In-depth analysis of supply chain data using Python to uncover insights on product performance, inventory, suppliers, logistics, and customer behavior. Built in Jupyter Notebook with pandas, numpy, and plotly for data processing and interactive visualizations.

In this project we were supposed to predict Womart Sales using Time Series Approaches, but we weren't allowed to use related libraries and we must've done the calculations with the functions implemented in the script. Different simple methods of prediction are available in this notebook. Hope you enjoy!