Individual skill
vaex
Processes and analyzes tabular datasets too large for RAM using Vaex, a Python library for lazy, out-of-core DataFrames over memory-mapped HDF5 and Arrow files, with CSV and Parquet import/export. Covers virtual columns, filtering, groupby aggregations, large-data heatmaps and histograms, and vaex-ml transformers, PCA, and K-means. Use when opening or converting multi-gigabyte CSV/HDF5/Arrow/Parquet files, computing fast statistics on billions of rows, visualizing massive datasets, building ML pipelines that do not fit in memory, or speeding up slow aggregations with lazy evaluation and delay=True. Prefer polars when data fits in RAM, or dask for cluster-distributed work.
plugins/KalarisLabs/research-agent-skills/skills/vaex/SKILL.md
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- Last checked
- Nov 4, 2026
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- 1,532
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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- big-data,-out-of-core-dataframes,-hdf5,-data-analysis,-python Declared skill tag
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# Vaex
## Overview
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.
## Installation
Install the full meta-package (recommended):
```bash
uv pip install vaex
```
