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A solution to last week’s challenge can be found here.
For this challenge, you will be hosting the perfect Christmas night! You've invited friends over to eat cookies, listen to music, and watch a movie!
This is a two-part challenge: First you must choose each item (type of cookie, music and movie) based on a specific criterias that are in the container boxes below (you have opinionated friends), then you must use your 3 selections to find the key to the treasure box. The treasure box holds a special gift from your Weekly Challenge team!
(Hint: Label your final selection column as "Answer")
Cookie Criteria: Choose the cookie recipe that makes the most cookies!
1. You have 1000 grams of butter and 1000 g of sugar.
2. The cookies recipes require the ingredients as listed.
3. You are not limited by any of the other ingredients.
Music Criteria: Choose a Christmas playlist for your guests while you eat cookies!
1. Assume each song is 3 minutes and that your total music playtime will be 45 minutes - this determines how many songs you have on the list!
2. Every song must be a -9 or lower in loudness (ex. -15 would be a very quiet song)
3. Eric wants all the minor songs and Matthew wants songs in F major.
4.Thalita loves Dean Martin!
5. Put the songs in order of loudness, so the music builds as a transition to the movie.
The title of the last song is your "answer"!
Movie Criteria: Choose a crowd-pleaser movie
1. You only want a movie that was released in the theater
2. Nicole doesn't want to watch an animated movie.
3. Ryan is feeling nostalgic and wants to watch something from the 80's or 90's.
4. It must be the top rated movie of the year it debuted.
5. The movie with the longest run time in the Comedy genre is your "answer"!
After all that hard work to create the Best Christmas Evening Ever, use your three answers to find the key to the treasure box!
1. Use the provided lookup table to "find and replace" your answers to produce three sets of scrambled letters and numbers (hint: label column as "Answer").
2. Concatenate the key and add to the provided formula tool.
3. Once you run the key through the formula tool, you may open the treasure box and put the link in the tool configuration!
Resources:
Christmas music: https://data.world/promptcloud/spotify-musical-features-of-160-holiday-songs
Top Movies: https://www.spreadsheetshoppe.com/25-best-christmas-movies/ and IMBD
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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
Download Start File
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A solution to last week's challenge can be found here.
To solve this week’s challenge, use Designer Desktop or Designer Cloud, Trifacta Classic.
Merging columns is straightforward with Alteryx. However, in some scenarios there is more complexity to the merge than a simple transformation. In this Weekly Challenge, you have collected address information for your customers, but the information is not always complete. In the input file, you have multiple columns of data for an address: Address, Apt/Unit, and Zip. You need to merge the columns, but some of the column data is blank. For example:
This week your goal is to create a workflow that merges the Address, Apt/Unit, and Zip columns, and ignores any blank values.
Your output should look like this:
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The link to last week’s challenge (challenge #21) is HERE.
This week’s challenge is a little special. I have mentioned before that as internal users or Alteryx we all do these exercises every week and we started doing this at the beginning of 2014. There have been a lot of exercises since then and the product has changed a lot of the past few years. The exercise posted here is exercise #1, the inaugural exercise that we completed internally.
In the spirit of that, you will find the workflow will build from top down instead of from left to right, that is the way Alteryx used to work. For some more fun I would ask that before building the workflow, go to the “About” box from the HELP menu and double click the Colorado flag next to the text “Created in Boulder, Colorado” after that, the tool icons will change to the original Alteryx tool icons that used to be in the product. Don’t worry, once you close Alteryx and re-open it the icons will return to normal.
Now for the challenge , this week’s challenge is an intermediate difficulty one that requires parsing a text field to get at values to summarize.
Use case: The log files from an ATM machine have the transaction amounts embedded in text strings. The user needs to have these text amounts summarized by row (transaction).
Objective: For this assignment the numbers directly following the text ‘ATM2.’ are dollar amounts for transactions. Summarize the values on a row by row basis.
Have fun!
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Hello Community members!
A solution to last week’s challenge can be found here.
Thank you, @Qiu , for creating this fun challenge. Your submission was so extensive, we had to divide it into two parts! We appreciate your contributions to our Weekly Challenges!
Welcome to the first of two challenges where you will dive deep into the world of LEGO®! Get ready to uncover some cool facts about LEGO sets, themes, and part counts. Use the provided datasets to solve this challenge. Let’s go!
The datasets contain the following information:
sets.csv: Data on LEGO sets, including a unique set number, name, release year, theme ID, part count, and image URL.
themes.csv: Data on LEGO themes, with each theme having a unique ID, a name, and a reference to its parent theme when applicable.
You have three tasks to complete in this challenge:
Determine which LEGO set contains the largest number of parts.
Determine which LEGO theme has the largest number of sets.
Calculate the average number of parts per set for each year. Use integer as the data type for this task.
Good luck!
The Academy Team
Download Start File
Download Solution File
Data Sources:
https://rebrickable.com/downloads/
https://www.kaggle.com/code/andycapp29/best-bang-for-your-buck-lego-dataset-analysis/notebook
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