create table products_extended (
id INT primary key, 
name VARCHAR(50) not null,
category VARCHAR(50) not null,
price INT,
in_stock BOOLEAN default true,
email_support VARCHAR(50)
);

insert into products_extended (id, name, category, price, in_stock, email_support)
values (1, 'iPhone 14', 'smartphone', 799, true, 'iphone@apple.com'),
(2, 'MacBook Air', 'laptop', 1199,	false,	NULL),
(3, 'Galaxy S22', 'smartphone',	699,	true,	'galaxy@support.com'),
(4, 'ThinkPad X1',	'laptop',	1399,	true,	'thinkpad@lenovo.com'),
(5, 'iPad Pro',	'tablet',	999,	false,	'ipad@apple.com'),
(6, 'Kindle Paperwhite',	'ebook_reader',	149,	true,	NULL),
(7, 'Mi Band 7',	'smartwatch',	49,	true,	'miband@xiaomi.com'),
(8, 'Surface Pro',	'tablet',	1299,	true,	'surface@microsoft.com'),
(9, 'Honor Pad X9',	'tablet',	219,	true,	'honor@support.com'),
(10, 'Dell XPS 13',	'laptop',	1099,	false,	'dell@support.com');

alter table products_extended
alter column price type DECIMAL(10, 2)

------------------ Задание №1  (По нему ты говорил, что нечитаемо, объясни как переделать pls <3)
with email_false as (select * from 
(
select category, name, price, email_support, 
row_number() over (partition by category order by price desc) as rn
from products_extended 
where email_support is null) 
where rn = 1
),

email_true as (select * from 
(
select category, name, price, email_support, 
row_number() over (partition by category order by price desc) as rn
from products_extended 
where email_support is not null) 
where rn = 1
)

select category, name, price, email_support from email_false
union all
select category, name, price, email_support from email_true
order by category, price desc

---------------------- Задание №2 (Переделал с двух оконок в одном запросе на СТЕ с одной оконкой внутри)
with get_data as (
select name, category, price,
LEAD(price) OVER (PARTITION BY category order by price) AS next_price
from products_extended
)

select name, category, price, next_price,
price - next_price AS diff
from get_data

--------------------- Задание №3
select category, name, price,
SUM(price) over (partition by category order by price) as cumulative_sales
from products_extended

---------------------- Задание №4
with get_data as (
select category, name, price, AVG(price) over (partition by category) as avg_price
from products_extended
)
select category, name, price, avg_price, 
case when price > avg_price then true else false end as is_above_avg
from get_data