mizani
Scales for Python
Decision gist · record as of 2026-08-14
Yes, if you are building or extending a graphics library that needs production-grade scale and formatting logic. No, if you are a data analyst looking for a direct plotting tool—use plotnine or matplotlib instead. The aging maintenance status and minimal recent activity suggest it is stable but not actively developed; evaluate whether you need active upstream support.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; depends on numpy, scipy, pandas, and tzdata.
- Low friction installation with a pure Python wheel.
- Maintenance is aging—last release was 198 days ago and the repository shows minimal recent activity, though it remains active and not archived.
License · maintenance · safety
permissive license (permissive) — BSD License (permissive) allows commercial and private use with minimal restrictions; you must retain copyright and license notices in distributions.
last release 2026-01-28 (198 days) · last repo commit 2026-01-28 · 68 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,401,046 downloads/mo, #2,634 on PyPI
Alternatives
Verify before relying
pip install mizani
from mizani.scales import scale_continuous
from mizani.formatters import date_format
# Use scales and formatters in your graphics pipeline
scale = scale_continuous()
formatter = date_format('%Y-%m-%d')- Whether mizani is actively used in production graphics libraries or primarily in plotnine/ggplot2-style systems.
- Performance characteristics when handling large datasets or complex scale transformations.
- Compatibility with the latest versions of scipy and pandas beyond what classifiers declare.
What it is and what it does
Mizani is a scales library for Python graphics, inspired by Hadley Wickham's R Scales package. It provides tools to map data values to visual properties—colors, positions, sizes—and to format axes and legends. The package handles continuous and discrete scales, data transformations, and formatting functions that graphics systems need to render plots correctly.
It is typically used as a backend component in visualization libraries rather than directly by end users. The package depends on numpy, scipy, pandas, and tzdata to perform numerical transformations and handle time-zone-aware date formatting. With low install friction and support for Python 3.10+, it integrates cleanly into graphics pipelines that need robust, reusable scale logic.
Use it for
- Format axis labels and legends in a custom graphics system or plotting library.
- Transform data values (log, sqrt, date) for visualization without modifying the original dataset.
- Generate color scales and palettes for multi-dimensional data visualization.
- Handle timezone-aware date formatting in time-series plots.
- Standardize scale behavior across multiple chart types in a graphics framework.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or extending a graphics library that needs production-grade scale and formatting logic.
No, if you are a data analyst looking for a direct plotting tool—use plotnine or matplotlib instead. The aging maintenance status and minimal recent activity suggest it is stable but not actively developed; evaluate whether you need active upstream support.
Install
mizani on PyPI
Before you install
Low friction installation with a pure Python wheel. Maintenance is aging—last release was 198 days ago and the repository shows minimal recent activity, though it remains active and not archived.
Requires Python 3.10 or later; depends on numpy, scipy, pandas, and tzdata.
License in practice
BSD License (permissive) allows commercial and private use with minimal restrictions; you must retain copyright and license notices in distributions.
Quickstart
pip install mizani
from mizani.scales import scale_continuous
from mizani.formatters import date_format
# Use scales and formatters in your graphics pipeline
scale = scale_continuous()
formatter = date_format('%Y-%m-%d')Verify before relying
- Whether mizani is actively used in production graphics libraries or primarily in plotnine/ggplot2-style systems.
- Performance characteristics when handling large datasets or complex scale transformations.
- Compatibility with the latest versions of scipy and pandas beyond what classifiers declare.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesnumpyscipypandastzdata |
| Maintenance | Aging 198 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,401,046 / month, #2,634 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Visualization |
Evidence: mizani-0.14.4-py3-none-any.whl
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