polars
High-performance Python DataFrame library for ETL and analytics: expression-based manipulation, lazy queries, streaming and pandas migration.
- Kind
- Skill
- Works with
- Claude Code, Codex, Cursor, Gemini / Antigravity
- Languages
- Python
- Source
- Scientific Agent Skills (K-Dense) @ 5f2bc0341354
- Path
- skills/polars/SKILL.md
- Jobs
- Implementation
- Topics
- Data analysis & BI, Data pipelines
Credit
- Made by
- K-Dense-AI
- Original
- github.com/K-Dense-AI/scientific-agent-skills/blob/5f2bc03413…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
gh skill install K-Dense-AI/scientific-agent-skills polars
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/polars/ (the skill folder)
- 7 file(s) the skill refers to
- Runs scripts
- Yes
- shell block in the text
- Uses the network
- Yes
- downloads Python packages
- Needs secrets
- None found
- Source revision
- 5f2bc0341354
- Licence
- MIT
- Last activity
- 26 Oct 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# Polars
## Overview
Polars is a columnar DataFrame library for Python and Rust with Arrow interoperability. Work with Polars' expression-based API, lazy evaluation framework, and high-performance data manipulation capabilities for efficient data processing, pandas migration, and data pipeline optimization.
Reviewed against the official stable documentation and native Polars 1.44.2. Local
regression tests cover the corrected APIs and scientific failure cases; cloud, GPU,
BigQuery, and remote database recipes are illustrative and require provider setup.
Fragments using undefined columns, paths, or `...` require adaptation to the dataset.
## Quick Start
### Installation and Basic Usage
Install the current stable Polars release verified during this refresh:
```bash
uv pip install "polars==1.44.2"
```
Install optional integrations only when needed:
```bash
uv pip install "polars[excel,database,fsspec,pandas,numpy]==1.44.2"
```
Basic DataFrame creation and operations:
```python
import polars as pl
# Create DataFrame
df = pl.DataFrame({
"name": ["Alice", "Bob", "Charlie"],
"age": [25, 30, 35],
"city": ["NY", "LA", "SF"]
})
# Select columns
df.select("name", "age")
…