Retail Price Optimization

“The moment you make a mistake in pricing, you’re eating into your reputation”

@kaggle.suddharshan_retail_price_optimization

Table List

1 table(53.44 KB)

Retail Price

@kaggle.suddharshan_retail_price_optimization.retail_price

53.44 KB
676 rows
30 columns

product_id Product Id	product_category_name Product Category Name	month_year Month Year	qty Qty	total_price Total Price	freight_price Freight Price	unit_price Unit Price	product_name_lenght Product Name Lenght	product_description_lenght Product Description Lenght	product_photos_qty Product Photos Qty	product_weight_g Product Weight G	product_score Product Score	customers Customers	weekday Weekday	weekend Weekend	holiday Holiday	month Month	year Year	s S	volume Volume	comp_1 Comp 1	ps1 Ps1	fp1 Fp1	comp_2 Comp 2	ps2 Ps2	fp2 Fp2	comp_3 Comp 3	ps3 Ps3	fp3 Fp3	lag_price Lag Price
bed1	bed_bath_table	01-05-2017	1	45.95	15.1	45.95	39	161	2	350	4	57	23	8	1	5	2017	10.26739356	3800	89.9	3.9	15.01189655	215	4.4	8.76	45.95	4	15.1	45.9
bed1	bed_bath_table	01-06-2017	3	137.85	12.93333333	45.95	39	161	2	350	4	61	22	8	1	6	2017	6.503115265	3800	89.9	3.9	14.76921569	209	4.4	21.322	45.95	4	12.93333333	45.95
bed1	bed_bath_table	01-07-2017	6	275.7	14.84	45.95	39	161	2	350	4	123	21	10	1	7	2017	12.07165109	3800	89.9	3.9	13.99383333	205	4.4	22.1959322	45.95	4	14.84	45.95
bed1	bed_bath_table	01-08-2017	4	183.8	14.2875	45.95	39	161	2	350	4	90	23	8	1	8	2017	9.293873313	3800	89.9	3.9	14.65675676	199.5098039	4.4	19.41288462	45.95	4	14.2875	45.95
bed1	bed_bath_table	01-09-2017	2	91.9	15.1	45.95	39	161	2	350	4	54	21	9	1	9	2017	5.555555556	3800	89.9	3.9	18.77652174	163.3987097	4.4	24.3246875	45.95	4	15.1	45.95
bed1	bed_bath_table	01-10-2017	3	137.85	15.1	45.95	39	161	2	350	4	50	22	9	2	10	2017	8.333333333	3800	89.9	3.9	21.57214286	45.95	4	15.1	45.95	4	15.1	45.95
bed1	bed_bath_table	01-11-2017	11	445.85	15.83272727	40.53181818	39	161	2	350	4	97	22	8	4	11	2017	30.55555556	3800	89.9	3.9	16.294	40.53181818	4	15.83272727	40.53181818	4	15.83272727	45.95
bed1	bed_bath_table	01-12-2017	6	239.94	15.23	39.99	39	161	2	350	4	41	21	10	1	12	2017	16.66666667	3800	88.48823529	3.9	18.89833333	39.99	4	15.23	39.99	4	15.23	40.53181818
bed1	bed_bath_table	01-01-2018	19	759.81	16.53368421	39.99	39	161	2	350	4	62	23	8	2	1	2018	17.75700935	3800	86.9	3.9	19.38352941	39.99	4	16.53368421	39.99	4	16.53368421	39.99
bed1	bed_bath_table	01-02-2018	18	719.82	13.74944444	39.99	39	161	2	350	4	62	20	8	2	2	2018	16.82242991	3800	86.9	3.9	19.20909091	39.99	4	13.74944444	39.99	4	13.74944444	39.99


CREATE TABLE retail_price (
  "product_id" VARCHAR,
  "product_category_name" VARCHAR,
  "month_year" VARCHAR,
  "qty" BIGINT,
  "total_price" DOUBLE,
  "freight_price" DOUBLE,
  "unit_price" DOUBLE,
  "product_name_lenght" BIGINT,
  "product_description_lenght" BIGINT,
  "product_photos_qty" BIGINT,
  "product_weight_g" BIGINT,
  "product_score" DOUBLE,
  "customers" BIGINT,
  "weekday" BIGINT,
  "weekend" BIGINT,
  "holiday" BIGINT,
  "month" BIGINT,
  "year" BIGINT,
  "s" DOUBLE,
  "volume" BIGINT,
  "comp_1" DOUBLE,
  "ps1" DOUBLE,
  "fp1" DOUBLE,
  "comp_2" DOUBLE,
  "ps2" DOUBLE,
  "fp2" DOUBLE,
  "comp_3" DOUBLE,
  "ps3" DOUBLE,
  "fp3" DOUBLE,
  "lag_price" DOUBLE
);