Work with large scientific arrays by storing data in smaller blocks and reading selected portions. Guides compression, cloud storage, format migration, and NumPy, Dask, or Xarray integration while preserving dimensions, units, and other metadata.
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- Reading selected regions of large scientific arrays
- Choosing data blocks and compression settings
- Working with scientific arrays stored on S3 or GCS
K-Dense-AI/scientific-agent-skills☆ 5.3万2026年10月19日 更新
Chunked N-D arrays with compression and cloud storage. NumPy-style indexing. Backends: local, S3, GCS, ZIP, memory. Dask/Xarray integration for parallel and labeled computation. For lineage use lamindb; for labeled arrays use xarray.
中文简介正在准备中。当前显示原文说明。
jaechang-hits/SciAgent-Skills☆ 3812026年10月16日 更新
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
中文简介正在准备中。当前显示原文说明。
foryourhealth111-pixel/Vibe-Skills☆ 37312026年10月20日 更新
Fetch weather/climate data via Earth2Studio data sources for specific variables and times. Do NOT use for inference pipelines, model discovery, or installation.
中文简介正在准备中。当前显示原文说明。
NVIDIA/skills☆ 36612026年10月20日 更新
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
中文简介正在准备中。当前显示原文说明。
huang-sh/DeepScience☆ 42026年7月15日 更新