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Challenge #214: US Military and High Points

Alteryx Partner

What a challenge!  Definitely tested my knowledge of A LOT of tools.  I'm sure there is a way to solve with less tools, but my solution works and shows off different ways to accomplish similar tasks.  Enjoy and good luck!



6 - Meteoroid

I love that there are so many different ideas to do the same thing:)




6 - Meteoroid

Using that Make Columns was brilliant. Didn't even know it was there. I've never looked in the Experimental grouping section.

6 - Meteoroid

I really appreciated what Jonathan-Sherman did to keep the # of tools as limited as possible. I'm not great at the Regex command, so I used his formula tool and was able to get it down to only 12 tools. 9 for the correct answer:)





8 - Asteroid

Good one this week, parsing is always an interesting experience!



I needed that column tool in my life!  Thanks!




Alteryx Certified Partner

Question 1 and 2 were pretty straightforward. Question 3 is absolutely bonkers.


Solution attached

8 - Asteroid

My Solution:

12 - Quasar

I hate to quibble with the data here @AYXAcademy, but I believe there is something wrong with the polygon locations in the MIRTA dataset.


As someone who has spent a fair amount of time on the Redstone Arsenal in Alabama, I'm pretty sure it's misplaced as the polygon is located in Northern California.


alabama locations.png

(looking only at alabama MIRTA Locations, converted to centroids for simplicity)


Out of curiosity I fed the Alabama locations against a shape file of the state, and only 4 of the 32 records were actually located, well, in Alabama.


I'm happy to be terribly wrong here and missing something, but there's only one spatial object in the MIRTA sites, so I doubt it.


Has anyone else noticed this?



EDIT: I did some more digging, because I was convinced I was the one that was wrong. Based on my understanding, only 120 of the locations are actually in the state that they're listed. In fact, the remaining are all located at that one mysterious point in Northern California. (see attached workflow, using Census data install for state shapes)


Edit 2: It turns out when you go to the datasource for the MIRSA data and bring in the original shapefiles, the locations are correct. When you copy/paste those records as a text input (as I'm guessing was done to create start file for the challenge), the locations on the spatial objects get messed up!