Total 50,473 skills, Data Processing has 2559 skills
Showing 12 of 2559 skills
Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.
Under the assumption that the US dollar or a certain currency loses its reserve status and gold becomes the only anchor, deduce the 'implied gold price that the balance sheet can withstand' by dividing central bank monetary liabilities by gold reserves, and output the leverage level, gap and ranking of each country or currency.
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering. Activate on 'resolve dependencies', 'topological sort', 'cycle detection', 'dependency order', 'validate dag'. NOT for building DAGs (use dag-graph-builder) or scheduling execution (use dag-task-scheduler).
Expert-level Power BI, DAX, M language, data modeling, Power Query, report design, and paginated reports
Using palladium's leading trend reversal as a confirmation condition, verify whether silver's short-term price movements are supported by both industrial sentiment and risk sentiment, and mark failed trends that lack palladium participation.
Automatically crawl financial statements and operational disclosures (production volume, costs, capital expenditures) of mining companies from the web, back-calculate the fundamental explanations and interval thresholds (e.g., 1.2/1.7) of the "Mining Stock/Metal Price Ratio", and output reproducible valuation decomposition (cost factor / leverage factor / multiple factor / dilution factor).
Astronomy toolkit. FITS I/O, celestial coordinate transforms, cosmology calculations, time systems, WCS, units, astronomical tables, for astronomical data analysis and imaging.
Use when external agents must construct PubFi DSL requests for OpenSearch and Postgres without server-side natural language compilation.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Extract structured data from 40+ websites including Amazon, LinkedIn, Instagram, TikTok, Facebook, YouTube, and more. Uses Bright Data's Web Data APIs with automatic polling. Returns clean JSON with product details, profiles, reviews, posts, and comments.