probabilistic-analysis/csv_to_shp.py

@@ -19,7 +19,7 @@ sys.path.insert(0, '../lidar/')
 from nielsen import Gridder  # noqa
 
 MGA55 = 28355  # GDA94, MGA Zone 55
-BEACH = 'Roches'
+BEACH = 'Roches Beach'
 
 # Load profile data
 xlsx_path = '../lidar/Profiles 1 to 12 2019 DEM.xlsx'
@@ -67,7 +67,7 @@ for f in file_list:
             east, north = g.from_chainage(ch)
             row['easting'] = east.round(3)
             row['northing'] = north.round(3)
-            df = pd.concat([df, pd.DataFrame([row])])
+            df = df.append(row, ignore_index=True)
 
 # Convert floats to int
 for col in ['block', 'profile', 'year']: