Name: Meal Delivery Company
Creator: Kaggle
License: https://www.gnu.org/licenses/gpl.html

About this Dataset

Meal Delivery Company

Context

Your client is a meal delivery company which operates in multiple cities. They have various fulfillment centers in these cities for dispatching meal orders to their customers. The client wants you to help these centers with demand forecasting for upcoming weeks so that these centers will plan the stock of raw materials accordingly.

The replenishment of majority of raw materials is done on weekly basis and since the raw material is perishable, the procurement planning is of utmost importance. Secondly, staffing of the centers is also one area wherein accurate demand forecasts are really helpful. Given the following information, the task is to predict the demand for the next 10 weeks (Weeks: 146-155) for the center-meal combinations in the test set:

Historical data of demand for a product-center combination (Weeks: 1 to 145)
Product(Meal) features such as category, sub-category, current price and discount
Information for fulfillment center like center area, city information etc.

Content

Weekly Demand data (train.csv): Contains the historical demand data for all centers

fulfilment_center_info.csv: Contains information for each fulfillment center

meal_info.csv: Contains information for each meal being served

Acknowledgements

I don't own this data. This data is was par of Machine Learning Hackathon held jointly by Analytics Vidhya & Genpact during Dec 15 2018 00:00 GMT+0530 to Dec 16 2018 23:59 GMT+0530

Inspiration

What can you do with the data? What insights can you get? What else can you think of?
All the best.

Tables

Fulfilment Center Info

@kaggle.ghoshsaptarshi_av_genpact_hack_dec2018.fulfilment_center_info

5.13 kB
77 rows
5 columns

CREATE TABLE fulfilment_center_info (
  "center_id" BIGINT,
  "city_code" BIGINT,
  "region_code" BIGINT,
  "center_type" VARCHAR,
  "op_area" DOUBLE
);

Meal Info

@kaggle.ghoshsaptarshi_av_genpact_hack_dec2018.meal_info

3.19 kB
51 rows
3 columns

CREATE TABLE meal_info (
  "meal_id" BIGINT,
  "category" VARCHAR,
  "cuisine" VARCHAR
);

Test

@kaggle.ghoshsaptarshi_av_genpact_hack_dec2018.test

343.94 kB
32,573 rows
8 columns

CREATE TABLE test (
  "id" BIGINT,
  "week" BIGINT,
  "center_id" BIGINT,
  "meal_id" BIGINT,
  "checkout_price" DOUBLE,
  "base_price" DOUBLE,
  "emailer_for_promotion" BIGINT,
  "homepage_featured" BIGINT
);

Train

@kaggle.ghoshsaptarshi_av_genpact_hack_dec2018.train

4.63 MB
456,548 rows
9 columns

CREATE TABLE train (
  "id" BIGINT,
  "week" BIGINT,
  "center_id" BIGINT,
  "meal_id" BIGINT,
  "checkout_price" DOUBLE,
  "base_price" DOUBLE,
  "emailer_for_promotion" BIGINT,
  "homepage_featured" BIGINT,
  "num_orders" BIGINT
);