Krisk bring Echarts to Python Data Science Ecosystem, and helpful tools for high level statistical interactive visualization.
- Python 3.5 (Python 2.7 should be supported, haven't test it yet)
- Jupyter Notebook 4.2.x
- Pandas 0.18.x
- Echarts 3.2.1 (built-in)
pip install jupyter pandas krisk jupyter nbextension install --py krisk --sys-prefix jupyter nbextension enable --py krisk --sys-prefix
- Themes and Colors
- Legend, Title, and Toolbox
- Resync Data and Reproducible Charts
- Declarative Visualization
- Waterfall and Barline Chart
- Tidy Plot: Time Series and Other Custom Data Manipulation
What It Does
- Chart Integration with Jupyter Notebook, widgets, and Dashboard.
- Statistical interactive visualization
- Ability backed by Echarts (Toolbox, Transition, Tooltip, etc.)
What It Doesn't Do
Krisk won't implement all features of Echarts. For more advanced usage, Krisk users can use JSON
Only basic charts are supported for explanation visualization. The plan will support:
- More complex line, bar, scatter, and histogram.
- Geoscatter plot
- Time Series
Of course, contributions are welcome to support all chart types and advanced features.
Motivation for Another Visualization Library
Krisk is also act as tool to support reproducible chart by utilizing pandas DataFrame as data input.
How to Contribute
To contribute and unit tests your changes, please do the following,
- Fork this repository
- Clone this repo and do unit test,
pip install coverage pytest git clone https://github.com/your-username/krisk.git cd krisk coverage run --source krisk -m py.test