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trend_analyzer

Analyze time-series data to detect trends, seasonality, and growth.

1|Updated Mar 14, 2026
Search Tags:#patterns#time-series#analyze#forecast#data-visualization#trend#seasonality
One-click install
npx skills add https://github.com/marcoamu/openclaw-workspace --skill trend-analyzer-marcoamu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trend_analyzer
Source: https://github.com/marcoamu/openclaw-workspace/tree/main/skills/trend-analyzer
Command: npx skills add https://github.com/marcoamu/openclaw-workspace --skill trend-analyzer-marcoamu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analiza tendencias en datos de series temporales para identificar patrones, cambios y tendencias a lo largo del tiempo, ayudando a tomar decisiones basadas en datos.

Core Features & Use Cases

  • Detección de tendencias en series temporales y estacionalidad para planes de negocio.
  • Cálculo de estadísticas clave (medias móviles, tendencias, picos) para informes.
  • Aplicaciones: finanzas, marketing e investigación para pronósticos y análisis de comportamiento.

Quick Start

Carga un conjunto de datos de series temporales y ejecuta el análisis de tendencias para generar un informe.

Frequently Asked Questions about trend_analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze trends and seasonality in time-series data?▼

To analyze time-series data trends and seasonality, you ingest your dataset to compute moving averages and seasonality indicators, returning visualizations and concise summaries for pattern detection.

What is the best way to detect growth patterns in weekly or monthly data?▼

Detecting growth patterns in weekly or monthly data involves calculating moving averages and identifying peaks to reveal trends, which generates visual reports for business planning and forecasting.

Can I use this for financial forecasting and marketing behavior analysis?▼

Yes, time-series trend analysis applies to finance, marketing, and research by computing key statistics and seasonality indicators to generate forecasts and analyze behavior patterns over time.

How do I generate a trend analysis report from a time-series dataset?▼

Generating a trend analysis report requires loading a time-series dataset and running the analysis to compute key statistics, which outputs visualizations and concise summaries of revealed patterns.

What kinds of patterns can I identify using moving averages on time-series data?▼

Using moving averages on time-series data allows you to identify underlying trends, seasonality, and growth changes, providing concise summaries and visualizations for data-driven decision making.

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