Task $1$: Employee Analysis

Read the tab$-$delimeted file named 'HOP$\_$RBC$\_$Employees.txt$\text{'}$ and print as $\{$name$\}\{$position$\}\{$years of service$\}$ "years of service"

Examples:

Rick Owner $39$ years of service

Sarah General Manager $15$ years fo service

# Place your Python code here

Task $2$: New Menu Concepts

Use the appropriate function found in the Pandas library to read the CSV file named 'HOP$\_$RBC$\_$New$\_$Menu$\_$Concepts.csv$\text{'}$ into a Pandas DataFrame. The values to be used in the DataFrame columen names are found in the first row of the CSV file. Use the ItemID column as the DataFrame's index.

# Place your Python code here

Task $3$: Calculate the Number of Unique Pizza Creations at Rick's Brick & Cue

Rick's Brick & Cue provides a variety of options for customers to build their own pizza. These options are categorized into four distinct types: crust, sauce, cheese, and toppings. Each category has a range of choices available, and customers can pick one item from each category to make their own pizza.

You are tasked with calculating the total number of unique combinations that can be created, using the data stored in an Excel file named HOP$\_$RBC$\_$Build$\_$Your$\_$Own$\_$Pizza$\_$Options.xlsx$.$ The spreadsheet contains four worksheets:

Crust Options

Sauce Options

Cheese Options

Toppings Options

Assume that a customer can only select one option from each category. Read the data from the Excel file 'HOP$\_$RBC$\_$Build$\_$Your$\_$Own$\_$Pizza$\_$Options.xlsx$\text{'}$ into a single DataFrame. Use a read$\_$excel$()$ function call to read all four worksheets at the same time.

hint: the number of options for a category will be equal to the number of rows in the DataFrame. Recall from an earlier lesson that 'dataframe.shape' returns a tuple containing the number of rows and number of columns in the dataframe. Use this to get the number of rows: i$.$e$.,$ 'dataframe.shape$[0]\text{'},$ where 'dataframe' is the name of your DataFrame.

# Place your Python code here

Task $4$: Competitor Analysis

Rick's Brick & Cue recently acquired a list of competitors in the barbecue restaurant market from a reputable data provider. Rick, the owner, hopes this data will critical insights into the competitive landscape. The data about these competitors was delivered as a JSON file. Your task is to read the JSON file and print a list of competitors. For now, Rick only needs to see the competitor names, locations, and customer rating.

The JSON data is a nested structure. At the highest level is a list of competitors. Here are a few sample rows:

$\{$

"competitors": $[$

$\{$

"name": "Smokey Joe's BBQ$",$

"location": "Austin, TX$",$

"specialty": "Brisket",

"price$\_$range": $"$$$$",$

"customer$\_$rating": $4\mathrm{.}5$

$\},$

$\{$

"name": "Grillmaster's Paradise",

"location": "Memphis, TN$",$

"specialty": "Ribs",

"price$\_$range": $"$$$$",$

"customer$\_$rating": $4\mathrm{.}3$

$\},$

$...$

$\{$

"name": "Prairie Smoke",

"location": "Minneapolis, MN$",$

"specialty": "Wild Game",

"price$\_$range": $"$$$$$",$

"customer$\_$rating": $4\mathrm{.}6$

$\}$

$]$

$\}$

# Place your Python code here

Task $5$: Find the Winning Kid's BBQ Sauce Recipe

Rick's Brick & Cue recently held a unique contest where children aged $8$ and under were invited to submit their special BBQ sauce recipes via the restaurant's app. Parents granted permission for these submissions, and customers then voted for their favorite recipe. Your task is to identify and print out the winning recipe.

The data has been gathered in an XML file named 'HOP$\_$RBC$\_$BBQ$\_$Kids$\_$BBQ$\_$Sauce$\_$Contest.xml$.$

Objectives:

Parse the XML file to read the recipes.

Find the recipe with the most votes.

Print the winning recipe following this format:

First, print the title of the recipe

Second, print the child's name and age

Third, pirnt the number of votes

Fourth, list the ingredients, one per line

Fifth, list the steps for preparing the sauce, one per line

Guidelines:

Loop through each recipe in the XML file

Extract and store the number of votes for each recipe

Compare the number of votes to find the one with the most votes

Extract and print the details of the winning recipe

Hints:

Use the xml$.$etree.ElementTree module for XML parsing

Use the parse function to read the XML file

You might find it useful to use variable$($s$)$ to track the winning recipe as you iterate through them

Example output $($not the actual winner$)$:

Winning Recipe: Mia's Fruity Fizzle

Description: Fruit and fizz, what's not to love?

Number of Votes: $215$

Kid's Name and Age: Mia $(8)$

Ingredients:

$-$ Orange joos

$-$ Sprite

$-$ Hunny

Steps:

$-$ Mixy mix.

$-$ Taste it$,$ yum!