---
id: lovelyplots
version: "1.0.2"
license: MIT
license_treatment: permissive
maintenance: dormant
---

# lovelyplots — Format Matplotlib Plots for thesis, scientific papers and reports.

License: permissive · Maintenance: dormant · Downloads: 522.7K/mo

## What it is and what it does

LovelyPlots is a collection of matplotlib style sheets designed to produce publication-quality scientific figures. It installs predefined .mplstyle files into matplotlib's configuration directory, allowing you to apply consistent formatting across plots with a single line of code. The main 'ipynb' style sets figure dimensions, enables scientific notation, and configures output for Adobe Illustrator editability.

The package is particularly useful for academic writing: it includes color-blind-safe palettes, line styles, markers, and colormaps, plus utilities for font customization and retina display support. A key feature is SVG export without embedded fonts, allowing figures imported into LaTeX documents to automatically adopt the document's native font without manual editing.

Use it for:

- Format plots for inclusion in academic papers or thesis documents with consistent styling across all figures.
- Create publication-ready plots that remain fully editable in Adobe Illustrator for final design adjustments.
- Generate SVG figures that automatically inherit fonts from LaTeX documents when imported.
- Apply color-blind-safe color cycles to ensure accessibility across scientific visualizations.
- Quickly switch between multiple predefined styles (e.g., combining 'ipynb' with 'colorsblind34') for different output contexts.

## Worth the install?

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

LovelyPlots provides matplotlib style sheets that format scientific plots for papers, theses, and presentations while keeping them editable in Adobe Illustrator and compatible with LaTeX documents.

Yes, if you regularly produce scientific plots for papers or theses. The package is low-friction to install and solves a real workflow problem—consistent, publication-ready formatting with LaTeX and Adobe Illustrator compatibility. However, note the dormant maintenance status: the last release was 891 days ago, so verify compatibility with your current matplotlib version before relying on it for critical work.

## Install

pip install lovelyplots
uv add lovelyplots
poetry add lovelyplots

## Installing lovelyplots

Before you install: Low install friction with a single runtime dependency on matplotlib. The package is dormant (last release 891 days ago), though the repository remains active with recent commits and moderate community interest (926 stars).

License in practice: MIT license is permissive, allowing free use, modification, and distribution with minimal restrictions—suitable for academic and commercial projects.

Quickstart:

pip install lovelyplots

import lovelyplots
import matplotlib.pyplot as plt
plt.style.use('ipynb')

# Create and display plots normally
fig, ax = plt.subplots()
ax.plot(x, y)

As of version 1.0.0, the import lovelyplots statement must come before calling plt.style.use().

Verify before relying:

- Whether the package works with current matplotlib versions (last release was 891 days ago).
- Compatibility with modern Python versions beyond what the classifiers indicate.

## Package facts

- License: MIT (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: dormant
- Downloads: 522.7K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

matplotlib style sheets scientific, publication-ready plots, adobe illustrator compatible plots, latex figure formatting, thesis plot styling, matplotlib-styling, academic-publishing, scientific-visualization

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