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# https://vitepress.dev/reference/default-theme-home-page
layout: home
hero:
name: "YAXArrays.jl"
text: "Yet another xarray-like Julia package"
tagline: A package for operating on out-of-core labeled arrays, based on stores like NetCDF, Zarr or GDAL.
image:
src: /logo.png
alt: VitePress
actions:
- theme: alt
text: Get Started
link: /get_started
- theme: alt
text: View on Github
link: https://github.com/JuliaDataCubes/YAXArrays.jl
- theme: alt
text: API reference
link: /api
features:
- title: Flexible I/O capabilities
details: Open and operate on NetCDF and Zarr datasets directly. Or bring in data from other sources with ArchGDAL.jl, GRIBDatasets.jl, GeoJSON.jl, HDF5.jl, Shapefile.jl, GeoParquet.jl, etc.
link: /UserGuide/openZarr
- title: Interoperability
details: Well integrated with Julia's ecosystem, i.e., distributed operations are native. And plotting with Makie.jl is well supported.
- title: Named dimensions and GroupBy(in memory)
details: Apply operations over named dimensions, select values by labels and integers as well as efficient split-apply-combine operations with groupby via DimensionalData.jl.
link: /UserGuide/group_by
- title: Efficiency
details: Efficient mapslices(x) and mapCube operations on huge multiple arrays, optimized for high-latency data access (object storage, compressed datasets).
Settings
This document was generated with Documenter.jl version 1.5.0 on Friday 26 July 2024. Using Julia version 1.10.3.