I just posted the same question. Please respond to this again now that you have added the information. I will also be running this code in a Python environment. Please reflect this.

Below is the code I ran to use sqlite.

$!$pip install sqlalchemy$==1\mathrm{.}3\mathrm{.}23$

import sqlite$3$

$!$pip install ipython$-$sql

$\%$load$\_$ext sql

from google.colab import drive

drive.mount$(\text{'}/$content$/$drive$\text{'})$

$\%$sql sqlite:$////$content$/$drive$/$MyDrive$/$northwind$.$sqlite$3$

$\%\%$sql

SELECT sqlite$\_$version$()$;the code I ran to use sqlite.

Finally, I$\text{'}$m including a modification to my previous code. Please check if this code is correct.

QI$.$ Write a query to retrieve the top $10$order amounts from customers, the product information for those orders, and calculate the sum of the order amounts.

import sqlite$3$

import pandas as pd

conn $=$ sqlite$3.$connect$(\text{'}/$content$/$drive$/$MyDrive$/$northwind$.$sqlite$3\text{'})$ # 'your$\_$database.db$\text{'}.$

query $=\text{'}\text{'}\text{'}$

SELECT

o$.$OrderID,

c$.$CompanyName,

SUM$($od$.$Quantity $*$ od$.$UnitPrice$)$ AS OrderAmount,

p$.$ProductName

FROM

Orders o

INNER JOIN

OrderDetails od ON o$.$OrderID $=$ od$.$OrderID

INNER JOIN

Customers c ON o$.$CustomerID $=$ c$.$CustomerID

INNER JOIN

Products p ON od$.$ProductID $=$ p$.$ProductID

GROUP BY

o$.$OrderID, c$.$CompanyName, p$.$ProductName

ORDER BY

OrderAmount DESC

LIMIT $10$;

$\text{'}\text{'}\text{'}$

df $=$ pd$.$read$\_$sql$\_$query$($query$,$ conn$)$

df

Q$2.$Write a SQL query to find the category in which a customer ordered the most and calculate the total of that category.

import sqlite$3$

import pandas as pd

conn $=$ sqlite$3.$connect$(\text{'}/$content$/$drive$/$MyDrive$/$northwind$.$sqlite$3\text{'})$ # 'your$\_$database.db$\text{'}.$

query$1=\text{'}\text{'}\text{'}$

SELECT c$.$CompanyName,

c$.$Country,

cat.CategoryName,

SUM$($od$.$Quantity $*$ od$.$UnitPrice$)$ AS CategoryTotal

FROM Customers c

INNER JOIN Orders o ON c$.$CustomerID $=$ o$.$CustomerID

INNER JOIN OrderDetails od ON o$.$OrderID $=$ od$.$OrderID

INNER JOIN Products p ON od$.$ProductID $=$ p$.$ProductID

INNER JOIN Categories cat ON p$.$CategoryID $=$ cat.CategoryID

GROUP BY c$.$CompanyName, c$.$Country, cat.CategoryName

ORDER BY CategoryTotal DESC

$\text{'}\text{'}\text{'}$

df$1=$ pd$.$read$\_$sql$\_$query$($query$1,$ conn$)$

df$1$

Q$3.$Write an SQL query to get a list of orders placed by customers in Seattle and calculate the total amount of all orders.

import sqlite$3$

import pandas as pd

conn $=$ sqlite$3.$connect$(\text{'}/$content$/$drive$/$MyDrive$/$northwind$.$sqlite$3\text{'})$ # 'your$\_$database.db$\text{'}.$

query$2=\text{'}\text{'}\text{'}$

SELECT o$.$OrderID,

c$.$CompanyName,

SUM$($od$.$Quantity $*$ od$.$UnitPrice$)$ AS TotalAmount

FROM Orders o

INNER JOIN OrderDetails od ON o$.$OrderID $=$ od$.$OrderID

INNER JOIN Customers c ON o$.$CustomerID $=$ c$.$CustomerID

WHERE c$.$City $=$ 'Seattle'

GROUP BY o$.$OrderID, c$.$CompanyName

ORDER BY TotalAmount DESC

$\text{'}\text{'}\text{'}$

df$2=$ pd$.$read$\_$sql$\_$query$($query$2,$ conn$)$

df$2$

Q$4.$Write a SQL query that lists the names of the vendor companies that provided the products and sorts them in order of total revenue if the revenue generated by the products taken by employees with the job title "Sales Representative" is more than $$10,000.$What is the total of all vendor sales?

import sqlite$3$

import pandas as pd

conn $=$ sqlite$3.$connect$(\text{'}/$content$/$drive$/$MyDrive$/$northwind$.$sqlite$3\text{'})$ # 'your$\_$database.db$\text{'}.$

query$3=\text{'}\text{'}\text{'}$

SELECT

s$.$SupplierID,

s$.$CompanyName,

SUM$($od$.$Quantity $*$ od$.$UnitPrice$)$ AS Revenue

FROM

Suppliers s

INNER JOIN

Products p ON s$.$SupplierID $=$ p$.$SupplierID

INNER JOIN

OrderDetails od ON p$.$ProductID $=$ od$.$ProductID

INNER JOIN

Orders o ON od$.$OrderID $=$ o$.$OrderID

INNER JOIN

Employees e ON o$.$EmployeeID $=$ e$.$EmployeeID

WHERE

e$.$Title $=$ 'Sales Representative' $--$ Corrected column name for job title

GROUP BY

s$.$SupplierID, s$.$CompanyName

ORDER BY

Revenue DESC;

$\text{'}\text{'}\text{'}$

df$3=$ pd$.$read$\_$sql$\_$query$($query$3,$ conn$)$

print$("$Revenue by Supplier:"$)$

print$($df$3)$

query$4=\text{'}\text{'}\text{'}$

SELECT

SUM$($od$.$Quantity $*$ od$.$UnitPrice$)$ AS TotalVendorSales

FROM

OrderDetails od

INNER JOIN

Products p ON od$.$ProductID $=$ p$.$ProductID

INNER JOIN

Suppliers s ON p$.$SupplierID $=$ s$.$SupplierID;

$\text{'}\text{'}\text{'}$

df$4=$ pd$.$read$\_$sql$\_$query$($query$4,$ conn$)$

print$("$

Total Vendor Sales:"$)$

print$($df$4)$

Q$5.$The owner of Northwind Traders wants to know if his staff is deployed effectively. For example, he might assume that there are more employees in areas where there are more orders for goods, or that there are more employees in areas with high sales. You need to analyze the staffing status so that he can make a decision. You analyze the data in SQL and use the quantitative evidence from your analysis to form an opinion about the staffing.

import sqlite$3$

import pandas as pd

query$5=\text{'}\text{'}\text{'}$

SELECT Region, COUNT$(*)$ AS NumOrders

FROM Customers

GROUP BY Region

ORDER BY NumOrders DESC;

$\text{'}\text{'}\text{'}$

df$5=$ pd$.$read$\_$sql$\_$query$($query$5,$ conn$)$

print$("$:$")$

print$($df$5)$

query$6=\text{'}\text{'}\text{'}$

SELECT Region, COUNT$(*)$ AS NumEmployees

FROM Employees

GROUP BY Region

ORDER BY NumEmployees DESC;

$\text{'}\text{'}\text{'}$

df$6=$ pd$.$read$\_$sql$\_$query$($query$6,$ conn$)$

print$("$:$")$

print$($df$6)$