How to Select By Location and Attribute?
Hi,
I have 120 individual data points (each representing a small airport) that I would like to perform the following analysis:
- Select a county that the airport is located in and extract a statistic from that county (e.g. income/capita). Let’s call this County A and the statistic X.
- Select another county (let’s call it County B) subjected to the following constraint: County B must be intersected by a circle of the same geodesic radius as the distance between the airport in County A and a central location.
- The selection of County B should be based on another given statistic of County B being most similar to County A. Let’s call this selection criteria statistic Y. (E.g. If statistic Y is population, I would like to select the county with closest population to County A that is intersected by the circle.)
- Extract the names of County A, B as well as statistic X, Y for County A and B to a table.
- Repeat for the other rows of data (i.e. the other small airports and central locations they are paired with.)
The image below is an example of one of these situations. The small green dot towards the right is the airport in consideration, the selected county is County A in this situation. Thus, County B is the county that is closest to County A for a statistic Y (e.g. most similar in population) and is intersected by the geodesic circle.
I believe this is a combination of Selection by Location and Selection by Attribute. Would Model Builder be the best approach for this problem?
Thanks ahead for the help!
Regards,
Jao
This sounds like fun, so I tried something and this is the result:
and this is what the connecting lines look like:
This is the code used. Change lines according to your data and needs:
- 6 input featureclass
- 7, 8 and 9 the input fields
- 12 the output connector featureclass
- 15 the distance for the buffer
import arcpy
import os
def main():
# inputs
fc = r"D:\Xander\GeoNet\County\data.gdb\Counties_test"
fld_id = "GEOID"
fld_name = "NAME"
fld_pop = "POP010210D"
# output for validation
fc_out = r"D:\Xander\GeoNet\County\data.gdb\connections03"
# the geodesic distance
distance = "300000 Meters"
# internal settings
ws_mem = "IN_MEMORY"
arcpy.env.overwriteOutput = True
sr = arcpy.Describe(fc).spatialReference
# create featurelayer for selection
arcpy.MakeFeatureLayer_management(fc, "county_lyr")
# list to store output conector lines (between counties)
lst_feats = []
# start search cursor over counties
flds = ("SHAPE@", fld_id, fld_name, fld_pop)
with arcpy.da.SearchCursor(fc, flds) as curs:
for row in curs:
polygon = row[0]
geoid = row[1]
name = row[2]
pop = int(row[3])
# determine label point in input county
pnt = polygon.labelPoint
pntg = arcpy.PointGeometry(pnt, sr)
# buffer label point
fc_tmp = os.path.join(ws_mem, "tmp_buf")
arcpy.Buffer_analysis(in_features=pntg, out_feature_class=fc_tmp,
buffer_distance_or_field=distance,
method="GEODESIC")
# get first feature of buffer
buf_pol = arcpy.da.SearchCursor(fc_tmp, ("SHAPE@",)).next()[0]
# boundary = buf_pol.boundary()
# lst_feats.append(boundary)
# select by location
arcpy.SelectLayerByLocation_management("county_lyr", "CROSSED_BY_THE_OUTLINE_OF",
buf_pol, selection_type="NEW_SELECTION")
# search selected counties for similar population
min_dif = 999999
with arcpy.da.SearchCursor("county_lyr", flds) as curs_s:
for row_s in curs_s:
pnt_s = row_s[0].labelPoint
pop2 = int(row_s[3])
dif = abs(pop - pop2)
if dif < min_dif:
# found a county
min_dif = dif
pop_found = pop2
geoid_found = row_s[1]
name_found = row_s[2]
pnt_found = arcpy.Point(pnt_s.X, pnt_s.Y)
# create line between two counties
line = arcpy.Polyline(arcpy.Array([pnt, pnt_found]), sr)
lst_feats.append(line)
# print result
print "{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}".format(name, geoid, pop, name_found, geoid_found, pop_found, min_dif)
# copy line features to output featureclass
arcpy.CopyFeatures_management(lst_feats, fc_out)
if __name__ == '__main__':
main()
