Retail Sales Dataset

Unveiling Retail Trends: A Dive into Sales Patterns and Customer Profiles

@kaggle.mohammadtalib786_retail_sales_dataset

Table List

1 table(23.48 KB)

Retail Sales Dataset

@kaggle.mohammadtalib786_retail_sales_dataset.retail_sales_dataset

23.48 KB
1000 rows
9 columns

transaction_id Transaction ID	date Date	customer_id Customer ID	gender Gender	age Age	product_category Product Category	quantity Quantity	price_per_unit Price Per Unit	total_amount Total Amount
1	Fri Nov 24 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST001	Male	34	Beauty	3	50	150
2	Mon Feb 27 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST002	Female	26	Clothing	2	500	1000
3	Fri Jan 13 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST003	Male	50	Electronics	1	30	30
4	Sun May 21 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST004	Male	37	Clothing	1	500	500
5	Sat May 06 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST005	Male	30	Beauty	2	50	100
6	Tue Apr 25 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST006	Female	45	Beauty	1	30	30
7	Mon Mar 13 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST007	Male	46	Clothing	2	25	50
8	Wed Feb 22 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST008	Male	30	Electronics	4	25	100
9	Wed Dec 13 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST009	Male	63	Electronics	2	300	600
10	Sat Oct 07 2023 00:00:00 GMT+0000 (Coordinated Universal Time)	CUST010	Female	52	Clothing	4	50	200


CREATE TABLE retail_sales_dataset (
  "transaction_id" BIGINT,
  "date" TIMESTAMP,
  "customer_id" VARCHAR,
  "gender" VARCHAR,
  "age" BIGINT,
  "product_category" VARCHAR,
  "quantity" BIGINT,
  "price_per_unit" BIGINT,
  "total_amount" BIGINT
);