AE
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aeon
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Data & Repro
VA
Vaex
Maintainer K-Dense Inc. · Last updated April 1, 2026
Vaex is a high-performance Python library designed for la.
Original source
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/vaex
- Maintainer
- K-Dense Inc.
- License
- MIT license
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Vaex is a high-performance Python library designed for lazy, out-of-core DataFrames to process and visualize tabular datasets that are too large to fit into RAM. Vaex can process over a billion rows per second, enabling interactive data exploration and analysis on datasets with billions of rows.
- df = vaex.open('large_file.hdf5') # or.csv,.arrow,.parquet.
Source Doc
Excerpt From SKILL.md
When to Use This Skill
Use Vaex when:
- Processing tabular datasets larger than available RAM (gigabytes to terabytes)
- Performing fast statistical aggregations on massive datasets
- Creating visualizations and heatmaps of large datasets
- Building machine learning pipelines on big data
- Converting between data formats (CSV, HDF5, Arrow, Parquet)
- Needing lazy evaluation and virtual columns to avoid memory overhead
- Working with astronomical data, financial time series, or other large-scale scientific datasets
Core Capabilities
Vaex provides six primary capability areas, each documented in detail in the references directory:
1. DataFrames and Data Loading
Load and create Vaex DataFrames from various sources including files (HDF5, CSV, Arrow, Parquet), pandas DataFrames, NumPy arrays, and dictionaries. Reference references/core_dataframes.md for:
- Opening large files efficiently
- Converting from pandas/NumPy/Arrow
- Working with example datasets
- Understanding DataFrame structure
Use cases
- Processing tabular datasets larger than available RAM (gigabytes to terabytes).
- Performing fast statistical aggregations on massive datasets.
- Creating visuali.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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