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0.15.0

Getting Started

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

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

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¶

Here 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.

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-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

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

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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© Copyright 2014-2020, xarray Developers Last updated on 2020-02-17.

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