This repository contains a Jupyter notebook that focuses on forecasting energy consumption in Denmark using time series analysis. The study employs models like ExponentialSmoothing, Autoregression (AR), ARIMA, and SARIMA with exogenous parameters. It aims to provide an in-depth analysis of energy trends and forecasting accuracy.
To run this notebook, you'll need:
- Python 3.x
- Jupyter Notebook
- Libraries: pandas, numpy, statsmodels, matplotlib, seaborn
Clone the repository to your local machine:
To view and run the notebook:
- Navigate to the cloned directory.
- Start Jupyter Notebook:
Open
TimeSeriesForecastingStudyDenmarkEnergy.ipynb
.
Contributions to this project are welcome! Please fork the repository and submit a pull request with your changes.
For any queries, please reach out to [email protected].