Total 30,617 skills, Data Processing has 1468 skills
Showing 12 of 1468 skills
Develop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Actor code.
Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk analysis.
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
Use this skill for generating data-driven charts and visualizations using Python. Triggers: "create chart", "generate graph", "plot data", "visualize data", "bar chart", "line chart", "pie chart", "comparison chart", "positioning matrix", "trend chart", "market size chart", "TAM SAM SOM", "growth chart", "data visualization" Outputs: PNG/SVG chart images with accurate data representation. Used by: competitive-intel-agent, market-researcher-agent, pitch-deck-agent, review-analyst-agent
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
Elasticsearch development best practices for indexing, querying, and search optimization
Chart selection and data visualization guidance for effective data communication. Use when: creating visualizations, choosing chart types, designing dashboards, or when user mentions data visualization, charts, graphs, or needs help presenting data visually.
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".
Expert guidance for building web scrapers and crawlers using the Scrapy Python framework with best practices for spider development, data extraction, and pipeline management.
Perform forensic-level analysis of a single company's financial statements, evaluating earnings quality, financial health, fraud risk, and operational efficiency. Use when the user asks for a deep dive into a company's financials, DuPont analysis, earnings quality check, balance sheet analysis, cash flow analysis, Altman Z-score, Beneish M-score, working capital analysis, or any detailed single-company financial examination.
Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.