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
Fun stuff! Love me a hot sauce 🔥
Great challenge, definitely took me a minute or two to realise what needed to be joined. Here's my solution:
Great Challenge!
