Plotnine

Plotnine is a data visualization library for Python that implements the grammar of graphics, a declarative approach to building statistical graphics originally developed for R's ggplot2. It enables users to construct plots by mapping data variables to visual properties (aesthetics) and layering geometric and statistical components.

The library emphasizes core building blocks such as aesthetics mappings (aes), geometric objects (geoms), statistical transformations (stats), scales, coordinates, facets, and themes. Typical plots are built by providing a data frame (usually a pandas DataFrame) and adding layers like geom_point, geom_line, or geom_bar, optionally with statistical transformations and position adjustments. Faceting allows splitting data into subplots, and themes control the visual style, including colors, fonts, and axis details.

Plotnine renders plots via matplotlib, allowing integration with the Python data ecosystem and interactive environments such as Jupyter notebooks. It supports a broad range of geoms and stats, and can interoperate with pandas, numpy, and other visualization tools within data analysis workflows.

As an open-source project, plotnine is developed by contributors and hosted on public repositories. It provides a Pythonic alternative for users familiar with ggplot2 and is used in education, data analysis, and reproducible research to produce publication-quality graphics with a consistent, grammar-driven approach.