Restaurants Revenue Prediction

Predict the Restaurants monthly revenue using different methods

@kaggle.mrsimple07_restaurants_revenue_prediction

Table List

1 table(45.49 KB)

Restaurant Revenue 1

@kaggle.mrsimple07_restaurants_revenue_prediction.restaurant_revenue_1

45.49 KB
1000 rows
8 columns

number_of_customers Number Of Customers	menu_price Menu Price	marketing_spend Marketing Spend	cuisine_type Cuisine Type	average_customer_spending Average Customer Spending	promotions Promotions	reviews Reviews	monthly_revenue Monthly Revenue
61	43.11763548709968	12.66379252026928	Japanese	36.23613252393598		45	350.9120399867156
24	40.02007699061254	4.577892096932272	Italian	17.95256243749612		36	221.3190913292622
81	41.98148523678063	4.65291077125362	Japanese	22.600420287336984	1	91	326.52976287588587
70	43.00530706771189	4.416052595712783	Italian	18.984097602995394	1	59	348.19057312560795
30	17.456199471525764	3.47505191324589	Italian	12.766142708740048	1	30	185.0091205967936
92	19.42766984259999	13.114473451233126	American	43.09994966542693	1	10	399.8675067311068
96	35.35034254880709	16.96031770498803	American	20.181621716866445		86	496.6536867303593
84	46.31464521850064	14.486349393533224	Italian	28.921100133720827	1	1	417.1586067140847
84	22.647863291859785	15.841872675210864	American	11.732610930172475		26	352.148065230514
97	33.53226703180226	8.095968581703996	Italian	37.97357865010572		98	272.7935167604014


CREATE TABLE restaurant_revenue_1 (
  "number_of_customers" BIGINT,
  "menu_price" DOUBLE,
  "marketing_spend" DOUBLE,
  "cuisine_type" VARCHAR,
  "average_customer_spending" DOUBLE,
  "promotions" BIGINT,
  "reviews" BIGINT,
  "monthly_revenue" DOUBLE
);