Cloud Quest #7: Marvel-ous Comics

[AYXAcademy]

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!

1. Download and extract the provided ZIP file containing your starting data and workflow files.
2. Upload the provided Cloud Quest 7 - Start File.json into your Analytics Cloud library.
3. Reconnect the provided charactersToComics.csv and comics.csv datasets to your starting workflow file.
4. 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.

Spoiler

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!

[geoff_zath]

Spoiler

 

[RWvanLeeuwen]

So if the Replace() function in the formula tool is broken, what do we do?

Yes, we use workarounds like regex

Spoiler

[JoachimCaronTIL]

Here is my solution

Spoiler

 

[Ladarthure]

my solution, good warmup with regex!

[Jean-Balteryx]

Here is my solution !

Spoiler

[ScottMcV]

Mine is a little long and non-linear because I tend to think very incrementally.  So extract the year, remove the year, remove the issue... so I can go back and modify or reuse the bits.  The core is the same as others I suspect (join, regex, summarize, unique/sample, sort).

Spoiler

[Qiu]

@AYXAcademy 
This is a nice one. Thanks.
Similar with my case, and observed from someones snapshot, it seems that the "#" is not allowed as Field Name?
In my case, it will be forced to turned to "_".
But in the answer file, the # is showing correctly.

Spoiler

[Shelbey]

I chose to use the Unique tool instead of the Summarize tool like the hint suggested.

Spoiler

[Towers]

always love a bit of regex

Spoiler

 

[mceleavey]

Another one in the books. 

Spoiler

Joined them accordingly, used regex to parse out the Year, summarised into the appropriate grouping (Task 1). I then removed the empty year rows and sampled the first record of each group where the grouping was by CharacterID and the sorting was ascending on 
Year and Issue No.