Unfortunately, chart.xkcd only supports a few chart types as a visualization libraray, thus if you have more needs in various kind of chart, pyecharts is better.
The aim of this project is showing others that it's not difficult to write a pyecharts-like project. In fact, pyecharts does have no magic in its source code. As a member of Python cummunity, I sincerely hope more and more developers can use their creativity to make lots of related projects for our favorite Python world.
$ pip(3) install cutecharts
install from source
$ git clone https://github.com/cutecharts/cutecharts.py.git $ cd cutecharts.py $ pip install -r requirements.txt $ python setup.py install
from cutecharts.charts import Line chart = Line("某商场销售情况") chart.set_options( labels=["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"], x_label="I'm xlabel", y_label="I'm ylabel", ) chart.add_series("series-A", [57, 134, 137, 129, 145, 60, 49]) chart.add_series("series-B", [114, 55, 27, 101, 125, 27, 105]) chart.render()
render.html is rendered as below. Isn't that cool！
There are some jupyterlab details that you should pay attention to.
All demo codes are under examples directory.
⛏ Software development
$ pip install -r tests/requirements.txt $ test