YAXArrays.jl
xarray
| YAXArrays.jl | xarray | |
|---|---|---|
| 1 | 7 | |
| 80 | 3,420 | |
| - | 1.2% | |
| 8.3 | 9.7 | |
| 5 days ago | 7 days ago | |
| Julia | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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YAXArrays.jl
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What is lacking in Julia ecosystem?
we actually have https://github.com/JuliaDataCubes/YAXArrays.jl
xarray
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Request for Startups: Climate Tech
PyTorch and JAX are used heavily in climate science on the ML side. For more general analytics, not so much. Many of our users like to use Xarray as a high-level API. There has been some work to integrate Xarray with PyTorch (https://github.com/pydata/xarray/issues/3232) but we're not there yet.
The Python Array API standard should help align these different back-ends: https://data-apis.org/array-api/latest/
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Python for Data Analysis, 3rd Edition – The Open Access Version Online
Does polars have N-D labelled arrays, and if so can it perform computations on them quickly? I've been thinking of moving from pandas to xarray [0], but might consider poplars too if it has some of that functionality.
[0] https://xarray.dev/
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What is lacking in Julia ecosystem?
https://xarray.dev
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How we found and helped fix 24
bugs in 24 hours (in Tensorflow, Sentry, V8, PyTorch, Hue, and more)
Pydata's xarray
- Xarray awarded a support grant from NASA
- xarray: N-Dimensional labeled arrays and datasets in Python
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Could somebody who has experience with reading .asc files / using xarray please give me some direction?
It does seem like it isn't installed. If you take a look at the source, it catches import errors, meaning it won't error out immediately if the package isn't installed.
What are some alternatives?
QML.jl - Build Qt6 QML interfaces for Julia programs.
iris - A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
Overview-of-the-Julia-Python-R-Universe - Contribute to the side by side overview of the three leading open source data science ecosystems of today
tensorflow - An Open Source Machine Learning Framework for Everyone
ArraysOfArrays.jl - Efficient storage and handling of nested arrays in Julia
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
DimensionalData.jl - Named dimensions and indexing for julia arrays and other data
dask-awkward - Native Dask collection for awkward arrays, and the library to use it.
AxisArrays.jl - Performant arrays where each dimension can have a named axis with values
Dask - Parallel computing with task scheduling
Gtk.jl - Julia interface to Gtk windowing toolkit.
wxee - A Python interface between Earth Engine and xarray for processing time series data