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I am using ArcGIS 10.5.

I have a list of ZIP codes and a number of listings (consider it the number of incidents in each polygon). In each ZIP code I want to group the ZIP codes in such a way that I get territories (bigger polygons by merging the shape) having a total of listing (sum of incidents in all the polygons merge for making the bigger polygon) in range 700-750 per territory.

I tried the grouping analysis tool, but I could not apply the logic of bringing listing value to 700-750 in each territory.

Steps:

  1. Take a polygon if the listing value (attribute) is less than 750. For that polygon look for another nearest polygon to it and merge it with the first polygon.
  2. Add the listing attribute of both polygons to get the value for the bigger polygon.
  3. Keep on repeating 1-2 till the bigger polygon reaches the 700-750 range.
  4. Continue for the whole map.

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  • You say that you "tried the grouping analysis tool" but what precisely did you try? Are you using ArcGIS Pro or the earlier ArcGIS Desktop 10.x architecture? I think you question needs significantly more detail before it can be answered. – PolyGeo Jan 4 '18 at 1:32
  • I am using Arcgis 10.5, I have added more details i do not know how to use grouping analysis tool. – Sandeep Kumar Jan 4 '18 at 1:46
  • From what I can tell from your explanation, you are looking to classify (group) the polygons of the same Zip Code into "incidents" of 700 to 750. What you are looking to do there is start with a zip code and step through all the polygons with that zip code until you reach an incident count of between 700 and 750. I am not aware of tool in Arc which will do this, you will have to write a script to step through each polygon and merge them until the criteria are met. – Keagan Allan Jan 8 '18 at 11:47
  • Have you tried Districting for ArcGIS? esri.com/software/arcgis/extensions/districting – Rayner Jan 9 '18 at 11:04
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There is now a great ArcGIS Pro tool in version 2.1 (released this month):

Spatially Constrained Multivariate Clustering

The tool finds spatially contiguous clusters of features based on a set of feature attribute values and optional cluster size limits.

You can define how many features (points or polygons) each cluster should include, or a range of (summed) field values to use to separate the different clusters.

enter image description here

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