Total 50,523 skills, Data Processing has 2561 skills
Showing 12 of 2561 skills
Analyze mental health data, identify psychological patterns, assess mental health status, and provide personalized mental health recommendations. Supports correlation analysis with other health data such as sleep, exercise, and nutrition.
Fetches web pages, parses HTML with CSS selectors, calls REST APIs, and scrapes dynamic content. Use when extracting data from websites, querying JSON APIs, or automating browser interactions.
Provides comprehensive guidance for Elasticsearch including indexing, searching, aggregations, mappings, and cluster management. Use when the user asks about Elasticsearch, needs to implement search functionality, work with Elasticsearch queries, or manage Elasticsearch clusters.
Patterns for efficient ML data pipelines using Polars, Arrow, and ClickHouse. TRIGGERS - data pipeline, polars vs pandas, arrow format, clickhouse ml, efficient loading, zero-copy, memory optimization.
Analyze nutrition data, identify nutrition patterns, assess nutritional status, and provide personalized nutrition recommendations. Supports correlation analysis with exercise, sleep, and chronic disease data.
R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
以全球鎳供給結構為核心，量化各國的主導程度（例如印尼）、主要礦區供給量、以及政策配額/減產情境對全球供需平衡與價格非對稱的影響。
Construct a business cycle model using leading and coincident indicators, and interpret two business cycle phases: Expansion (Risk-On) and Contraction (Risk-Off), and generate "Iceberg" and "Sinking" event signals based on the theory.
Measure the valuation range (overvalued/undervalued) of the mining stock sector relative to the metal itself using the ratio of Silver Mining Stock Price to Silver Price, and derive 'bottom/top' signals and scenario projections through historical percentiles and analogous intervals.
Guidance for implementing high-performance portfolio optimization using Python C extensions. This skill applies when tasks require optimizing financial computations (matrix operations, covariance calculations, portfolio risk metrics) by implementing C extensions for Python. Use when performance speedup requirements exist (e.g., 1.2x or greater) and the task involves numerical computations on large datasets (thousands of assets).
Retrieve real-time or historical cash flow statement data including Net Income, Operating Cash Flow, Investing Cash Flow, Financing Cash Flow, Free Cash Flow, and Cash Position for public companies. Use when analyzing cash generation, capital allocation, or liquidity trends.