Altair

"Altair is a declarative statistical visualization library for Python.

With Altair, you can spend more time understanding your data and its meaning. Altair's API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code.

Altair provides a Python API for building statistical visualizations in a declarative manner. By statistical visualization we mean:

• The data source is a DataFrame that consists of columns of different data types (quantitative, ordinal, nominal and date/time).
• The DataFrame is in a tidy format where the rows correspond to samples and the columns correspond the observed variables.
• The data is mapped to the visual properties (position, color, size, shape, faceting, etc.) using the group-by operation of Pandas and SQL.

The Altair API contains no actual visualization rendering code but instead emits JSON data structures following the Vega-Lite specification. For convenience, Altair can optionally use ipyvega to display client-side renderings seamlessly in the Jupyter notebook.

 The features include:

• Carefully-designed, declarative Python API based on traitlets.
• Auto-generated internal Python API that guarantees visualizations are type-checked and in full conformance with the Vega-Lite specification.
• Auto-generate Altair Python code from a Vega-Lite JSON spec.
• Display visualizations in the live Jupyter Notebook, on GitHub and nbviewer.
• Export visualizations to PNG images, stand-alone HTML pages and the Online Vega-Lite Editor.
• Serialize visualizations as JSON files.
• Explore Altair with 40 example datasets and over 70 examples.

and Altair can be installed using pip or conda."

https://github.com/altair-viz/altair

http://pbpython.com/altair-intro.html

https://dansaber.wordpress.com/2016/10/02/a-dramatic-tour-through-pythons-data-visualization-landscape-including-ggplot-and-altair/