Altair is a declarative statistical visualization library for Python, based on Vega-Lite. It provides a high-level API for creating complex visualizations with minimal code. Please include code and sample data in your question.
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 visualization grammar. 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 to 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.