Hi Maveryx,
We posted the solution JSON file to Cloud Quest #6. 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!
Download and extract the provided ZIP file containing your starting data and workflow files.
Upload the provided Cloud Quest 7 - Start File.json into your Analytics Cloud library.
Reconnect the provided charactersToComics.csv and comics.csv datasets to your starting workflow file.
Reconnect the Solution (Task 1).csv file to the Output Solution for Task 1 if you would like to review it. The Task 2 solution output is provided in the JSON 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:
Marvel Comics has a long history dating back to the 1930s and has created hundreds of characters we still find in superhero stories today. For today’s quest you will be blending and parsing data to identify every appearance of each character in Marvel Comics’ publication history (up to 2018).
Task 1: Use the provided datasets to determine the title, year, and issue number of every comic in which the characters in the Characters Text Input tool appear.
Task 2: Identify the first appearance of each character - year and issue number.
* Remove records without a publication year before sampling.
For those of you who are curious, titles without a published year are generally trade paperbacks and omnibuses that are collections of previously published comic issues. These are organized in narrative order rather than publication date and may include multiple titles contributing to the same storyline.
Hint: Use the RegEx tool to parse comic titles and publication years. Use a Summarize tool to group parsed data by Character Name, Comic Title, Publication Year, and Issue Number.*
*If you notice records with an issue number of -1, this is a numbering convention Marvel sometimes uses to indicate a prequel story. This will not affect your result.
A combination of the RegEx, Join, Summarize, Formula, Filter, and Sample 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
Creating Regular Expressions
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,
We posted the solution JSON file to Cloud Quest #5. 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!
Download the provided JSON start file and upload it into your Analytics Cloud library. For more detailed instructions on how to import and export Designer Cloud workflow files, check out the pinned article .
Scenario:
This week’s quest revolves around data provided about standardized math exams administered in New York City Public Schools from 2013 to 2019. Download the provided district_math_results.csv dataset and reconnect it in your starting workflow file. Ensure that the Interpret Column Datatypes checkbox is not selected in the Input Data tool options. The dataset includes details on the district, grade, year, category (male/female); the number of students who took the test; and the percentage of students who achieved each level, with Level 4 being the highest.
You have two tasks:
Calculate the change, by district, in the percentage of 8th grade female students who achieved a Level 4 score in 2019 compared to 2013.
Identify the top three districts that showed the most significant improvement in the Level 4 percentage over the same period.
Hint: Configure the Cross Tab tool to create a new column based on the Year field, labeling the columns as Year 2013 and Year 2019. The Level 4 percentage should serve as the value for these columns, using the Use First Value method. Ensure the data is grouped by District.
A combination of the Sample, Filter, Cross Tab, Formula, and Select tools should solve your problem, but not necessarily in this sequence.
A combination of the Sample, Filter, Cross Tab, Formula, and Select 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 workflow screenshot as attachments to your comment.
Here’s to a successful quest!
Source: https://infohub.nyced.org/docs/default-source/default-document-library/2014-15-to-2022-23-nyc-regents-overall-and-by-category---public.xlsx
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Hi Maveryx,
A solution to last week’s challenge can be found here.
This challenge was submitted by our ACE and an active member in the Alteryx Community, Ippei Nakagawa (@gawa) . Thank you Gawa for your contribution and we look forward to the next ones that you may bring to the table!
Across the United States, an annular solar eclipse was observed on October 14, 2023, and a total solar eclipse will be observed on April 8, 2024. In this challenge, you will determine which lucky cities in the USA observed an annular solar eclipse in 2023 and which ones will observe the total solar eclipse in 2024, as well as one lucky city that will observe both! The provided datasets include solar eclipse information from 2023 and 2024 including the name of the city; latitude and longitude of the city; how long the eclipse will last; and the eclipse’s category (P: partial, T: total, A: annual).
Your tasks:
Create a combined list of the cities that observed the annular eclipse in 2023 and which cities will observe the total eclipse in 2024.
Create a map to visualize each eclipse’s path throughout the year for 2023 and 2024.
Determine the lucky city that will get to see both eclipses!
Hint: The provided datasets are JSON files. To facilitate the data extraction, use the Parse JSON tool in the Developer tab of Designer.
Need a refresher? Review these lessons in Academy to gear up:
Changing Data Layouts
Parsing JSON
Creating Spatial Objects
Sources: https://svs.gsfc.nasa.gov/ https://svs.gsfc.nasa.gov/vis/a000000/a005000/a005073/2023_city_times.json
https://svs.gsfc.nasa.gov/vis/a000000/a005000/a005073/2024_city_times.json
Good luck!
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Hi Maveryx,
A solution to last week’s challenge can be found here.
This challenge was submitted by @AkimasaKajitani . Thanks Aki for this great contribution!
You and your friends enjoy high-energy songs. Since your friends know you are skilled at using Alteryx, they have asked you to create a 60-minute playlist using the Optimization tool. This playlist should contain the most popular and energetic songs, each included only once.
Each record in the provided dataset contains the variable (song ID), song name, popularity, level of energy (ranging from 0 to 1, with 0 being less energetic and 1 being more energetic), and song duration. Additionally, you are given the formatted for the B anchor of the Optimization tool. This represents the maximum duration of 3600 seconds, or 60 minutes (rhs).
Your task is to create a maximum 60-minute playlist that maximizes song popularity from the top 100 high-energy songs. Each song should only be included once. Additionally, output the total popularity value of (Objective ).
Summary of Data:
You are provided with a file containing a song popularity dataset with energy values for each song and its duration. Additionally, you are given the formatted input for the B anchor or the Optimization tool.
Hints:
Ensure you select Maximize Objective in the Optimization tool settings and spend most of your time structuring the data for the Specify the Model as Matrices option. You will not need to change any other settings in the tool (other than Maximize Objective).
Field names matter! Check out this article, which features data format.
song_popularity = coefficient
lb and ub values are a binary datatype of 0,1
Need a refresher? Review these resources to gear up:
Tool Mastery | Optimization
Article: Beginners Guide To Alteryx Optimization
Help Documentation: Optimization Tool
Source: The dataset was modified to align with the learning objectives of the challenge. https://www.kaggle.com/datasets/maharshipandya/-spotify-tracks-dataset
Good luck!
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A solution to last week’s challenge can be found here.
When working with a traditional spreadsheet, it's relatively straightforward to summarize over rows and columns. But we often would like to do something similar in Designer! We also have the added feature to be able to create reports in a variety of formats.
For this challenge, find the total cost for all food items for each country as well as the total cost for each food item. Then create a report of your choice to show your findings.
Hint: How to Generate and Format Totals and Subtotals
https://community.alteryx.com/t5/Engine-Works/How-to-Generate-and-Format-Totals-and-Subtotals/ba-p/916853
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