given the Database Schema. write SQL queries for the following.

$1.$List of booking id that was shipped by Air with departure date in Jan $2021$

$2.$ List the number of bookings by each mode of shipment id with departure date

in Jan $2021$

$3.$ List the bookings $($by booking$\_$id$)$ invoiced to FurniturePlus $($customer id:

$214598)$ that departed in Jan $2021$

$4.$ List the highest valued $10$ invoices $($by invoice$\_$id$)$ invoiced in GBP that were

sent in Jan $2021$

$5.$ Return the list of customer names that had more than $10$ unique invoices sent

in Jan $2021.$

$6.$ Return the the list of legs and the amount invoiced to each leg in invoice

currency of FurniturePlus$($customer id: $214598)$ first ever created shipment.

Hint: the integer id in the booking table is unique and auto$-$increment.

$7.$ Return the list of the top $10$ customers, in descending order, by sales $($in

invoice currency$)$ invoiced in GBP in Jan $2021.$ In addition, for each of these

customers, return the next customer $($by sales in invoice currency$)$ from in the

same country, the amount of sales and the difference in sales between the

current and the next customer from the same country. Hint: columns needed:

o customer$\_$name

o total$\_$sales

o lag$\_$customer$\_$name$\_$same$\_$country

o lag$\_$total$\_$sales$\_$same$\_$country

o difference$\_$in$\_$sales

Python:

$1.$ Write a python function which reads json data from public API

$($ api.coindesk.com$/$v$1/$bpi$/$currentprice$.$json$)$ and do below

a$.$ Flatten the data in meaningful manner

b$.$ insert the data into table

i$.$ Keep a CSV file instead for the table.

$2.$ Create a Analysis report on the above data basis your inferences.