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Tables Data
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Tables Data
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# Roll-Company-SQL-Project
The project involves analysing the Roll Company data which I prepared by myself. I used DBeaver to run my SQL queries and Google Spreadsheets to discover relationships between two quantities, identify trends, and more.
CREATE TABLE driver(driver_id integer,reg_date date);
INSERT INTO driver(driver_id,reg_date)
VALUES (1,'01-01-2021'),
(2,'01-03-2021'),
(3,'01-08-2021'),
(4,'01-15-2021');
CREATE TABLE ingredients(ingredients_id integer,ingredients_name varchar(60));
INSERT INTO ingredients(ingredients_id,ingredients_name)
VALUES (1,'Paneer'),
(2,'Chilli Sauce'),
(3,'Chicken'),
(4,'Cheese'),
(5,'Kebab'),
(6,'Mushrooms'),
(7,'Onions'),
(8,'Egg'),
(9,'Peppers'),
(10,'Schezwan Sauce'),
(11,'Tomatoes'),
(12,'Mayonnaise');
CREATE TABLE rolls(roll_id integer,roll_name varchar(30));
INSERT INTO rolls(roll_id ,roll_name)
VALUES (1,'Non Veg Roll'),
(2,'Veg Roll');
CREATE TABLE rolls_recipes(roll_id integer,ingredients varchar(24));
INSERT INTO rolls_recipes(roll_id ,ingredients)
VALUES (1,'2,3,4,5,6,7,8,10'),
(2,'1,4,6,7,9,10,11,12');
CREATE TABLE driver_order(order_id integer,driver_id integer,pickup_time datetime,distance VARCHAR(7),duration VARCHAR(10),cancellation VARCHAR(23));
INSERT INTO driver_order(order_id,driver_id,pickup_time,distance,duration,cancellation)
VALUES
(1,1,'2022-01-01 18:15:34','20km','32 mins',''),
(2,1,'2022-01-01 19:10:54','20km','27 mins',''),
(3,1,'2022-01-03 00:12:37','13.4km','20 mins','NaN'),
(4,2,'2022-01-04 13:53:03','23.4km','40 mins','NaN'),
(5,3,'2022-01-08 21:10:57','10km','15 mins','NaN'),
(6,3,null,null,null,'Cancellation'),
(7,2,'2022-01-08 21:30:45','25km','25 mins',null),
(8,2,'2022-01-10 00:15:02','23.4km','15 mins',null),
(9,2,null,null,null,'Customer Cancellation'),
(10,1,'2022-01-11 18:50:20','10km','10 mins',null);
CREATE TABLE customer_orders(order_id integer, customer_id integer, roll_id integer, not_include_items VARCHAR(4), extra_items_included VARCHAR(4), order_date datetime);
INSERT INTO customer_orders(order_id, customer_id, roll_id, not_include_items, extra_items_included, order_date)
VALUES
(1,101,1,'','','2022-01-01 18:05:02'),
(2,101,1,'','','2022-01-01 19:00:52'),
(3,102,1,'','','2022-01-02 23:51:23'),
(3,102,2,'','NaN','2022-01-02 23:51:23'),
(4,103,1,'4','','2022-01-04 13:23:46'),
(4,103,1,'4','','2022-01-04 13:23:46'),
(4,103,2,'4','','2022-01-04 13:23:46'),
(5,104,1,null,'1','2022-01-08 21:00:29'),
(6,101,2,null,null,'2022-01-08 21:03:13'),
(7,105,2,null,'1','2022-01-08 21:20:29'),
(8,102,1,null,null,'2022-01-09 23:54:33'),
(9,103,1,'4','1,5','2022-01-10 11:22:59'),
(10,104,1,null,null,'2022-01-11 18:34:49'),
(10,104,1,'2,6','1,4','2022-01-11 18:34:49');
delete from driver_order
select * from customer_orders;
select * from driver_order;
select * from ingredients;
select * from driver;
select * from rolls;
select * from rolls_recipes;