Hi, Possibly something for Ideas, but perhaps others have input before I suggest something. I'm calculating distances in a notebook on a Spatially Enabled Dataframe. The SDF has just over 5,300 records, SR is 4326. Using %time in Jupyter (shame you can't use magics in Pro 2.5 notebooks interface), I run the same function twice, the only difference being the code line below: arcgis.geometry.distance(sr, sdf_row['SHAPE'], prev_row['SHAPE'], 9001, True)['distance'] Wall time: 1h 2min from geopy.distance import geodesic
...
geodesic((sdf_row['SHAPE'].y, sdf_row['SHAPE'].x), (prev_row['SHAPE'].y, prev_row['SHAPE'].x)).meters Wall time: 2.46 s That is a staggering difference. There's no difference in the results given a reasonable precision. count 5394.0000000000 mean -0.0000000018 std 0.0000000030 min -0.0000000141 25% -0.0000000025 50% -0.0000000006 75% 0.0000000001 max 0.0000000034 Name: diff, dtype: float64
Why is arcgis.geometry.distance so slow?
Cheers
m
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