# Xarray related projects Below is a list of existing open source projects that build functionality upon xarray. See also section [Xarray Internals](../internals/index.html.md#internals) for more details on how to build xarray extensions. We also maintain the [xarray-contrib](https://github.com/xarray-contrib) GitHub organization as a place to curate projects that build upon xarray. ## Geosciences - [aospy](https://aospy.readthedocs.io): Automated analysis and management of gridded climate data. - [argopy](https://github.com/euroargodev/argopy): xarray-based Argo data access, manipulation and visualisation for standard users as well as Argo experts. - [cf_xarray](https://cf-xarray.readthedocs.io/en/latest/): Provides an accessor (DataArray.cf or Dataset.cf) that allows you to interpret Climate and Forecast metadata convention attributes present on xarray objects. - [climpred](https://climpred.readthedocs.io): Analysis of ensemble forecast models for climate prediction. - [geocube](https://vylor.github.io/geocube): Tool to convert geopandas vector data into rasterized xarray data. - [GeoUtils](https://geoutils.readthedocs.io): Raster and vector operations for geospatial analysis, built on rasterio and geopandas. - [GeoWombat](https://github.com/jgrss/geowombat): Utilities for analysis of remotely sensed and gridded raster data at scale (easily tame Landsat, Sentinel, Quickbird, and PlanetScope). - [grib2io](https://github.com/NOAA-MDL/grib2io): Utility to work with GRIB2 files including an xarray backend, DASK support for parallel reading in open_mfdataset, lazy loading of data, editing of GRIB2 attributes and GRIB2IO DataArray attrs, and spatial interpolation and reprojection of GRIB2 messages and GRIB2IO Datasets/DataArrays for both grid to grid and grid to stations. - [gsw-xarray](https://github.com/DocOtak/gsw-xarray): a wrapper around [gsw](https://teos-10.github.io/GSW-Python) that adds CF compliant attributes when possible, units, name. - [infinite-diff](https://github.com/spencerahill/infinite-diff): xarray-based finite-differencing, focused on gridded climate/meteorology data - [marc_analysis](https://github.com/darothen/marc_analysis): Analysis package for CESM/MARC experiments and output. - [MetPy](https://unidata.github.io/MetPy/dev/index.html): A collection of tools in Python for reading, visualizing, and performing calculations with weather data. - [MPAS-Analysis](https://mpas-dev.github.io/MPAS-Analysis): Analysis for simulations produced with Model for Prediction Across Scales (MPAS) components and the Accelerated Climate Model for Energy (ACME). - [OGGM](https://oggm.org/): Open Global Glacier Model - [Oocgcm](https://oocgcm.readthedocs.io/): Analysis of large gridded geophysical datasets - [Open Data Cube](https://www.opendatacube.org/): Analysis toolkit of continental scale Earth Observation data from satellites. - [Pangaea](https://pangaea.readthedocs.io/en/latest/): xarray extension for gridded land surface & weather model output). - [Pangeo](https://pangeo.io): A community effort for big data geoscience in the cloud. - [PyGDX](https://pygdx.readthedocs.io/en/latest/): Python 3 package for accessing data stored in GAMS Data eXchange (GDX) files. Also uses a custom subclass. - [pyinterp](https://pangeo-pyinterp.readthedocs.io/en/latest/): Python 3 package for interpolating geo-referenced data used in the field of geosciences. - [pyXpcm](https://pyxpcm.readthedocs.io): xarray-based Profile Classification Modelling (PCM), mostly for ocean data. - [Regionmask](https://regionmask.readthedocs.io/): plotting and creation of masks of spatial regions - [rioxarray](https://vylor.github.io/rioxarray): geospatial xarray extension powered by rasterio - [salem](https://salem.readthedocs.io): Adds geolocalised subsetting, masking, and plotting operations to xarray’s data structures via accessors. - [SatPy](https://satpy.readthedocs.io/) : Library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats. - [SARXarray](https://tudelftgeodesy.github.io/sarxarray/): xarray extension for reading and processing large Synthetic Aperture Radar (SAR) data stacks. - [shxarray](https://shxarray.wobbly.earth/): Convert, filter,and map geodesy related spherical harmonic representations of gravity and terrestrial water storage through an xarray extension. - [spharmgrid](https://spharmgrid.readthedocs.io/): Spherical harmonic tools for atmospheric science, including scalar and vector filtering, regridding, differential operators, and kinematics. Built on [DUCC](https://gitlab.mpcdf.mpg.de/mtr/ducc), implementing most of [NCL](https://www.ncl.ucar.edu/)’s high-level spherical harmonic operations. - [Spyfit](https://spyfit.readthedocs.io/en/master/): FTIR spectroscopy of the atmosphere - [TOAD](https://github.com/tipmip-methods/toad/): TOAD (Tipping and Other Abrupt events Detector) detects and clusters abrupt shifts in gridded Earth system data and operates directly on xarray datasets. - [windspharm](https://ajdawson.github.io/windspharm/index.html): Spherical harmonic wind analysis in Python. - [wradlib](https://wradlib.org/): An Open Source Library for Weather Radar Data Processing. - [wrf-python](https://wrf-python.readthedocs.io/): A collection of diagnostic and interpolation routines for use with output of the Weather Research and Forecasting (WRF-ARW) Model. - [xarray-eopf](https://github.com/EOPF-Sample-Service/xarray-eopf): An xarray backend implementation for opening ESA EOPF data products in Zarr format. - [xarray-regrid](https://github.com/EXCITED-CO2/xarray-regrid): xarray extension for regridding rectilinear data. - [xarray-simlab](https://xarray-simlab.readthedocs.io): xarray extension for computer model simulations. - [xarray-spatial](https://xarray-spatial.org/): Numba-accelerated raster-based spatial processing tools (NDVI, curvature, zonal-statistics, proximity, hillshading, viewshed, etc.) - [xarray-topo](https://xarray-topo.readthedocs.io/): xarray extension for topographic analysis and modelling. - [xbpch](https://github.com/darothen/xbpch): xarray interface for bpch files. - [xCDAT](https://xcdat.readthedocs.io/): An extension of xarray for climate data analysis on structured grids. - [xclim](https://xclim.readthedocs.io/): A library for calculating climate science indices with unit handling built from xarray and dask. - [xESMF](https://pangeo-xesmf.readthedocs.io/): Universal regridder for geospatial data. - [xgcm](https://xgcm.readthedocs.io/): 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](https://xmitgcm.readthedocs.io/): a python package for reading [MITgcm](https://mitgcm.org/) binary MDS files into xarray data structures. - [xnemogcm](https://github.com/rcaneill/xnemogcm/): a package to read [NEMO](https://nemo-ocean.eu/) output files and add attributes to interface with xgcm. ## Machine Learning - [ArviZ](https://arviz-devs.github.io/arviz/): Exploratory analysis of Bayesian models, built on top of xarray. - [Darts](https://github.com/unit8co/darts/): User-friendly modern machine learning for time series in Python. - [Elm](https://ensemble-learning-models.readthedocs.io): Parallel machine learning on xarray data structures - [sklearn-xarray (1)](https://phausamann.github.io/sklearn-xarray): Combines scikit-learn and xarray (1). - [sklearn-xarray (2)](https://sklearn-xarray.readthedocs.io/en/latest/): Combines scikit-learn and xarray (2). - [xbatcher](https://xbatcher.readthedocs.io): Batch Generation from Xarray Datasets. ## Other domains - [ptsa](https://pennmem.github.io/ptsa/html/index.html): EEG Time Series Analysis - [pycalphad](https://pycalphad.org/docs/latest/): Computational Thermodynamics in Python - [pyomeca](https://pyomeca.github.io/): Python framework for biomechanical analysis - [movement](https://movement.neuroinformatics.dev/): A Python toolbox for analysing animal body movements ## Extend xarray capabilities - [Collocate](https://github.com/cistools/collocate): Collocate xarray trajectories in arbitrary physical dimensions - [eofs](https://ajdawson.github.io/eofs/): EOF analysis in Python. - [hypothesis-gufunc](https://hypothesis-gufunc.readthedocs.io/en/latest/): Extension to hypothesis. Makes it easy to write unit tests with xarray objects as input. - [ntv-pandas](https://github.com/loco-philippe/ntv-pandas) : A tabular analyzer and a semantic, compact and reversible converter for multidimensional and tabular data - [nxarray](https://github.com/nxarray/nxarray): NeXus input/output capability for xarray. - [xarray-compare](https://github.com/astropenguin/xarray-compare): xarray extension for data comparison. - [xarray-dataclasses](https://github.com/astropenguin/xarray-dataclasses): xarray extension for typed DataArray and Dataset creation. - [xarray_einstats](https://xarray-einstats.readthedocs.io): Statistics, linear algebra and einops for xarray - [xarray_extras](https://github.com/crusaderky/xarray_extras): Advanced algorithms for xarray objects (e.g. integrations/interpolations). - [xarray-mongodb](https://xarray-mongodb.readthedocs.io/en/latest/): Store xarray objects on MongoDB. - [xeofs](https://github.com/nicrie/xeofs): PCA/EOF analysis and related techniques, integrated with xarray and Dask for efficient handling of large-scale data. - [xpublish](https://xpublish.readthedocs.io/): Publish Xarray Datasets via a Zarr compatible REST API. - [xrft](https://github.com/rabernat/xrft): Fourier transforms for xarray data. - [xr-scipy](https://xr-scipy.readthedocs.io): A lightweight scipy wrapper for xarray. - [X-regression](https://github.com/kuchaale/X-regression): Multiple linear regression from Statsmodels library coupled with Xarray library. - [xskillscore](https://github.com/xarray-contrib/xskillscore): Metrics for verifying forecasts. - [xyzpy](https://xyzpy.readthedocs.io): Easily generate high dimensional data, including parallelization. - [xarray-lmfit](https://github.com/kmnhan/xarray-lmfit): xarray extension for curve fitting using [lmfit](https://lmfit.github.io/lmfit-py/). ## Visualization - [datashader](https://datashader.org), [geoviews](https://geoviews.org), [holoviews](https://holoviews.org/), : visualization packages for large data. - [hvplot](https://hvplot.pyviz.org/) : A high-level plotting API for the PyData ecosystem built on HoloViews. - [psyplot](https://psyplot.readthedocs.io): Interactive data visualization with python. - [xarray-leaflet](https://github.com/davidbrochart/xarray_leaflet): An xarray extension for tiled map plotting based on ipyleaflet. - [xtrude](https://github.com/davidbrochart/xtrude): An xarray extension for 3D terrain visualization based on pydeck. - [pyvista-xarray](https://github.com/pyvista/pyvista-xarray): xarray DataArray accessor for 3D visualization with [PyVista](https://github.com/pyvista/pyvista) and DataSet engines for reading VTK data formats. ## Non-Python projects - [xframe](https://github.com/xtensor-stack/xframe): C++ data structures inspired by xarray. - [AxisArrays](https://github.com/JuliaArrays/AxisArrays.jl), [NamedArrays](https://github.com/davidavdav/NamedArrays.jl) and [YAXArrays.jl](https://github.com/JuliaDataCubes/YAXArrays.jl): similar data structures for Julia. More projects can be found at the [“xarray” Github topic](https://github.com/topics/xarray).