postgreSQL $-$ PART $1$: Creating a table using the following attributes: sale$\_$date,sale$\_$year,sale$\_$month,age,gender,country,state,category,sub$\_$category,quantity,unit$\_$cost$,$unit$\_$price,cost,revenue: Please use the following instructions: PART $1$ Creating the Table and Importing the Data

$1.$ Create the table with appropriate data types

a$.$ Name the table customer$\_$spending

b$.$ Reuse the column titles from the csv$,$ do not change these

c$.$ When selecting data types for your tables, ensure they accommodate the full

range of values and avoid truncating any values. Ensure that decimals, lengths,

and other specifications are sufficient for all data to be imported completely.

i$.$ You must declare precision and scale when applicable.

ii$.$ Go bigger if needed$-$ you will not lose points for adding extra space but

you will lose points if your data types do not accommodate all values. PART $2$: Please note that column names in bold to help you identify the columns from the table to be

used in each question. However, these aren't necessarily the columns that your query output

should return. Be sure to read each question carefully. Ensure results show all expected

decimal places unless otherwise specified! Remember, the data types you declared can

influence the outcome of your calculations in PostgreSQL.

$1.$ Write a query that returns each category and the corresponding total revenue for that

category for the sale$\_$year $2016.$ The output should be arranged alphabetically.

$2.$ Write a query that returns a list of sub$\_$categories and their corresponding average

unit$\_$price, average unit$\_$cost$,$ as well as the difference between these two values

$($name this column margin$)$ for the sale$\_$year $2015.$ Organize the results alphabetically.

$3.$ Write a query that returns the total number of female buyers $($gender$)$ who made

purchases in the Clothing category.

$4.$ Write a query that returns the age, sub$\_$cateogry, average quantity $($as a whole

number$),$ and average cost of products purchased by each age and sub$\_$category.

Output should show the columns in the same order they are listed. Organize the data by

age, oldest to youngest, and then by sub$\_$category alphabetically.

$5.$ Write a query that returns a list of countries where more than $30$ transactions were

made by customers between the ages of $18-25($inclusive$).$

$6.$ Write a query that returns a list of sub$\_$categories along with their average quantity

and average cost, both rounded to $2$ decimal places, and named as avg$\_$quantity and

avg$\_$cost respectively. Only include sub$\_$categories that have at least $10$ records in the

data set. Organize the data by sub$\_$category alphabetically.

$7.$ Write a query that returns each sub$\_$cateogry and their respective total quantity and

total revenue for male buyers $($gender$),$ in the sale$\_$year of $2016.$

$8.$ Write a query to determine each country$$s total revenue generated from sales, sorted

alphabetically.

$9.$ Write a query to determine the highest unit$\_$cost$,$ lowest unit$\_$cost$,$ and average

unit$\_$cost for each gender in each category. The output columns should be gender,

category, high$\_$cost$,$ low$\_$cost$,$ avg$\_$cost$.$ Organize the results by gender and then

category.

$10.$ Write a query to return the country that has the highest average revenue. Your output

columns should be country and high$\_$sales.

Hint: To obtain the highest value, you will need to return only one row from your results. Think of

how you$$ll need to sort the output and then see this link if you need guidance on how to select a

single row.