AI Skill MartBrowse skillsPromptsProgramsLearnWhat is a Skill?
 
← Back to list

Polars DataFrame Guide

A skill that helps Claude write fast, idiomatic Polars code using its expression API, lazy engine, and pandas migration mappings.

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

What it does

  • Guides installation (uv pip install "polars==1.41.2") plus optional extras for Excel, databases, cloud storage, and GPU.
  • Writes idiomatic core operations: select, filter, with_columns, group_by().agg().
  • Explains when to use eager DataFrames vs lazy LazyFrames, with predicate/projection pushdown and streaming collection for out-of-core data.
  • Provides a pandas → Polars operation mapping table for migrating existing code.
  • Covers I/O across CSV, Parquet, JSON, Excel, databases, and S3/GCS/Azure, plus joins, concat, pivot, and unpivot.
  • Ships six reference docs under references/ that are loaded on demand for deeper topics.

Who it's for

  • Data analysts and engineers hitting pandas performance walls on large CSV/Parquet files.
  • Python developers rewriting ETL pipelines with the Polars expression API.
  • Newcomers to Polars syntax, especially over() window functions, when/then, and regex column selection.

Example uses

  1. "Convert this pandas script to Polars" → maps assign to with_columns, groupby to group_by, etc.
  2. "Aggregate average salary per city from a 30GB CSV" → builds a scan_csv lazy pipeline with early column selection and collect(engine="streaming").
  3. "Add group averages and ranks without collapsing rows" → generates window expressions like pl.col("age").mean().over("city").

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/polars/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

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 AI Skill Mart.
Copy the skills/polars folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/polars/.
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 /tmp/sas && mkdir -p ~/.claude/skills && cp -r /tmp/sas/skills/polars ~/.claude/skills/

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

  1. Open a terminal.
  2. Clone the 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/polars ~/.claude/skills/
  5. On Python 3.10+, install the library: uv pip install "polars==1.41.2" (or pip install "polars==1.41.2").
  6. For Excel/database/cloud support: uv pip install "polars[excel,database,fsspec,pandas,numpy]==1.41.2"
  7. Restart Claude Code and ask something like "use Polars to aggregate this CSV" to trigger the skill.
View source on GitHub ↗License: MIT