Big Market sales

In this post we worked in Python from beginning to end. It’s about exploring, cleaning, detecting the missing values of store data and optimize it in order to predict the sales in the future…we used some algorithms to learn from our training data but not having the sales from our test data we couldn’t  check our accuracy.

We answered at interesting questions, like: how the location of the store affect sales, or the location of the product on the shelf or could maybe the weight of the product have a say in this?

In conclusion if location is an important factor of the sales and is not a surprise, what’s a surprise at leas for me is that on the second place is the weight of the product. The price and the visibility of the product on the shelf comes right after.