---
id: scienceplots
version: "2.2.2"
license: MIT
license_treatment: permissive
maintenance: active
---

# SciencePlots — Format Matplotlib for scientific plotting

License: permissive · Maintenance: active · Downloads: 274.7K/mo

## What it is and what it does

SciencePlots is a Matplotlib style package that registers pre-configured visual themes optimized for scientific publication. When imported, it adds styles like 'science', 'ieee', and 'nature' that you apply via `plt.style.use()` to automatically adjust figure dimensions, fonts, colors, and line weights to match journal or presentation standards.

The package is designed to eliminate manual formatting work when preparing figures for academic papers. It supports cascading styles (combining 'science' with 'ieee' or 'nature' for journal-specific tweaks), includes multiple color cycles (some colorblind-safe), and provides localized support for CJK fonts and other languages. The main constraint is that LaTeX must be installed separately for full functionality, and the import statement must appear before any style application.

Use it for:

- Format plots for IEEE papers by combining 'science' and 'ieee' styles to match column width and font requirements
- Prepare figures for Nature or other journals using journal-specific style combinations
- Create consistent, publication-ready plots in Jupyter notebooks with the 'notebook' style variant
- Apply colorblind-safe color cycles to ensure accessibility across different audiences
- Generate multilingual scientific figures using CJK font support for Chinese, Japanese, or Korean text

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a collection of Matplotlib style sheets designed to format scientific figures for papers, presentations, and theses with publication-ready appearance.

Yes. SciencePlots is worth installing if you regularly produce scientific figures for publication. It eliminates repetitive manual formatting, is actively maintained, has no security vulnerabilities, carries a permissive license, and depends only on matplotlib. The only gotcha is the LaTeX requirement, which is standard in academic workflows anyway.

## Install

pip install scienceplots
uv add scienceplots
poetry add scienceplots

## Installing SciencePlots

Before you install: Low friction install with a single runtime dependency on matplotlib. The project is actively maintained with recent releases and high community engagement (9127 GitHub stars), indicating stable, well-supported code.

License in practice: MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both academic and commercial projects.

Quickstart:

pip install scienceplots

import matplotlib.pyplot as plt
import scienceplots

plt.style.use('science')
plt.plot([1, 2, 3])
plt.show()

LaTeX must be installed separately on your system for full style functionality.

Verify before relying:

- Whether LaTeX installation is truly mandatory or only needed for certain styles
- Performance impact of importing scienceplots on matplotlib initialization
- Compatibility with specific matplotlib versions beyond the general Python 3.8+ requirement

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 274.7K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

matplotlib scientific plotting styles, publication-ready figure formatting, scientific paper figure templates, matplotlib journal styles, academic figure styling, matplotlib-styling, academic-publishing, figure-formatting

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