An open-source Python package that provides N-D labeled arrays and datasets, inspired by pandas, making it easier to work with multi-dimensional scientific data.
xarray
- Python
- Data Analytics, Ecology and Sustainability, Marine Science, Mathematics, Simulation
- Climate, Deep Learning, Environmental Engineering, Environmental Impact, Machine Learning, Sustainability Metrics, User experience (UX)
Features:
- Labeled N-dimensional arrays (DataArray), datasets of aligned DataArrays (Dataset), dimension names, coordinates (tick labels), attributes (metadata), label-based indexing and selection, broadcasting by dimension name, groupby operations, interpolation and resampling, plotting capabilities (integration with Matplotlib, Seaborn), parallel computation with Dask, I/O for NetCDF, Zarr, GeoTIFF and other formats
Pricing:
- Free
- Powerful for handling multi-dimensional labeled data, simplifies complex data manipulation and analysis, integrates well with pandas, NumPy, Dask, and Matplotlib, excellent for climate, oceanography, meteorology, and other geoscience data, active community.
- Learning curve for understanding its data model (dimensions, coordinates, attributes) compared to simple NumPy arrays, can have memory overhead if not used carefully with large datasets (though Dask helps significantly), some advanced operations might have a more complex syntax.
Best for:
- Scientists and researchers working with multi-dimensional labeled datasets, particularly in fields like climate science, oceanography, meteorology, and remote sensing, for analysis, visualization, and data manipulation.