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Vaex Big Data Analytics

Helps Claude use Vaex to aggregate, visualize, and run ML on billion-row tabular datasets that don't fit in RAM.

Data & AnalyticsIntermediate★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

Gives Claude a working playbook for Vaex, the lazy out-of-core DataFrame library, so it can analyze tabular files (CSV, HDF5, Arrow, Parquet) far larger than available memory.

  • Lazy evaluation and virtual columns for zero-copy feature engineering
  • Blazing-fast statistics, groupby/agg, and batched computation with delay=True
  • Heatmaps and histograms of hundreds of millions of rows via df.viz
  • vaex-ml pipelines: scaling, encoding, PCA, K-means, plus scikit-learn/XGBoost/CatBoost integration
  • I/O strategy guidance, including converting CSV to HDF5/Arrow for instant reloads
  • Six topic reference docs loaded on demand (dataframes, processing, performance, viz, ML, I/O)

Who it's for

  • Analysts crunching multi-GB to TB log, transaction, or sensor tables on one machine
  • Python users who keep hitting pandas out-of-memory errors
  • Researchers with astronomy data or large financial time series
  • Engineers who want to max out a single box before standing up Dask/Spark

Examples

  1. "Convert this 30GB transaction CSV to HDF5 and sum revenue by category" → generates vaex.open, export_hdf5, and groupby().agg() code
  2. "Plot a heatmap of 100M lat/lon points" → produces df.viz.heatmap(df.lon, df.lat, limits='99.7%') script
  3. "Build a preprocessing pipeline and XGBoost model on data that won't fit in RAM" → vaex-ml transformers plus training and model serialization

· · · Install guide · · ·

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/vaex folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/vaex/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/vaex ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal (Terminal on macOS/Linux, PowerShell on Windows).
  2. Clone the skills repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy just this skill: cp -r scientific-agent-skills/skills/vaex ~/.claude/skills/
  5. Install Vaex in your Python environment: uv pip install vaex (or pip install vaex).
  6. Use Python 3.10+ (3.12 with vaex >= 4.19.0 recommended). For cloud storage add uv pip install s3fs gcsfs adlfs.
  7. Restart Claude Code, then ask something like "analyze this huge CSV with vaex" and the skill will activate automatically.
View source on GitHub ↗License: MIT