pyecharts is a library to generate charts using Echarts. It simply provides the interface of 28+ kinds of charts between Echarts and Python.
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.
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_literalsYou can install it via pip
$ pip install pyecharts
or clone it and install it
$ git clone --recursive https://github.com/pyecharts/pyecharts.git
$ cd pyecharts
$ pip install -r requirements.txt
$ python setup.py install
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.
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.
pyecharts exposes chart API and template API so that it can work on some common platforms.
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.
With the help of pyecharts API,it is easy to integrate pyecharts to your web projects, such as Flask and Django.
Demo
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.
All map is hosted by the repository echarts-china-cities-js and echarts-countries-js .
All examples is hosted on the repository pyecharts-users-cases .
You should install the libraries in the requirements.txt files.
pip install -r test\requirements.txt
And run with the nose commands.
$ makeflake8 and pylint are used to improve the quality of code.
The project is developed with Travis CI .
pyecharts is released under the MIT License. See LICENSE for more information.