Time Series Analysis
This is a straightforward prompt for having Claude handle time series work like forecasting, seasonality detection, and trend decomposition. You'd reach for it when you need to predict future values from historical data, spot cyclical patterns in sales or traffic, or break down temporal data into its component parts. The skill comes from aj-geddes' useful-ai-prompts collection, which has 245 GitHub stars and passes all three security audits. It covers the standard time series toolkit: autocorrelation analysis, confidence intervals, and the classic decomposition into trend, seasonal, and residual components. Good fit if you're doing exploratory data analysis on timestamped data and want Claude to guide the analytical approach rather than just crunching numbers.
- GitHub stars
- 317
- last updated
- Aug 21, 2026
Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill 'Time Series Analysis' --agent claude-codeInstalls into .claude/skills of the current project.
Files
Time Series Analysis
Overview
Time series analysis examines data points collected over time to identify patterns, trends, and seasonality for forecasting and understanding temporal dynamics.
When to Use
- Forecasting future values based on historical trends
- Detecting seasonality and cyclical patterns in data
- Analyzing trends over time in sales, stock prices, or website traffic
- Understanding autocorrelation and temporal dependencies
- Making time-based predictions with confidence intervals
- Decomposing data into trend, seasonal, and residual components
Core Components
- Trend: Long-term directional movement
- Seasonality: Repeating patterns at fixed intervals
- Cyclicity: Long-term oscillations (non-fixed periods)
- Stationarity: Constant mean, variance over time
- Autocorrelation: Correlation with past values
Key Techniques
- Decomposition: Separating trend, seasonal, residual components
- Differencing: Making data stationary
- ARIMA: AutoRegressive Integrated Moving Average models
- Exponential Smoothing: Weighted average of past values
- SARIMA: Seasonal ARIMA models
Implementation with Python
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- Repository
- github.com/aj-geddes/useful-ai-prompts
- Category
- AI & Agent Building
- First seen
- Jun 3, 2026
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