ggplot

What it is and what it does

ggplot is a Python port of the R ggplot2 library, implementing the grammar of graphics paradigm for building plots. Rather than calling functions to draw specific chart types, you compose plots by layering components: a data source, aesthetic mappings (which columns map to which visual properties), geometric layers (points, lines, densities), scales, and facets. The library was designed to bring R's declarative plotting approach to Python, though it does not aim for feature-parity with ggplot2.

The package has been abandoned since its latest release on 2016-09-29 and receives no maintenance. While it has no runtime dependencies and installs cleanly, its age means it was built for older Python versions (2.7 and 3.3 era) and may not work reliably with modern environments or current data science libraries. The repository is archived with a last commit on 2023-01-21.

Use it for:

• Build multi-layered statistical plots by composing data, aesthetics, and geometric layers in a declarative style.
• Create faceted plots that split data across multiple subplots based on categorical variables.
• Apply consistent color scales and themes across multiple plot types using a unified grammar.
• Prototype exploratory data visualizations when you prefer a grammar-of-graphics approach over imperative plotting.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

ggplot is a Python implementation of the grammar of graphics that lets you build layered statistical graphics by combining data, aesthetic mappings, and geometric layers.

No. The package is abandoned (latest release 2016-09-29, repository archived) and almost certainly incompatible with modern Python and libraries. While it has no dependencies and a permissive license, the lack of maintenance makes it unsuitable for new projects. Consider alternatives or test thoroughly before use.

Install

ggplot on PyPI

pip install ggplot

uv add ggplot

poetry add ggplot

Installing ggplot

Before you install

Installation is straightforward with no runtime dependencies. However, the package is abandoned—the repository is archived and the last release was in 2016. No maintenance or updates are forthcoming.

License in practice

ggplot is licensed under BSD (permissive), which allows commercial and private use with minimal restrictions. This poses no licensing barrier to adoption.

Quickstart

pip install ggplot

from ggplot import ggplot, aes, geom_density, scale_color_brewer, facet_wrap
ggplot(diamonds, aes(x='price', color='clarity')) + \
    geom_density() + \
    scale_color_brewer(type='div', palette=7) + \
    facet_wrap('cut')

The package was last updated in 2016 and may not be compatible with modern Python or dependency versions; testing on your target environment is essential.

Verify before relying

• Whether the package works with current Python versions or modern data science libraries.
• What specific data structures or formats are required for the input data argument.
• Whether all ggplot2 features are implemented or which major features remain unported.

Package facts

Evidence: ggplot-0.11.5-py2.py3-none-any.whl

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