Dataset from Zenodo · Dataman
BigMart Retail Sales
- License
- cc-bycommercial use allowed
- This license allows commercial use. Usually you must credit the author; read the license for the exact terms.
- Formats
- CSV
- Size
- 1.4 MB
- Updated
- May 2, 2022
Description
Nothing ever becomes real till it is experienced. -John Keats While we don't know the context in which John Keats mentioned this, we are sure about its implication in data science. While you would have enjoyed and gained exposure to real world problems in this challenge, here is another opportunity to get your hand dirty with this practice problem. Problem Statement : The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and find out the sales of each product at a particular store. Using this model, BigMart will try to understand the properties of products and stores which play a key role in increasing sales. Please note that the data may have missing values as some stores might not report all the data due to technical glitches. Hence, it will be required to treat them accordingly. Data : We have 14204 samples in data set. Variable Description Item Identifier : A code provided for the item of sale Item Weight : Weight of item Item Fat Content : A categorical column of how much fat is present in the item…
Description from Zenodo, shortened.
Files (1)
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