{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/7"},{"label":"GIS","url":"https://skillfed.io/packages/category/scientific-engineering-gis"}],"enrichment":{"capability":"rioxarray extends xarray with geospatial and raster operations powered by rasterio, enabling you to work with georeferenced gridded data using familiar xarray syntax.","skillfed_tags":["geospatial","raster-data","xarray-extension"],"use_cases":["Load satellite or aerial imagery into xarray and perform analysis using labeled dimensions and coordinate-aware slicing","Reproject raster data between different coordinate reference systems while preserving spatial metadata","Read and write raster formats with automatic coordinate and CRS metadata handling","Clip raster datasets to geographic regions using coordinate-aware operations","Combine raster analysis with xarray's groupby, resample, and aggregation operations for time-series or multi-band data"],"what_it_does":"rioxarray is an xarray extension that adds geospatial and raster-specific operations to xarray DataArrays and Datasets. It bridges xarray's labeled array interface with rasterio's raster I/O and geospatial capabilities, letting you work with georeferenced gridded data\u2014satellite imagery, climate models, digital elevation models\u2014using xarray's familiar syntax and operations.\n\nThe package handles common geospatial tasks like reading and writing raster files, reprojecting between coordinate reference systems, clipping to geographic bounds, and managing spatial metadata. It depends on rasterio for raster I/O, xarray for the array interface, pyproj for coordinate transformations, and numpy for underlying computation. It's actively maintained and supports Python 3.12 and later.","worth_installing":"Yes. rioxarray is actively maintained, has no known vulnerabilities, installs with low friction, and fills a genuine gap for developers working with geospatial gridded data in Python. If you use xarray and need raster operations or geospatial metadata handling, it's the standard choice. The Apache-2.0 license is permissive for all use cases."},"id":"rioxarray","links":{"html":"https://skillfed.io/packages/rioxarray","md":"https://skillfed.io/packages/rioxarray.md","pypi":"https://pypi.org/project/rioxarray/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-27","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"rioxarray","python_support":"supports_current","summary":"geospatial xarray extension powered by rasterio"},"popularity":{"monthly_downloads":1141789,"position":4306,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.23.0"}