vaex-dataframes SKILL.md skillA
vaex-dataframes from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/vaex-dataframes@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/scientific-computing/vaex-dataframes/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 24,905 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Out-of-core DataFrame for billion-row data via lazy evaluation and memory-mapped files. Use when data exceeds RAM (10 GB–TB) for fast aggregation, filtering, virtual columns, and visualization without loading. Supports HDF5, Arrow, Parquet, CSV with cloud (S3, GCS, Azure). Built-in ML transformers (scaling, PCA, K-means). In-memory: polars; distributed: dask.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Vaex DataFrames ## Overview Vaex is a high-performance Python library for lazy, out-of-core DataFrame operations on datasets too large to fit in RAM. It processes over a billion rows per second using memory-mapped files and lazy evaluation, enabling interactive exploration and analysis without loading data into memory. ## When to Use - Processing tabular datasets larger than available RAM (10 GB to terabytes) - Fast statistical aggregations on massive datasets (mean, std, quantiles at billion-row scale) - Creating visualizations (heatmaps, histograms) of large datasets without sampling - Building ML preprocessing pipelines (scaling, encoding, PCA) on big data - Converting between data formats (CSV to HDF5/Arrow for fast repeated access) - Feature engineering with virtual columns that consume zero additional memory - Working with astronomical catalogs, financial time series, or large scientific datasets - For **in-memory speed** on data that fits in RAM, use **polars** instead - For **distributed multi-node** computing, use **dask** instead ## Prerequisites ```bash pip install vaex # Optional extras: pip install vaex-hdf5 # HDF5 support (recommended) …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/vaex-dataframes@sha256:ed7a65e2686ea341The line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_cnho7nk3fk3nea5n)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 24,905 B | A | view · diff |
| git:20260218.e460066 | 2026-02-18 | e460066 | 25,041 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (24905 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_cnho7nk3fk3nea5n GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/vaex-dataframes GET https://markdownregistry.com/api/v1/blob/ed7a65e2686ea341f45743b05079ee1bd7f13a2de4696caa22ae93a444ccd8a8
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.