geoplot-themes 0.1.4

Stunning pre-designed map themes and styling templates for Matplotlib, Seaborn, and GeoPandas

GeoPlot-Themes 🌍🎨

Stunning pre-designed map themes, custom geographic colormaps, and cartographic templates for Matplotlib, Seaborn, and GeoPandas.

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geoplot-themes bridges the gap between Python's data processing ecosystem (GeoPandas, Shapely, Pandas) and R's layout rendering engine (ggplot2, ggspatial, ggnewscale). Create publication-quality, aesthetically gorgeous maps instantly without spent hours tweaking grid lines, legend alignment, or north arrow coordinates.

🌟 Visual Showcase

Handcrafted Cartographic Themes

natgeo_minimalist (Cream/Editorial)	retro_blueprint (Classic Technical)	dark_matter (Neon/Dark Mode)

Complex Vector Overlays with Independent Legends

A base raster (elevation/erosion) layered with multiple separate vector shapefiles (wetlands and rivers), featuring automatically styled, independent, conflict-free scales:

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🚀 Key Features

• Pre-designed Themes: Instantly switch visual aesthetics (natgeo_minimalist, dark_matter, retro_blueprint) without altering your plotting code.
• Geographic Colormaps: Built-in, science-backed palettes optimized for terrain (elevation), oceanography (bathymetry), technical grids (blueprint), and digital screens (neon).
• Conflict-Free Legends: Stack infinite shapefile layers (polygons, lines, points) with independent, color-coordinated legends.
• Auto-Orientation & Fit: Calculates data bounding boxes dynamically (orientation="auto") to yield tightly cropped maps without margins or white padding.
• Floating Inset Maps: Sub-coordinate map inserts that automatically render a global or country-level context and draw a reference box of your zoom location.
• Automatic Label Repulsion: Non-overlapping text labels powered by ggrepel that cleanly connect text back to point coordinates.

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📦 Installation

To install geoplot-themes with uv (recommended):

uv add geoplot-themes

Or via standard pip:

pip install geoplot-themes

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📚 Documentation

For full documentation, including Quickstart guides, API reference, and detailed Design reference, please visit our official website:

https://charles483.github.io/geoplot-themes/

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🤝 Contributing & Support

Contributions are welcome! Please read the Contributing Guidelines and submit Pull Requests.

For questions, issues, or feedback, please contact us at [e-mail].

Created and maintained by Perur Geospatial Solutions.