Xarray: N-D labeled arrays and datasets in Python

Xarray is an open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience.Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.
Xarray provides data models for working with labeled arrays and datasets. Its toolkit includes a broad set of domain-agnostic functions for advanced analytics and visualization with these data structures.
Interoperable with the scientific Python ecosystem including NumPy, Dask, Pandas, and Matplotlib.
Apply operations over named dimensions
Select values by label instead of integer location
Vectorized operations
Mathematical operations vectorize across multiple dimensions (array broadcasting) based on dimension names, not shape.
Flexible split-apply-combine operations with groupby.
Database like operations
Database like alignment based on coordinate labels that smoothly handles missing values.
Arbitrary metadata tracking
Keep track of arbitrary metadata in the form of a Python dictionary.
Flexible and Extensible I/O backend API
Read and write data to and from NetCDF, HDF, Zarr, OpenDAP, and GRIB.
Try Xarray in a REPL directly in your browser (no installation needed)!
Xarray is part of the larger scientific Python ecosystem. It is built on top of NumPy, Pandas, and Dask and supports a wide range of domain specific scientific applications.
This section lists some of the standalone packages, projects developed with xarray.
Backend-agnostic tools for diagnostics and visualizations of Bayesian inference in Python
An accessor for Xarray objects that interprets Climate and Forecast (CF) metadata convention attributes
Verification of weather and climate forecasts
A high-level plotting API for the PyData ecosystem built on HoloViews
Collection of tools for reading, visualizing and performing calculations with weather data
Integrated modeling and experimental data analysis software for magnetically confined thermonuclear fusion experiments
A community platform for Big Data geoscience
Scalable statistical genetic data analysis in Python
Collection of tools for the analysis and visualization of spatial molecular data
Python library for processing spatial data and interpolating it on regular grids
Raster-based Spatial Analytics for Python
General Circulation Model Postprocessing with xarray
Analysis ready CMIP6 data in Python the easy way with pangeo tools.
Xarray supports multiple array backends, allowing users to choose array types that work best for their application.
NumPy is the fundamental package for array computing with Python.
Distributed arrays and advanced parallelism for analytics, enabling performance at scale.
NumPy-compatible array library for GPU-accelerated computing with Python.
An implementation of chunked, compressed, N-dimensional arrays for Python.
Sparse multi-dimensional arrays for the PyData ecosystem
Operate and manipulate physical quantities in Python
We thank these institutions for generously supporting the development and maintenance of Xarray.
Xarray is a NumFOCUS Sponsored Project, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Xarray with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. For more information, visit numfocus.org If you like Xarray and want to support our mission, please consider making a donation to support our efforts.
© 2026, Xarray core developers. Apache 2.0 Licensed.