Update README.md

README.md

@@ -1,19 +1,59 @@
 ---
 title: SimpleTS
-emoji: 🚀
-colorFrom: red
-colorTo: red
+emoji: 📈
+colorFrom: green
+colorTo: blue
 sdk: docker
 app_port: 8501
 tags:
-- streamlit
+  - streamlit
+  - time-series
+  - forecasting
+  - prophet
+  - arima
+  - holt-winters
 pinned: false
-short_description: Streamlit template space
+short_description: Analyze and forecast time series — no code required.
 ---
 
-# Welcome to Streamlit!
+# SimpleTS
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+Interactive Streamlit dashboard for time series analysis and forecasting. Upload your CSV or use built-in demos.
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+## Author
+Eduardo Nacimiento García  
+📧 enacimie@ull.edu.es  
+📜 Apache 2.0 License
+
+## Features
+- Upload CSV or use daily/monthly/weekly demo datasets
+- Automatic date parsing and time series setup
+- Stationarity test (ADF)
+- Seasonal decomposition (trend, seasonality, residuals)
+- ACF & PACF plots
+- Forecasting models:
+  - Holt-Winters Exponential Smoothing
+  - ARIMA (configurable p,d,q)
+  - Prophet (by Meta)
+- Metrics: MAE, MSE, RMSE
+- Interactive future forecasting
+- Plotly visualizations
+
+## Demo Datasets
+Three built-in demos:
+- **Daily** (1 year, 365 points)
+- **Weekly** (2 years, 104 points)
+- **Monthly** (4 years, 48 points)
+
+## Deployment
+Ready for [Hugging Face Spaces](https://huggingface.co/spaces) (free tier).
+
+> ⚠️ Uses `sdk: docker` — include `Dockerfile`.
+
+## Requirements
+- Python 3.8+
+- Streamlit, pandas, numpy, plotly, statsmodels, prophet, scikit-learn
+
+---
+
+💡 Tip: After uploading, select date/value columns → analyze stationarity & seasonality → choose model → forecast future values!