Vaex is a Python library that handles huge tables of data with billions of rows. It works even when the data does not fit in your computer's memory. Out-of-core processing means Vaex reads data straight from disk without loading everything at once. This makes it fast for tasks like counting, grouping, or making charts on massive datasets. You can also build machine learning pipelines on data that would normally crash your system.
People who work with big CSV, HDF5, Arrow, or Parquet files benefit the most. Astronomers, financial analysts, and data scientists use Vaex to explore and visualize large tables interactively. It is a single‑machine tool, not a cluster, so it is easy to set up.
Vaex uses lazy evaluation to delay work until you actually need the result. That saves time and memory. It also creates virtual columns without duplicating data. If your data is bigger than RAM, Vaex is a smart choice.
Add Vaex skill to your workflow
Global
mkdir -p ~/.claude/skills/vaexProject
mkdir -p .claude/skills/vaexSource Repository
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