polars
Polars
Overview
Polars is a blazingly fast DataFrame library written in Rust with Python bindings. Built for performance and memory efficiency, Polars leverages parallel execution and lazy evaluation to process data faster than pandas, especially on large datasets.
When to Use This Skill
Activate when the user:
- Wants to work with DataFrames and needs high performance
- Mentions Polars explicitly or asks for "fast" data processing
- Needs to process large datasets (millions of rows)
- Wants lazy evaluation for query optimization
- Asks for data transformations, filtering, grouping, or aggregations
- Needs to read/write CSV, Parquet, JSON, or other data formats
- Wants to combine with DuckDB for SQL + DataFrame workflows
Installation
More from silvainfm/claude-skills
duckdb
Fast in-process analytical database for SQL queries on DataFrames, CSV, Parquet, JSON files, and more. Use when user wants to perform SQL analytics on data files or Python DataFrames (pandas, Polars), run complex aggregations, joins, or window functions, or query external data sources without loading into memory. Best for analytical workloads, OLAP queries, and data exploration.
232streamlit
Fast Python framework for building interactive web apps, dashboards, and data visualizations without HTML/CSS/JavaScript. Use when user wants to create data apps, ML demos, dashboards, data exploration tools, or interactive visualizations. Transforms Python scripts into web apps in minutes with automatic UI updates.
198reflex-dev
Guide for building full-stack web applications using Reflex, a Python framework that compiles to React frontend and FastAPI backend. Use when creating, modifying, or debugging Reflex apps - covers state management, event handlers, components, routing, styling, and data integration patterns.
92project-planner
Comprehensive project planning and documentation generator for software projects. Creates structured requirements documents, system design documents, and task breakdown plans with implementation tracking. Use when starting a new project, defining specifications, creating technical designs, or breaking down complex systems into implementable tasks. Supports user story format, acceptance criteria, component design, API specifications, and hierarchical task decomposition with requirement traceability.
38reportlab
Python library for programmatic PDF generation and creation. Use when user wants to generate PDFs from scratch, create invoices, reports, certificates, labels, or custom documents with precise control over layout, fonts, graphics, tables, and charts. Supports both low-level drawing (Canvas) and high-level documents (Platypus).
23marketing-ideas
When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 140 proven marketing approaches organized by category.
20