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Polars DataFrame Skill

Guides the agent to write fast Polars code for data cleaning, analysis, and pandas migration

Source Download skill
Repository
K-Dense-AI/scientific-agent-skills
Stars
55,780
Licence
MIT
Files
8 files

What it does

Polars is a fast Python library for working with tables of data. This skill teaches the agent Polars' expression-based syntax, lazy query optimization, and common patterns such as filtering, grouping, joins, reading and writing CSV, Parquet and JSON files, and moving code over from pandas. Once installed, the agent can write and check Polars code for you, using reference guides for details like I/O, best practices and migration.

Great for

  • Data analysts or engineers building ETL or reporting pipelines in Python
  • Developers moving existing pandas code to Polars for speed
  • Anyone handling datasets too large to comfortably load into memory

Skip it if

  • Non-programmers who only need a spreadsheet; the skill assumes Python and command-line installs
  • Production pipelines that depend on cloud, GPU or remote database recipes without testing them, since the skill says those are illustrative and need provider setup

Try asking

  • “Rewrite this pandas groupby script in Polars using lazy evaluation”
  • “Load these large CSV files with scan_csv, filter them and save the result as Parquet”
  • “Add a column that ranks each salary within its department using Polars window functions”
  • “Convert my pandas merge and pivot code to the equivalent Polars joins”
Step-by-step guide: how to use Polars DataFrame SkillInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 8 original files, the MIT licence and an attribution note.

    polars.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip polars.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip polars.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Ask the agent to use lazy scan_ functions and collect() for large files, so Polars can optimize the query
  • Give the agent a sample of your column names and types, since the examples use placeholder columns and paths that must be adapted
  • Run the generated code on a small sample first and check results against your existing pandas output

What's inside

  • references/best_practices.md
  • references/core_concepts.md
  • references/io_guide.md
  • references/operations.md
  • references/pandas_migration.md
  • references/review.md
  • references/transformations.md
  • SKILL.md

Redistributed unmodified from K-Dense-AI/scientific-agent-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.