E- Commerce Dataset

E-Commerce Dataset with Products, Customers, Sales Trends, and Shipping Insights

@kaggle.malaiarasugraj_e_commerce_dataset

Table List

1 table(16.28 MB)

Diversified Ecommerce Dataset

@kaggle.malaiarasugraj_e_commerce_dataset.diversified_ecommerce_dataset

16.28 MB
1000000 rows
16 columns

product_id Product ID	product_name Product Name	category Category	price Price	discount Discount	tax_rate Tax Rate	stock_level Stock Level	supplier_id Supplier ID	customer_age_group Customer Age Group	customer_location Customer Location	customer_gender Customer Gender	shipping_cost Shipping Cost	shipping_method Shipping Method	return_rate Return Rate	seasonality Seasonality	popularity_index Popularity Index
P6879	Jacket	Apparel	53.85	5	15	150	S535	35-44	New York, USA	Male	23.32	Standard	4.49	Yes	56
P5132	Camera	Electronics	761.26	10	15	224	S583	25-34	London, UK	Female	20.88	Overnight	16.11	No	79
P2941	Sneakers	Footwear	1756.76	5	8	468	S118	25-34	Tokyo, Japan	Non-Binary	16.43	Standard	4.93	No	40
P8545	Cookbooks	Books	295.24	10	15	25	S104	18-24	Paris, France	Female	27.49	Standard	1.31	No	93
P4594	Camera	Electronics	832	10	12	340	S331	55+	Tokyo, Japan	Male	45.93	Overnight	4.37	No	56
P1388	Non-Fiction	Books	584.19	15	8	204	S523	45-54	Singapore	Female	40.12	Express	19.03	No	91
P7313	Running Shoes	Footwear	1343.95		10	493	S878	18-24	Sydney, Australia	Female	35.91	Overnight	17.73	Yes	41
P1060	Blender	Home Appliances	1873.52		15	349	S396	18-24	Phoenix, USA	Male	46.42	Standard	4.79	No	60
P1241	Fiction	Books	1586.65	25	5	237	S183	35-44	Cape Town, South Africa	Male	33.1	Express	2.55	Yes	90
P9687	Heels	Footwear	1975.69	20	8	132	S672	18-24	New York, USA	Female	5.25	Overnight	16.5	Yes	96


CREATE TABLE diversified_ecommerce_dataset (
  "product_id" VARCHAR,
  "product_name" VARCHAR,
  "category" VARCHAR,
  "price" DOUBLE,
  "discount" BIGINT,
  "tax_rate" BIGINT,
  "stock_level" BIGINT,
  "supplier_id" VARCHAR,
  "customer_age_group" VARCHAR,
  "customer_location" VARCHAR,
  "customer_gender" VARCHAR,
  "shipping_cost" DOUBLE,
  "shipping_method" VARCHAR,
  "return_rate" DOUBLE,
  "seasonality" VARCHAR,
  "popularity_index" BIGINT
);