{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"GIS","url":"https://skillfed.io/packages/category/scientific-engineering-gis"},{"label":"Atmospheric Science","url":"https://skillfed.io/packages/category/scientific-engineering-atmospheric-science"}],"enrichment":{"capability":"regionmask creates spatial masks for gridded data that identify which region each grid point belongs to, enabling regional aggregation of climate, reanalysis, and other geospatial datasets.","skillfed_tags":["geospatial","climate-data","gridded-data"],"use_cases":["Compute regional climate averages from global model output by masking grid points to countries or continents.","Aggregate reanalysis data over custom geographic regions defined in scientific literature.","Generate land-sea masks or other binary spatial masks for filtering gridded datasets.","Create visualizations of predefined or custom regions overlaid on geospatial grids.","Build workflows that combine multiple region definitions (overlapping or non-overlapping) for multi-scale analysis."],"what_it_does":"regionmask is a Python package for creating spatial masks that map grid points in geospatial datasets to geographic regions. It solves the common problem in climate science and geospatial analysis of needing to aggregate gridded data (such as climate model output or reanalysis data) by region\u2014countries, continents, or custom areas\u2014by determining which region each grid point belongs to. The package generates masks in multiple formats (2D integer, 3D boolean, or 3D fractional) and handles edge cases like region boundaries and overlaps carefully.\n\nThe package includes a library of predefined regions (countries, landmasks, and regions from scientific literature) and can also work with user-defined regions from shapefiles via geopandas, numpy arrays, or shapely geometries. It depends on geopandas, numpy, xarray, rasterio, shapely, pooch, and packaging to handle data I/O, spatial operations, and grid manipulation. It is actively maintained, supports modern Python versions, and carries no known security vulnerabilities.","worth_installing":"Yes. regionmask is actively maintained, has no known vulnerabilities, installs with low friction, and is licensed permissively. It directly solves a common and specific need in climate and geospatial data workflows. Install it if you work with gridded data and need to aggregate or mask by geographic region."},"id":"regionmask","links":{"html":"https://skillfed.io/packages/regionmask","md":"https://skillfed.io/packages/regionmask.md","pypi":"https://pypi.org/project/regionmask/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-12-03","license_spdx":null,"license_treatment":"permissive","name":"regionmask","python_support":"supports_current","summary":"create masks of geospatial regions for arbitrary grids"},"popularity":{"monthly_downloads":177263,"position":10216,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.13.0"}