The goal of this project was to extract useful information about a multi-category online store, using the data that covers a span of time of 7 months, precisely from October 2019 to April 2020. We are asked to analyze the behaviour of the customers in the store according to their actions (views of a particular product, additions to cart and purchase) and particular statistics about the store. For instance, we are going to highlight the overall most selling categories, the brands with the highest average prices, the conversion rate and so on so forth.
We obviously coulnd't upload the data here, due to its dimensions, but if one is eager to download it or simply wants to know better what we're working on, here's the link to the official Kaggle repo.
The repository consists of the following files:
main.ipynb:A Jupyter notebook which provides the solutions to all the research questions. The notebook just contains the answers, there is almost no code here.
functions.py:A Python script containing all the functions used in the
main.ipynb.