There are errors in the code below. Provide the line number in which the error occurs and the corrected code. import pandas as pd

products $=[$

$\{"$ProductID$"$: $1,$ "ProductName": "Laptop", "Category": "Electronics", "Price": $999\mathrm{.}99,$ "Stock": $10\},$

$\{"$ProductID$"$: $2,$ "ProductName": "Chair", "Category": "Furniture", "Price": $85\mathrm{.}50,$ "Stock": $5\},$

$\{"$ProductID$"$: $3,$ "ProductName": "Tablet", "Category": "Electronics", "Price": $199\mathrm{.}99,$ "Stock": $8\},$

$\{"$ProductID$"$: $4,$ "ProductName": "Desk", "Category": "Furniture", "Price": $120\mathrm{.}00,$ "Stock": $7\},$

$\{"$ProductID$"$: $5,$ "ProductName": "Smartphone", "Category": "Electronics", "Price": $699\mathrm{.}99,$ "Stock": $15\},$

$\{"$ProductID$"$: $6,$ "ProductName": "Bookshelf", "Category": "Furniture", "Price": $150\mathrm{.}00,$ "Stock": $3\},$

$\{"$ProductID$"$: $7,$ "ProductName": "Headphones", "Category": "Electronics", "Price": $59\mathrm{.}99,$ "Stock": $28\},$

$\{"$ProductID$"$: $8,$ "ProductName": "Microwave", "Category": "Appliances", "Price": $89\mathrm{.}99,$ "Stock": $12\},$

$\{"$ProductID$"$: $9,$ "ProductName": "Refrigerator", "Category": "Appliances", "Price": $499\mathrm{.}99,$ "Stock": $2\},$

$\{"$ProductID$"$: $10,$ "ProductName": "Lamp", "Category": "Furniture", "Price": $45\mathrm{.}00,$ "Stock": $10\}$

$]$

df $=$ pd$.$DataFrame$($products$)$

electronics $=$ df$[$df$["$Category$"]=$ "Electronics"$]$

print$("$Electronics:

$",$ electronics$)$

price$\_$range $=$ df$[($df$["$Price$"]>=50)$ and $($df$["$Price

print$("$Price between $50$ and $150$:

$",$ price$\_$range$)$

in$\_$stock $=$ df$[$df$["$Stock$"]>0]$

print$("$In Stock:

$",$ in$\_$stock$)$

furniture$\_$under$\_200=$ df$[($df$["$Category$"]==$ "Furniture"$)$ & $($df$["$Price$"]<mtext></mtext><mn>2</mn><mn>0</mn><mn>0</mn><mi>)</mi>$ & $($df$["$Stock$"]>5)]$

print$("$Furniture under $200$ with more than $5$ in stock:

$",$ furniture$\_$under$\_200)$

df$[\text{'}$TotalStockValue$\text{'}]=$ df$[\text{'}$Price$\text{'}]*$ df$[\text{'}$Quantity$\text{'}]$

stock$\_$value$\_$by$\_$category $=$ df$.$groupby$(\text{'}$Category$\text{'})[\text{'}$TotalStockValue$\text{'}].$sum$()$

print$("$Total Stock Value by Category:

$",$ stock$\_$value$\_$by$\_$category$)$

most$\_$expensive $=$ df$[$df$["$Price$"]=$ df$["$Price$"].$max$()]$

print$("$Most Expensive Product:

$",$ most$\_$expensive$)$

contains$\_$phone $=$ df$[$df$["$ProductName$"].$str$.$contain$("$phone$",$ case$=$False$)]$

print$("$Products containing 'phone":

$",$ contains$\_$phone$)$

df$\_$filtered $=$ df$[$df$["$Stock$"]>=5]$

print$("$Products with Stock $>=5$:

$",$ df$\_$filtered$)$

new$\_$product $=\{"$ProductID$"$: $11,$ "ProductName": "Air Conditioner", "Category": "Appliances",

"Price": $299\mathrm{.}99,$ "Stock": $6\}$

df $=$ pd$.$concat$([$df$,$ new$\_$product$],$ ignore$\_$index$=$True$)$

print$("$DataFrame after adding new product:

$",$ df$)$

sorted$\_$by$\_$price $=$ df$.$sort$\_$values$($by$=$"Costs", ascending$=$False$)$

print$("$Sorted by Price $($Descending$)$:

$",$ sorted$\_$by$\_$price$)$