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SUBMIT YOUR IDEAThis is a tough one!
The first time I tried to solve this I got different averages than the solution: that's because the "window" on which the average is calculated differed in my first attempt than in the provided solution.
This is also a good challenge to practice some initial data exploration when you first get the data. When I first opened the Starter workbook, I started by playing around with the data at first with the Data Investigation tools. I left my Interactive Report on the canvas as this one I found to be the most useful.
The trick with this one is to redefine the "window" of which the average is calculated: it has to include the "changeover" nodes in the map.
I think I need to revisit this at some point - I tried to "shave" the polygon object to make it more of a line instead of the funky filled shape that I have here. Also - could I use the Tile tool to construct the sequence instead?
Shout out to @nick_ceneviva for his solution to give me the idea to redefine the "window"
Good spatial challenge!
My solution:
Hello everyone. Once again, I am respectfully disagreeing with the results provided with the problem. Loved the problem though, I lived through Harvey and played host to 4 displaced families during the flood. Thankfully no damage to my home.
The provided solution seems to have messed up average intensity results while building the map. Have a look inside the spoiler for my reasoning.
Attached solution provides both computations - the one matching the specified solution (upper right) and the one that I think is correct (lower right).
The solution calls for creating overlapping polylines so that the map will not have gaps between the segments. It does this by adding the first point of the subsequent segment to the previous segment, extending each polyline over the beginning of the next one. This is fine and fair enough.
The thing is, it messes up the average intensity results by including the first point of the next segment in the computation. This is not right. I have included a version which excludes the additional point.
This goes to show how analytics can help save lives.