Hello Community members, A solution to last week’s challenge can be found here. We are back with another exciting challenge, and this one is all about hot sauces! A big thank you to James Gust for creating this spicy challenge! This week’s challenge is the first of two parts. For Part 1, you have a collection of individual reviews of hot sauces, but the data is spread across multiple tables due to how it was stored in a relational database. Now, it is your job to bring it all together and extract meaningful insights! Your datasets include the following: * Hot Sauce Data.xlsx: Contains details about the sauce names, manufacturing information, ratings, spiciness, viscosity labels, tastings, and flavors. * Tasting and Flavors1 Text Input: Maps tasting IDs to Flavor IDs. * Flavors Text Input: Maps Flavor IDs to their corresponding flavor names. Your goal in this challenge is to identify the viscosity and flavor labels associated with each sauce. To do so, you need to: * Find the viscosity labels for each sauce (how thick or runny they are). * Find the flavor labels associated with each sauce (for example, spicy, tangy, garlicky). * Ensure each Sauce ID is unique in the final output, avoiding duplicate entries. Your output should include Sauce ID, viscosity, and flavors. HINT: Joining data by flavor and tastings is key to finding your answers! Need a refresher? Review the following lessons in Academy to gear up: * Joining Data * Summarizing Data We can’t wait to review your solutions! Happy solving! The Academy Team Challenge468_solution_file.yxzp Challenge468_start_file.yxzp

Spoiler My Solution 468 Solution.yxmd 468 Solution.bmp

Had to create a data lineage diagram to map out the joins but great challenge Challenge468_solution_file.yxmd

Challenge Completed Spoiler Challenge_468_Joe_Serpis.yxzp

Challenge #468: Many-to-Many Like it Hot – Part 1

AYXAcademy

Weekly Challenge LMS Banner.png

Hello Community members,

A solution to last week’s challenge can be found here.

We are back with another exciting challenge, and this one is all about hot sauces! A big thank you to James Gust for creating this spicy challenge!

This week’s challenge is the first of two parts. For Part 1, you have a collection of individual reviews of hot sauces, but the data is spread across multiple tables due to how it was stored in a relational database. Now, it is your job to bring it all together and extract meaningful insights!

Your datasets include the following:

Hot Sauce Data.xlsx: Contains details about the sauce names, manufacturing information, ratings, spiciness, viscosity labels, tastings, and flavors.
Tasting and Flavors1 Text Input: Maps tasting IDs to Flavor IDs.
Flavors Text Input: Maps Flavor IDs to their corresponding flavor names.

Your goal in this challenge is to identify the viscosity and flavor labels associated with each sauce. To do so, you need to:

Find the viscosity labels for each sauce (how thick or runny they are).
Find the flavor labels associated with each sauce (for example, spicy, tangy, garlicky).
Ensure each Sauce ID is unique in the final output, avoiding duplicate entries.

Your output should include Sauce ID, viscosity, and flavors.

HINT: Joining data by flavor and tastings is key to finding your answers!

Need a refresher? Review the following lessons in Academy to gear up:

We can’t wait to review your solutions!

Happy solving!

The Academy Team

Challenge468_solution_file.yxzp

Challenge468_start_file.yxzp

Join

Core

Transform

Basic

Accepted answers

All comments

merald_acupang

here's my solution

Challenge468_solution_MA.yxmd

argxgd

Trichy!!

Challenge468_Solution_AG.yxzp

AronasZilys

Spoiler

Challenge468_DONE.yxmd

victor_02

Spoiler

challenge_468_VY.yxmd

Miffy_Allen

Spoiler

Challenge468_start_file.yxmd

SteveY02

Done.

One question, my original solution did not include values like "1x" in the concat_viscosity column. After checking, I found that the output of the initial file also calculated null values for viscosity. This doesn't seem to make sense. we shouldn't count null value, right?

Challenge468_Solution_Steve.yxmd

dfuhriman

Spoiler

Challenge468_DF_Finished file_3-27-25.yxzp

mattnason1

Joins took a while to figure out. But otherwise fun.

Challenge468_start_file_MN.yxmd

Fizzledrizzle

I noticed there were nulls on both sides of the solution and tried to account for that as much as possible.

Challenge468_solution.yxmd

Woojac

My solution. I created a union at the end to capture the sauces that did not have a matching Flavor profile. I also noticed that there were a few records with a NULL viscosity. I went ahead and retained these NULLs as these records reflect in the solution. i.e. Sauce ID = 12.

Challenge468_start_file.yxmd

CeliaC_Silje

Spoiler

challenge468

Omitted the sorting step as it does not really affecting the result.

Challenge468_Silje.yxzp

jadepech

Fun!

Challenge468_Jade.yxzp

elainebusby

Fun challenge!

EB_Solution_468.yxzp

DeepakPoojary

Resolved!

Challenge468_solution_file.yxmd

Carlithian

Well now I really want some chicken wings....

Spoiler

Completed Challenge 468 Carlithian.yxzp

Daniel_Homola

Here

Challenge468_start_file.yxmd

Smatthias

Did it through the formula, I think there's a nicer solution than my code, but I was too sleepy to think, because they set the clock one hour before. That always makes me tired.