pyecharts
pyecharts is a library to generate charts using Echarts. It simply provides the interface 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
pyecharts works on Python2 and Python3. For more information please refer to changelog.md
Jupyter-Notebook
Make sure you hava installed jupyter-notebook enviroment if you want to show your charts on notebook.
How to install it?
$ pip install notebook
pyecharts
You can install it via pip
$ pip install pyecharts
or clone it and install it
$ git clone --recursive https://github.com/chenjiandongx/pyecharts.git
$ cd pyecharts
$ python setup.py install
Basic Usage
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.
Working with pandas & numpy
working with Flask & Django
Flask
Django
Documentation
-
中文文档
Test
$ cd test
$ nosetests --with-coverage --cover-package pyecharts --cover-package test
Author
pyecharts is developed and maintained by chenjiandongx (chenjiandongx@qq.com)
License
pyecharts is released under the MIT License. See LICENSE for more information.