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This repository contains a Jupyter notebook that demonstrates time series analysis and forecasting using ARIMA, auto-ARIMA, and Prophet. Time series analysis is a powerful tool for understanding and predicting future trends, and these techniques are widely used in a variety of fields such as finance, economics, and marketing. The notebook is based
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This repository contains a Jupyter notebook that demonstrates time series analysis and forecasting using ARIMA, auto-ARIMA, and Prophet. The notebook is based on the work of ANDRESHG and has been modified with additional explanations and examples.
Python 3.6 or higher Jupyter Notebook Required Python packages: pandas, numpy, matplotlib, statsmodels, pyramid, fbprophet Installation To use the notebook in this repository, clone or download the repository and install the required packages using pip:
pip install -r requirements.txt ( I will added soon )
To view the notebook, open the time-series-analysis-and-forecasting.ipynb file in Jupyter Notebook. The notebook contains explanations and examples of how to use ARIMA, auto-ARIMA, and Prophet for time series analysis and forecasting.