Data Scientist

by code-yeongyu

Data Scientist is a Data skill for Claude Code, published by code-yeongyu in lazycodex.

3.2K stars201 forkson code-yeongyu/lazycodexAdded 2026/08/17+1% in starsRepository updated 2026/08/09

View source on GitHub Download repo ZIP

aiai-agentsclaudeclaude-codeclicodexdeveloper-toolslazylazycodexoh-my-openagentomoopenaiorchestrationtypescript

Install in seconds

Install Data Scientist

Copy Data Scientist into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/code-yeongyu/lazycodex/tree/main/plugins/omo/skills/data-scientist ~/.claude/skills/data-scientist

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/code-yeongyu/lazycodex.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: plugins/omo/skills/data-scientist/SKILL.md in code-yeongyu/lazycodex
Installs to: ~/.claude/skills/data-scientist
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Data Scientist does

Data Scientist processes and analyzes data files using DuckDB and Polars for high-performance workloads. Use it when you need to query, filter, join, aggregate, visualize, or clean CSV, Parquet, JSON, or DuckDB datasets.

Data Scientist is cataloged under Data on DirSkills. Data Scientist comes from a repository tagged ai, ai-agents, claude, claude-code and cli.

Documentation

README

Excerpt

Data Scientist: High-Performance Data Processing Expert

Role & Expertise

Performance-obsessed data scientist with expertise in:

Intelligent tool selection: DuckDB vs Polars based on operation characteristics
Zero-copy data interchange via Apache Arrow
Memory-efficient processing for datasets exceeding RAM
SQL and DataFrame API mastery for analytical workloads

Environment Setup

Everything runs through uv. If uv is not on PATH, set it up first — pick the path that matches the system and run it, no manual guesswork:

bash scripts/setup-uv.sh        # macOS / Linux / WSL / Git Bash — auto-detects OS + arch, installs or updates uv to latest

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Data Scientist

What else does code-yeongyu publish alongside Data Scientist?
Data Scientist is one of 25 skills that DirSkills catalogs from code-yeongyu/lazycodex, the repository it ships in. Its siblings there include Ast-Grep, Bug Fix Contribution and Codex Rules. Each one is a separate skill with its own page in this directory, installs the same way Data Scientist does, and is maintained by code-yeongyu in that same repository. The rest of the collection is listed on the code-yeongyu/lazycodex page.
How does Data Scientist compare to other Data skills?
Data Scientist ranks #220 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Data Scientist against them. Open each page to compare what they document and how they install.