Data Science & Analytics
AlterLab Vaex
Out-of-core tabular analytics with Vaex — memory-mapped HDF5/Arrow/Parquet via vaex.open, lazy virtual columns, delayed single-pass aggregations on billion-row tables, binned histograms/heatmaps, and vaex.ml transformers on one machine. Vaex is in minimal-maintenance mode (vaex-core 4.19 from Sep 2025 supports only Python 3.9–3.12 and pandas < 3), so use it to run, fix, or migrate existing Vaex code; for new larger-than-RAM work prefer Polars lazy/streaming queries (alterlab-polars) or Dask (alterlab-dask). Use when a project already depends on Vaex, when opening memory-mapped HDF5/Arrow files, batching aggregations with delay=True, or porting a Vaex pipeline to 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
cf09293f8ad6299790abefb95bdbe8d61b24fc33e96b02e50494c7dc155fbe9f