The Time Series Analysis Tool helps users analyze trends, seasonality, and patterns in chronological data. Whether forecasting future values, detecting anomalies, or decomposing time series components, this tool is essential for finance, economics, business, and scientific research.

Key Features

✅ Trend & Seasonality Detection – Identifies long-term trends and seasonal variations in time series data.
✅ Multiple Analysis Methods – Supports Moving Averages, Exponential Smoothing, ARIMA, and Decomposition.
✅ Forecasting Capabilities – Predicts future values based on historical data.
✅ Graphical Visualization – Displays line charts, autocorrelation plots, and seasonal decomposition graphs.
✅ PDF Report Generation – Export insights, statistical summaries, and visual trends.

Use Cases

📌 Financial Market Analysis – Track stock prices, exchange rates, and economic indicators.
📌 Business Sales & Demand Forecasting – Predict sales trends and inventory needs.
📌 Weather & Climate Studies – Analyze temperature and rainfall patterns over time.
📌 Healthcare & Epidemiology – Monitor disease spread and patient trends over time.

How It Works

1️⃣ Upload or Enter Time Series Data – Input data manually or upload a CSV file.
2️⃣ Choose Analysis Method – Select from Moving Averages, ARIMA, Exponential Smoothing, or Seasonal Decomposition.
3️⃣ Run Analysis – The tool processes data and generates statistical insights.
4️⃣ Visualize Trends – View interactive graphs to explore patterns, seasonality, and anomalies.
5️⃣ Download PDF Report – Export a full analysis report, including findings and predictive insights.

This tool makes time series analysis accessible and actionable for data-driven decision-making. 🚀