Machine learning model using Python 3.6 Libraries needed: pandas, numpy, seaborn, matplotlib, plotly, datetime (src/data/requirements.txt)
Topic: Sales volume of a supermarket and its forecast, data of 20 months.
EDA file is the first notebook, it prepares the data for the model.
MODEL file is the notebook with SARIMA model (seasonal data)
A glance of the model:
NOTES:
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The csv file is in drive https://drive.google.com/file/d/1kULFqfxUwXamPo7GZrmBhufDNsCSarDo/view?usp=sharing
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Data was downloaded from https://datamarket.es/#productos-de-supermercados-dataset
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It is required to change the source of the jupyter notebook, the directory of the file csv ("url" on EDA_MercadonaTimeSeries notebook)