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Hi Maveryx,
A solution to last week’s challenge can be found here.
Roland (@RWvanLeeuwen) submitted this challenge as a follow-on to our Valentine’s Day spatial challenge, and solving it now is a great way to celebrate summer in the northern hemisphere. Thank you, Roland, for submitting another great challenge!
In Challenge #413 you applied your data analytics skills to help your friends visit as many ice cream shops as possible, including those that served a particular ice cream flavor. However, your friends are now worried about all the caloric intake, and for the next road trip they want to add some balance by focusing on store locations that are somewhat clustered together so you can all ride your bicycles to the ice cream shops instead!
Note: This challenge helps us check whether a group of shops might be located on the border of multiple states. We need to eliminate the limitation that the closest stores have to be located in the same state. Additionally, the bike ride you and your friends plan to take has specific distance parameters that you all believe will work best.
Your tasks for this challenge:
Need a refresher? Review the following lessons in Academy to gear up:
Good luck!
I am assuming it can be any point we want correct @AYXAcademy? I misunderstood, apologies. I hate that the defect came in where you can't customize the Find Nearest maximum distance without editing the XML 😞
I finally got the answer though!
The most challenging question I've had to answer related to ice cream
Bug in Find Nearest tool in 2024.1, had to change the distance and number using control parameters.
Thank you @RWvanLeeuwen and @AYXAcademy. This was a neat spatial challenge. Love the ice cream topic, especially the summer edition when the temperatures are climbing .
See my solution attached. Would be nice to have the spatial data for the lakes/water polygons to subtract them out from the final output, as it looks like some of the shops ended on the water, lol! :) I welcome your solution to that.
Mine looks slightly different than the answer, but very close - it looks like in posting this I may have the same answer as others. I had forgotten how long it takes to run some of the spatial tools and removed the spatial fields in the output of the Find Nearest tool to conserve memory. Added them back to get the map.,
Had to use 23.1 because 23.2 wouldn't let me edit the Find Nearest tool to custom values.
I spent some time to get the results.
I forgot to include state in grouping. My results is similar but somehow different.
Sooo.. Maybe the next step is to calculate the travel distance from each grid as starting point and calculating the total caloric intake versus the calories consumed as fuel for biking?
Anyways: this is what I'd build today for this challenge:
well yes this may be so @mmontgomery but this analysis can be easily translated to customers (or to pubs for that matter) - hope you had fun!