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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.
In data analytics, cross joins are not often recommended because they can cause massive amounts of data to be generated; however, there are times when they are necessary.
For this week's challenge, you are working in the warehouse for a company that sells bed frames. When bed frames are sold, there are necessary accessories that go along with them (screws, casters, tools, etc.). The manufacturer of these bed frames and accessories ships the products to your warehouse in multiple packages. The manufacturer labels the packages, but then the shipping company adds their own labels to the box, US Customs adds their own label, the trucking company adds their own label, and so on.
At the warehouse, you now have many packages, and it is difficult to determine which packages belong together. Receiving created one spreadsheet for frames and another for accessory sets that lists all the labels that were found on each package. Your job is to identify which packages belong together. To do so, you need to find packages with labels that match.
Using the datasets provided, create a workflow to determine which packages belong together. To solve this challenge, you must calculate the total number of matches.
Hint: Notice that the label A1 appears in both lists.
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Hi Maveryx,
We posted the solution JSON file to Cloud Quest #7. Check it out and let us know what you think! Send suggestions to academy@alteryx.com or leave a comment below!
Let’s dive into this week's quest!
Upload the provided Cloud Quest 8 - Start File.json file into your Analytics Cloud library.
The input and output datasets are included in the start file.
For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article Cloud Quest Submission Process Update.
Scenario:
A group of friends are playing their favorite game. Not understanding the importance of inputting data in an easy-to-work-with format, they devised an incredibly inefficient way to keep score of their game!
In the game, there are five rounds of play and five players (a, b, c, d, and e—the first letter of their names). Each time the player’s initial appears in lowercase, the player is awarded 1 point. Each time their initial appears in uppercase, 1 point is subtracted from their overall score. Now it is your job to figure out each player’s score for each round and their respective totals after all five rounds of play. Who won?
Hints:
Tokenize the input data into rows.
There are many ways to calculate scores for each letter, but an If/Then statement can accomplish this in one expression.
When pivoting, you can perform multiple calculations at once including Sum and Total Column.
A combination of the Cross Tab, RegEx, Formula, and Dynamic Replace tools should solve your problem, but not necessarily in this sequence.
If you find yourself struggling with any of the tasks, feel free to explore these interactive lessons in the Maveryx Academy for guidance:
Getting Started with Designer Cloud
Building Connections in Designer Cloud
Building Your Workflow in Designer Cloud
Once you have completed your quest, go back to your Analytics Cloud library.
Download your workflow solution file.
Include your JSON file and a screenshot of your workflow as attachments to your comment.
Here’s to a successful quest!
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Hi Maveryx,
A solution to last week’s challenge can be found here.
In April, we celebrate Earth Month, a time dedicated to raising awareness and taking action for environmental conservation and sustainability.
This weekly challenge delves into temperatures, highlighting their crucial role in our planet's health. The dataset presents comprehensive information on global temperature records, covering various countries worldwide. It includes average temperature records in Celsius for major cities from 1743 to 2013.
To solve this challenge, we will be concentrating on the data from 1950 onwards.
Your tasks are as follows:
Determine which cities have average temperatures greater than or equal to 25 degrees.
Among the cities identified in the previous task, identify the country with the highest number of such cities.
Examining all countries within the dataset, pinpoint the year with the highest average temperature and the year with the lowest average temperature across the globe.
Need a refresher? Review these lessons in Academy to gear up:
Sorting Data
Separating Data into Columns and Rows
Summarizing Data
Source: https://www.kaggle.com/datasets/maso0dahmed/global-temperature-records-1850-2022
Good luck!
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The link to last week’s challenge (challenge #28) is HERE
Hi everyone, what an awesome time we had at the Alteryx Inspire 2016 Conference in San Diego last week. It was so nice to meet many of the Community members in person. If you attended the conference and went to the Grand Prix event, this week’s challenge is the first of the four laps. We will cover all of laps as weekly challenges in the next weeks. See if you have what it takes to compete, keep in mind the contestants only had about 10 minutes per lap maximum so maybe time yourself.
Use Case: You are the commissioner for your fantasy baseball team. You recently completed your draft and you want to run some simple statistics about each fantasy team.
You have 3 inputs
1) Fantasy pick summary from your draft
2) Hitter stats on all field players (whether selected in your draft or not)
3) Pitchers stats on all pitchers (whether selected in your draft or not)
Objective: In order to run some stats on your draft, you first need to prep your data. Please combine all 3 files so that you have a single output that contains stats on each player drafted in your draft, ordered by "Overall_Pick."
Drivers start your engines!
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Hi Maveryx,
A solution to last week’s challenge can be found here.
This week, we have a special Easter challenge, and we want to express our gratitude to Jifeng Qiu (@Qiu) for his enthusiastic participation in the Community and for suggesting another challenge idea for us. His submission was inspired by a Designer Desktop discussion about joining tables. Thank you, Qiu!
Your neighborhood's community outreach program plans to distribute 100 Easter baskets to local children during Easter. Each basket includes a stuffed animal and a candy treat. There are four variations of baskets, and the organization plans to make 25 of each basket combination. The group will be fundraising to buy the supplies and wants to estimate how much money they will need for the baskets in 2024.
The datasets provide information on the items each basket should contain and the prices of the contents for the years 2021, 2022, and 2023.
In this challenge, you have two tasks:
Build a table that displays the percentage increase of the cost of each basket over the past 3 years (2021–2023).
Use the percentage increase from 2022 to 2023 as a reference point to estimate the amount of fundraising required in 2024 to cover the cost of all 100 baskets.
If you need a little help, you can review these lessons in Academy:
Summarizing Data
Changing Data Layouts
Blending Data with Unions
Have a wonderful Easter!
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