integrate with CSS framework.

In addition,pyecharts also ships a lot of jinja2 template functions used in template files.

Custom Map Library

All map is hosted by the repository echarts-china-cities-js and echarts-countries-js .

Documentation

• 中文文档
• English Documentation

Examples

All examples is hosted on the repository pyecharts-users-cases .

Test

Unit Test

You should install the libraries in the requirements.txt files.

pip install -r test\requirements.txt

And run with the nose commands.

$ make

Quality Assurance

flake8 and pylint are used to improve the quality of code.

Continuous Integration

The project is developed with Travis CI and AppVeyor.

Author

License

pyecharts is released under the MIT License. See LICENSE for more information.