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-1

Import your shp to gdb. Code below will print each polygon extent: import arcpy arcpy.env.overwriteOutput = True arcpy.env.workspace = r"GDB" fc = 'feature_class' count = int(arcpy.GetCount_management(fc)[0]) +1 for fid in range(1, count): arcpy.MakeFeatureLayer_management(fc, 'temp','"OBJECTID" = {}'.format(fid))) arcpy....


4

It appears to be degrees and decimal minutes: 51329338= 51 degrees, 32.9338 minutes Then in decimal degrees latitude: 51 + 32.9338/60.0 =51.54889666666666 and longitude: -7.7573/60.0=-0.129288333333333


0

UPDATE: After thinking about it, the most efficient method for you to transform the coordinates is probably to not use apply but to use the column array. from pyproj import Proj pp = Proj(proj='utm',zone=10,ellps='WGS84', preserve_units=False) xx, yy = pp(My_data["LON"].values, My_data["LAT"].values) My_data["X"] = xx My_data["Y"] = yy Using Transformer ...


3

You can directly use shapely or GeoPandas but with 9888562 records It will take a long time to do (if you want a Progress bar during the pandas operations, you can use tqdm: ) 1) With your solution and the first 4 points import pandas as pd df = pd.DataFrame({'LAT':[47.9767,47.9803,47.9801,47.9798], 'LON':[-122.2450,-122.2458,-122.2472,-122.2465]}) ...


1

As per the answer from Vince, this is fairly easy with a library. The Geodesic class from the geographiclib library provides a great implementation for Java (other language implementations are also available): GeodesicData g1 = Geodesic.WGS84.Inverse(52.515343254180486, 13.384435940499088, 52.51544771840784, 13.386055994744083); GeodesicData g2 = ...


0

This is actually both of the Geodetic Problems, used serially. First you solve the Inverse (aka Reverse) problem, to obtain distance and bearing from two points, then you use the Forward (aka Direct) problem to travel distance and bearing from the first point. I'd recommend you find a library that implements these functions, but it's certainly possible ...


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