Total 52,846 skills, Data Processing has 2644 skills
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Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.
Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.
Extract a typed JSON object from one or more web pages against a JSON Schema with fastCRW. Use when you need structured data — "get the price and stock status", "extract all job listings as JSON", "pull structured fields from this page". Step 6 of the crw workflow ladder.
Scrape, crawl, map, search, parse, and extract web data with fastCRW — the open-source, self-hostable Firecrawl alternative (single Rust binary, ~6 MB RAM, Firecrawl-compatible /v1 + /v2 API). Use whenever the user needs page content, site-wide extraction, URL discovery, web search, PDF parsing, structured JSON from pages, or change tracking. Also use when the user mentions Firecrawl, Tavily, Crawl4AI, or "scrape/crawl/map/fetch/get the page/read this site/search the web" — crw is a drop-in for the Firecrawl SDKs.