This is the code that you could use to convert the csv into a 3D polyline:
def main():
import csv
import arcpy
# input csv
csv_path = r"C:\Forum\3Dpnts_3Dlines\SampleData_well.csv"
fld_x = 'bh_long'
fld_y = 'bh_lat'
fld_z = 'Z'
fld_order = 'measdpth'
fld_lineid = 'api_wellno'
# settings
sr = arcpy.SpatialReference(4326) # WGS_1984
arcpy.env.overwriteOutput = True
feetinmeter = 0.3048
# output featureclass (could also point to fc in fgdb)
fc = r"C:\Forum\3Dpnts_3Dlines\shp\test01.shp"
lineids = []
dct = {}
# read csv
with open(csv_path, 'rb') as f:
reader = csv.reader(f)
cnt = 0
for row in reader:
cnt += 1
if cnt == 1:
# header
header = row
else:
# read fields from data
lineid = row[header.index(fld_lineid)]
x = float(row[header.index(fld_x)])
y = float(row[header.index(fld_y)])
z = float(row[header.index(fld_z)]) * feetinmeter
# create point object with XYZ
pnt = arcpy.Point(x, y, z)
# read order and create string to sort on (lineid + order)
order = row[header.index(fld_order)]
srt = "{0}_{1}".format("%04d" % (int(lineid),),
"{0}".format(round(float(order), 1)).zfill(8))
# create nested dictionary with points per line
if lineid in dct:
dct[lineid][srt] = pnt
else:
dct[lineid] = {}
dct[lineid][srt] = pnt
# create polylines
lst_polylines = []
for lineid, dct2 in dct.items():
lst_pnt = []
for srt, pnt in sorted(dct2.items()):
lst_pnt.append(pnt)
polyline = arcpy.Polyline(arcpy.Array(lst_pnt), sr, True, False)
lst_polylines.append(polyline)
# write polylines to output featureclass
arcpy.CopyFeatures_management(lst_polylines, fc)
if __name__ == '__main__':
main()
