{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/2"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"GIS","url":"https://skillfed.io/packages/category/scientific-engineering-gis"}],"enrichment":{"capability":"Cartopy makes it easy to draw maps for data analysis and visualization by providing object-oriented projection definitions, point/line/polygon transformations between map projections, and Matplotlib integration for advanced mapping.","skillfed_tags":["geospatial","cartography","matplotlib-extension"],"use_cases":["Plot weather or climate data on map projections for meteorological analysis.","Visualize geographic boundaries, coastlines, and administrative regions from shapefiles.","Overlay scientific measurements (satellite data, sensor readings) onto map backgrounds.","Create publication-quality cartographic visualizations for research papers or reports.","Transform and display geospatial point, line, or polygon data across different map projections."],"what_it_does":"Cartopy is a Python library that simplifies drawing maps for scientific data visualization and analysis. It sits on top of Matplotlib and provides object-oriented map projection definitions, coordinate transformations between projections, and vector data handling through Shapely integration. The library lets you work with geographic data\u2014points, lines, polygons, and raster images\u2014and transform them between different map projections, then render them directly in Matplotlib plots.\n\nYou use Cartopy when you need to visualize geospatial data on maps: plotting weather data across regions, displaying geographic features like coastlines and borders, or overlaying scientific measurements on map backgrounds. It handles the projection math and Matplotlib integration so you can focus on your data rather than coordinate system details. The package depends on numpy, matplotlib, shapely, pyproj, pyshp, and packaging\u2014all mature libraries in the scientific Python ecosystem.","worth_installing":"Yes. Cartopy is actively maintained, has no known vulnerabilities, and is the standard choice for map visualization in the scientific Python ecosystem. Medium install friction is typical for geospatial libraries with compiled components. The permissive BSD-3-Clause license poses no restrictions. Install it if you need to visualize geographic or geospatial data in Python."},"id":"cartopy","links":{"html":"https://skillfed.io/packages/cartopy","md":"https://skillfed.io/packages/cartopy.md","pypi":"https://pypi.org/project/cartopy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-08-01","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"Cartopy","python_support":"supports_current","summary":"A Python library for cartographic visualizations with Matplotlib"},"popularity":{"monthly_downloads":5250900,"position":2127,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.25.0"}