xarray is a widely used open-source Python library for working with labeled, multi-dimensional arrays. It is particularly well suited for climate and environmental data, where variables are often indexed by dimensions such as time, latitude, and longitude.
xarray builds on top of NumPy and integrates closely with the scientific Python ecosystem. It provides a high-level interface for reading, manipulating, and analyzing raster and time-series data stored in formats such as NetCDF and GRIB.
In DHIS2 Climate Tools, xarray is used as the core data structure for working with gridded climate data after it has been downloaded. Loading climate datasets as xarray objects makes it easy to inspect variables, subset data by time or space, and perform aggregation and transformation operations. xarray is also supported by the convenient aggregation functions provided by earthkit.
xarray also supports working with large datasets through lazy loading and chunked computation, which is important when processing multi-year climate time series.
Key documentation and learning resources: