Data Science & Analytics
AlterLab Dask
Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.
- Publisher / source
- AlterLab-IEU/AlterLab-Academic-Skills (found on the CSV list)
- Upstream record
- AlterLab-IEU/AlterLab-Academic-Skills
- Version
- Version 3
- Published
- Publication review
- Approved for publication
- Content fingerprint
17a620e93aab2cd03141ab2b02322a9e2fc4b72a43cec8619cf322555685f672