Some useful Queries

Link of the dataset for the following queries

https://drive.google.com/file/d/1KhkV8f76UoCq3sfqBGFKHZBERgm4pfa8/view?usp=sharing

-- Select everything from sales table

select * from sales;

-- Show just a few columns from sales table

select SaleDate, Amount, Customers from sales;
select Amount, Customers, GeoID from sales;

-- Adding a calculated column with SQL

Select SaleDate, Amount, Boxes, Amount / boxes  from sales;

-- Naming a field with AS in SQL

Select SaleDate, Amount, Boxes, Amount / boxes as 'Amount per box'  from sales;

-- Using WHERE Clause in SQL

select * from sales
where amount > 10000;

-- Showing sales data where amount is greater than 10,000 by descending order
select * from sales
where amount > 10000
order by amount desc;

-- Showing sales data where geography is g1 by product ID &
-- descending order of amounts

select * from sales
where geoid='g1'
order by PID, Amount desc;

-- Working with dates in SQL

Select * from sales
where amount > 10000 and SaleDate >= '2022-01-01';

-- Using year() function to select all data in a specific year

select SaleDate, Amount from sales
where amount > 10000 and year(SaleDate) = 2022
order by amount desc;

-- BETWEEN condition in SQL with < & > operators

select * from sales
where boxes >0 and boxes <=50;

-- Using the between operator in SQL

select * from sales
where boxes between 0 and 50;

-- Using weekday() function in SQL

select SaleDate, Amount, Boxes, weekday(SaleDate) as 'Day of week'
from sales
where weekday(SaleDate) = 4;

-- Working with People table

select * from people;

-- OR operator in SQL

select * from people
where team = 'Delish' or team = 'Jucies';

-- IN operator in SQL

select * from people
where team in ('Delish','Jucies');

-- LIKE operator in SQL

select * from people
where salesperson like 'B%';

select * from people
where salesperson like '%B%';

select * from sales;

-- Using CASE to create branching logic in SQL

select 	SaleDate, Amount,
		case 	when amount < 1000 then 'Under 1k'
				when amount < 5000 then 'Under 5k'
                when amount < 10000 then 'Under 10k'
			else '10k or more'
		end as 'Amount category'
from sales;

-- GROUP BY in SQL

select team, count(*) from people
group by team