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_literals

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.

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)
4. Chinese counties: echarts-china-counties-pypkg (4.1MB)
5. Custom Chinese regions: echarts-china-misc-pypkg (148KB)
6. United Kingdom map: echarts-united-kingdom-pypkg (1MB)

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

$ pip install echarts-countries-pypkg
$ pip install echarts-china-provinces-pypkg
$ pip install echarts-china-cities-pypkg
$ pip install echarts-china-counties-pypkg
$ pip install echarts-china-misc-pypkg
$ pip install echarts-united-kingdom-pypkg

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 command line utility and a library extension which renders the output of pyecharts as a svg, png, jpeg, gif image or a pdf file.

After you will have installed pyecharts-snapshot, you can modify previous example file slightly and get png output directly:

bar.render(path="render.png")

So please see installation instruction and other usage at that repository.

pyecharts exposes chart API and template API so that it can work on other python frameworks.

In the Notebook cell, you can simply pass on chart instance itself to Jupyter, which will diplay the chart. Please note render_notebook function has been removed.

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.

Since pyecharts 0.5.5+, nteract is supported. Once the following two lines should added to your notebook, you could use pyecharts in nteract in the same way as in jupyter notebook.

from pyecharts import enable_nteract

enable_nteract()

However, when rendering output as image, the instructions are the same as jupyter notebook. Only default html(including js) output should call enable_nteract().

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 custom CSS.

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

All maps are developed and maintained by echarts-maps github organisation.

• 中文文档
• English Documentation

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.

$ make

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

The project is developed with Travis CI and AppVeyor.

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