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Vaex

Maintainer K-Dense Inc. · Last updated March 31, 2026

Vaex is a high-performance Python library designed for la.

Claude CodeOpenClawNanoClawAnalysisWritingvaexdata-analysispackagedata analysis & visualization

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: March 31, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

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: