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Found 19 Skills
ARIMA, SARIMA, Prophet, trend analysis, seasonality detection, anomaly detection, and forecasting methods. Use for time-based predictions, demand forecasting, or temporal pattern analysis.
Ljung-Box portmanteau tests for model diagnostics and residual analysis
查询亚马逊商品的历史时序数据，包括价格走势、BSR（畅销排名）趋势、评分变化、卖家数量和月销量，支持多个亚马逊站点的任意ASIN。当用户提到价格历史、价格追踪、BSR历史、BSR趋势、历史定价、价格波动、Keepa数据、排名历史、降价提醒、秒杀历史价格、Buy Box价格趋势、优惠券价格、FBA/FBM价格对比、卖家数量变化、评分趋势、销量历史、price history, BSR trends, Keepa historical data, price tracking, sales history, rating changes, seller count changes, price fluctuation时触发此技能。即使用户未明确提及"Keepa"或"时序数据"，只要其需求涉及亚马逊历史商品级数据（如价格、排名或销量随时间的变化趋势），也应触发此技能。
Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis
Expertise in analyzing time-series repository health metrics, investigating root causes, and proposing proactive workflow improvements.