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I am running an iterator in ModelBuilder that ultimately takes the output from each iteration (a point feature class) and runs the spatial auto-correlation tool (global Moran's I). I have about 450 output feature classes, and what I would like to have is the feature class name, index value, z-score, and p-value from each iteration (of Moran's I) added as a new record in a table. These values are reported in the .HTML report and the model run summary window, but I can't figure out how to extract them and add them to a table.

If I were doing this with a statistical model in R, I could simply call the model output values (index, p-value, etc.). But Ideally I would like to do this in ModelBuilder. I'm not opposed to writing a Python script, but before I go down that road I'm wondering if there's a more direct way to do it with existing geoprocessing or ModelBuilder tools.

As an additional note, I would also like to get the default calculated bandwith from the Kernel density tool output to a table similar to the Moran's I values.

I am running ArcGIS Pro 2.3.

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Using the arcpy implementation of the spatial autocorrelation tool, you can get this information. Albeit, in a somewhat roundabout way.

Firstly, as per the documentation (example 2), if you set a variable called moransI to the actual call of the tool such as:

moransI = arcpy.SpatialAutocorrelation_stats("olsResults.shp", "Residual",
                        "NO_REPORT", "GET_SPATIAL_WEIGHTS_FROM_FILE", 
                        "EUCLIDEAN_DISTANCE", "NONE", "#", 
                        "euclidean6Neighs.swm")

You'll get access to the getMessages function. This contains the full output text of the tool. And it's ugly:

"Start Time: Thursday, 21 March 2019 3:32:00 PM\nRunning script SpatialAutocorrelation...\nWARNING 001605: Distances for Geographic Coordinates (degrees, minutes, seconds) are analyzed using Chordal Distances in meters.\nWARNING 000846: 58 feature(s) had no neighbors which generally invalidates the statistical properties of a test.\nWARNING 000847: Features with no neighbors (only includes first 30): FID = 1186, 6475, 6634, 6712, 7563, 10078, 13157, 13518, 13941, 14496, 15894, 17155, 17156, 17195, 17363, 17365, 20442, 20986, 21047, 21171, 21350, 23587, 26744, 28141, 28153, 28615, 28982, 30519, 30520, 30768.\n\n Global Moran's I Summary \nMoran's Index: 0.210751 \nExpected Index: -0.000018 \nVariance: 0.000001 \nz-score: 176.055455\np-value: 0.000000 \n\nDistance measured in Meters\n\nCompleted script Spatial Autocorrelation (Global Moran's I)...\nSucceeded at Thursday, 21 March 2019 3:32:26 PM (Elapsed Time: 26.01 seconds)"

However, you can create a list for each line of text like so:

moranList = moransI.getMessages().split('\n')

Then, you can get all the summary values by accessing those items in the list:

moranIndex = moranList[-10]
ExpectedIndex = moranList[-9]
Variance = moranList[-8]
zScore = moranList[-7]
pValue = moranList[-6]

Of course, this will have some unwanted text, which I'll leave as an exercise. You'll just want to pull out the numbers from the strings.

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