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Getting Started

  • Overview: Why xarray?
  • Frequently Asked Questions
  • Quick overview
  • Examples
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User Guide

  • Terminology
  • Data Structures
  • Indexing and selecting data
  • Interpolating data
  • Computation
  • GroupBy: split-apply-combine
  • Reshaping and reorganizing data
  • Combining data
  • Time series data
  • Weather and climate data
  • Working with pandas
  • Reading and writing files
  • Parallel computing with Dask
  • Plotting
  • Working with numpy-like arrays

Help & reference

  • What’s New
  • How do I …
  • API reference
  • xarray Internals
  • Development roadmap
  • Contributing to xarray
  • Xarray related projects
    • Geosciences
    • Machine Learning
    • Other domains
    • Extend xarray capabilities
    • Visualization
    • Non-Python projects
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Xarray related projects¶

Below is a list of existing open source projects that build functionality upon xarray. See also section xarray Internals for more details on how to build xarray extensions. We also maintain the xarray-contrib GitHub organization as a place to curate projects that build upon xarray.

Geosciences¶

  • aospy: Automated analysis and management of gridded climate data.

  • climpred: Analysis of ensemble forecast models for climate prediction.

  • geocube: Tool to convert geopandas vector data into rasterized xarray data.

  • infinite-diff: xarray-based finite-differencing, focused on gridded climate/meterology data

  • marc_analysis: Analysis package for CESM/MARC experiments and output.

  • MetPy: A collection of tools in Python for reading, visualizing, and performing calculations with weather data.

  • MPAS-Analysis: Analysis for simulations produced with Model for Prediction Across Scales (MPAS) components and the Accelerated Climate Model for Energy (ACME).

  • OGGM: Open Global Glacier Model

  • Oocgcm: Analysis of large gridded geophysical datasets

  • Open Data Cube: Analysis toolkit of continental scale Earth Observation data from satellites.

  • Pangaea:: xarray extension for gridded land surface & weather model output).

  • Pangeo: A community effort for big data geoscience in the cloud.

  • PyGDX: Python 3 package for accessing data stored in GAMS Data eXchange (GDX) files. Also uses a custom subclass.

  • pyinterp: Python 3 package for interpolating geo-referenced data used in the field of geosciences.

  • pyXpcm: xarray-based Profile Classification Modelling (PCM), mostly for ocean data.

  • Regionmask: plotting and creation of masks of spatial regions

  • rioxarray: geospatial xarray extension powered by rasterio

  • salem: Adds geolocalised subsetting, masking, and plotting operations to xarray’s data structures via accessors.

  • SatPy : Library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats.

  • Spyfit: FTIR spectroscopy of the atmosphere

  • windspharm: Spherical harmonic wind analysis in Python.

  • wrf-python: A collection of diagnostic and interpolation routines for use with output of the Weather Research and Forecasting (WRF-ARW) Model.

  • xarray-simlab: xarray extension for computer model simulations.

  • xarray-spatial: Numba-accelerated raster-based spatial processing tools (NDVI, curvature, zonal-statistics, proximity, hillshading, viewshed, etc.)

  • xarray-topo: xarray extension for topographic analysis and modelling.

  • xbpch: xarray interface for bpch files.

  • xclim: A library for calculating climate science indices with unit handling built from xarray and dask.

  • xESMF: Universal regridder for geospatial data.

  • xgcm: Extends the xarray data model to understand finite volume grid cells (common in General Circulation Models) and provides interpolation and difference operations for such grids.

  • xmitgcm: a python package for reading MITgcm binary MDS files into xarray data structures.

  • xshape: Tools for working with shapefiles, topographies, and polygons in xarray.

Machine Learning¶

  • ArviZ: Exploratory analysis of Bayesian models, built on top of xarray.

  • Elm: Parallel machine learning on xarray data structures

  • sklearn-xarray (1): Combines scikit-learn and xarray (1).

  • sklearn-xarray (2): Combines scikit-learn and xarray (2).

Other domains¶

  • ptsa: EEG Time Series Analysis

  • pycalphad: Computational Thermodynamics in Python

  • pyomeca: Python framework for biomechanical analysis

Extend xarray capabilities¶

  • Collocate: Collocate xarray trajectories in arbitrary physical dimensions

  • eofs: EOF analysis in Python.

  • hypothesis-gufunc: Extension to hypothesis. Makes it easy to write unit tests with xarray objects as input.

  • nxarray: NeXus input/output capability for xarray.

  • xarray-compare: xarray extension for data comparison.

  • xarray-custom: Data classes for custom xarray creation.

  • xarray_extras: Advanced algorithms for xarray objects (e.g. integrations/interpolations).

  • xpublish: Publish Xarray Datasets via a Zarr compatible REST API.

  • xrft: Fourier transforms for xarray data.

  • xr-scipy: A lightweight scipy wrapper for xarray.

  • X-regression: Multiple linear regression from Statsmodels library coupled with Xarray library.

  • xskillscore: Metrics for verifying forecasts.

  • xyzpy: Easily generate high dimensional data, including parallelization.

Visualization¶

  • datashader, geoviews, holoviews, : visualization packages for large data.

  • hvplot : A high-level plotting API for the PyData ecosystem built on HoloViews.

  • psyplot: Interactive data visualization with python.

  • xarray-leaflet: An xarray extension for tiled map plotting based on ipyleaflet.

  • xtrude: An xarray extension for 3D terrain visualization based on pydeck.

Non-Python projects¶

  • xframe: C++ data structures inspired by xarray.

  • AxisArrays and NamedArrays: similar data structures for Julia.

More projects can be found at the “xarray” Github topic.

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