aniket1899 / instacart-mba-rfm

project-aarvind-ankale

DataSet and Large EDA Notebook Link - https://drive.google.com/drive/folders/1yu3rMS7tAvCzQQiyA1dWZzNi_OIyktf3?usp=sharing

File descriptions Each entity (customer, product, order, aisle, etc.) has an associated unique id. Most of the files and variable names should be self-explanatory.

aisles.csv

 aisle_id,aisle  
 1,prepared soups salads  
 2,specialty cheeses  
 3,energy granola bars  
 ...

departments.csv

 department_id,department  
 1,frozen  
 2,other  
 3,bakery  
 ...

order_products__*.csv These files specify which products were purchased in each order. order_products__prior.csv contains previous order contents for all customers. 'reordered' indicates that the customer has a previous order that contains the product. Note that some orders will have no reordered items. You may predict an explicit 'None' value for orders with no reordered items. See the evaluation page for full details.

 order_id,product_id,add_to_cart_order,reordered  
 1,49302,1,1  
 1,11109,2,1  
 1,10246,3,0  
 ...

orders.csv This file tells to which set (prior, train, test) an order belongs. You are predicting reordered items only for the test set orders. 'order_dow' is the day of week.

 order_id,user_id,eval_set,order_number,order_dow,order_hour_of_day,days_since_prior_order  
 2539329,1,prior,1,2,08,  
 2398795,1,prior,2,3,07,15.0  
 473747,1,prior,3,3,12,21.0  
 ...

products.csv

 product_id,product_name,aisle_id,department_id
 1,Chocolate Sandwich Cookies,61,19  
 2,All-Seasons Salt,104,13  
 3,Robust Golden Unsweetened Oolong Tea,94,7  
 ...