Latest Contributions by XanderBakker

Hi @AFackler_NAPSG ,   You have to update the minimum distance and as @KenBuja  pointed out you have to put the return outside the for loop.   var searchDistance = 50; var points = $layer; var CurrentiaName = $feature.iaName; var closestPoints = Intersects(points, BufferGeodetic($feature, searchDistance, "Miles")); var minDistance = Infinity; for(var pnt in closestPoints){ var facilityDistance = DistanceGeodetic(pnt, $feature, "miles"); if (facilityDistance < minDistance){ if (CurrentiaName != pnt.iaName) { closestPoint = pnt; minDistance = facilityDistance; } } }; return closestPoint.iaName;  Furthermore, you have to avoid returning the same input feature. You could do this by checking for an ID (I used the iaName in this case.  ... View more

Hi @HussainMalik1  I suggested creating a table with the 5200 records for all archetype, year and variable combinations. Like this: (I used this snippet to create the content:) import random # 26(archetype)*4(years)*50(variables) for x in range(26): archetype = "archetype {}".format(x + 1) for y in range(4): year = 2020 + y * 10 for z in range(50): variable = "variable {}".format(z + 1) value = random.random() * 25 print("{}\t{}\t{}\t{}".format(archetype, year, variable, value))   I converted the data to an ArcGIS table in a FGDB and ow you can read the values either into a dictionary and query directly on archetype and year (if you are planning to use all the data) or simply load the variables related to a specified archetype and year using a query definition while reading the table. See the code below (including both example): import arcpy def main(): # table location and field names tbl = r'D:\GeoNet\EnergyCalc\ArchetypeYear\Default.gdb\ArchetypeYearData' fld_arche = 'Archetype' fld_year = 'Year' fld_var = 'Variable' fld_val = 'Value' # input values to query archetype = 'archetype 19' year = 2030 # get values using a dictionary dct = ReadDataIntoDict(tbl, fld_arche, fld_year, fld_var, fld_val) dct_res1 = GetDictValuesForArchetypeAndYear(dct, archetype, year) print(dct_res1) print("") # get values using the table and a query definition dct_res2 = GetTblValuesForArchetypeAndYear(tbl, fld_arche, fld_year, fld_var, fld_val, archetype, year) print(dct_res2) def ReadDataIntoDict(tbl, fld_arche, fld_year, fld_var, fld_val): dct = {} with arcpy.da.SearchCursor(tbl, [fld_arche, fld_year, fld_var, fld_val]) as curs: for row in curs: archetype = row[0] year = row[1] variable = row[2] value = row[3] if archetype in dct: dct_arche = dct[archetype] if year in dct_arche: dct_year = dct_arche[year] dct_year[variable] = value dct_arche[year] = dct_year dct[archetype] = dct_arche else: dct_arche[year] = {variable: value} dct[archetype] = dct_arche else: dct[archetype] = {year: {variable: value}} return dct def GetDictValuesForArchetypeAndYear(dct, archetype, year): return dct[archetype][year] def GetTblValuesForArchetypeAndYear(tbl, fld_arche, fld_year, fld_var, fld_val, archetype, year): dct = {} query = "{} = '{}' AND {} = {}".format(fld_arche, archetype, fld_year, year) with arcpy.da.SearchCursor(tbl, [fld_var, fld_val], query) as curs: for row in curs: dct[row[0]] = row[1] return dct if __name__ == '__main__': main()   In this example, specifying archetype "archetype 19" and year 2030 used the following query definition: Archetype = 'archetype 19' AND Year = 2030   ...and returned a dictionary with all the variables for this query (providing access to all the 50 variables): {'variable 1': 15.5244401870236, 'variable 2': 23.3657321633143, 'variable 3': 15.1579971665677, 'variable 4': 22.4358991530334, 'variable 5': 4.29857939816623, 'variable 6': 9.85983758111721, 'variable 7': 18.5286923152794, 'variable 8': 5.79755699855013, 'variable 9': 22.7302585515292, 'variable 10': 20.7952926242024, 'variable 11': 3.15393340209763, 'variable 12': 6.55497889635969, 'variable 13': 23.534915278783, 'variable 14': 0.320347367664924, 'variable 15': 7.48007771767636, 'variable 16': 19.7211779286983, 'variable 17': 5.28625570863067, 'variable 18': 7.73552043487549, 'variable 19': 17.2153002750518, 'variable 20': 6.89264095850893, 'variable 21': 2.36278203597135, 'variable 22': 7.46633514134018, 'variable 23': 3.48576873823912, 'variable 24': 4.14460495556789, 'variable 25': 21.7298557989618, 'variable 26': 12.3477762544827, 'variable 27': 5.06567178346359, 'variable 28': 23.3938881028709, 'variable 29': 9.22447098083539, 'variable 30': 20.6246227233889, 'variable 31': 9.2655784448017, 'variable 32': 16.7829187579809, 'variable 33': 5.41408450739008, 'variable 34': 10.4562086747899, 'variable 35': 12.3017493699073, 'variable 36': 4.87453196521707, 'variable 37': 21.2273082111302, 'variable 38': 9.83037462145755, 'variable 39': 6.71378949875001, 'variable 40': 17.1075560942317, 'variable 41': 13.9113667208803, 'variable 42': 21.2160384165932, 'variable 43': 10.144770899068, 'variable 44': 7.1533553156325, 'variable 45': 5.7455521841622, 'variable 46': 9.92663148960041, 'variable 47': 3.13525525773836, 'variable 48': 12.5155910723043, 'variable 49': 20.245329425554, 'variable 50': 0.227518270529811}   This can then be used to do the calculations.   When I looked at your features, I noticed that you have 4 copies of the same geometry (one for each year( and you have repetitions of multiple archetypes for a large part of the data. I don't quite see how you are planning to connect this data to the features you have.  Can you explain more about this? What is a scenario supposed to return? ... View more

Hi @SMehta ,   This for sharing the idea of using Collections::Counter, which is indeed a great way of splitting a text and get a dictionary with the counts. Kudos for that. However, in your code, I don't see you are handling the creation of the same field twice which I assume should fail and using the description for the field name would also fail since the descriptions are no valid field names.    @HussainMalik1 ,   Find below the part of the GetStats function which will now set values to 0 and avoids getting the Null values in the result:  def GetStats(archetype, dct_flds): # get the stats from the archetype dct_cnts = {} for description, fld_name in dct_flds.items(): dct_cnts[fld_name] = 0 archetypes = archetype.split(";") for description in archetypes: if description in dct_flds: fld_name = dct_flds[description] if fld_name in dct_cnts: dct_cnts[fld_name] += 1 else: # this part is no longer required dct_cnts[fld_name] = 1 else: # oops, value not defined in dct_flds, report this print('{} is not included in dct_flds'.format(description)) pass return dct_cnts   ... View more

Hi @HussainMalik1 ,   See below the script that allows you to get the statistics: import arcpy def main(): # read the input featureclass # fc = arcpy.GetParameterAsText(0) fc = r'D:\GeoNet\ExtractText\XanderBakker.gdb\Hussain_Data_ConcatenatedFieldValueCount' # input data field fld_name = 'ARCHETYPE' # define how the items relate to the fields dct_flds = {'Large Multi-Storey Home built < 2007': 'LMSHBLT2007', 'Large Multi-Storey Home built >= 2007': 'LMSHBGE2007', 'Large Multiplex built < 2007': 'LMBLT2007', 'Large Multiplex built >= 2007': 'LMBGE2007', 'Large Retail': 'LargeRetail', 'Large Schools': 'LargeSchools', 'Large Single Storey Home built < 2007': 'LSSHBLT2007', 'Large Single Storey Home built >= 2007': 'LSSHBGE2007', 'Medium Apartments Mixed': 'MediumAptMixed', 'Medium Offices': 'MediumOffices', 'Small Apartments Mixed': 'SmallAptMixed', 'Small Multi-Storey Home built < 2007': 'SMSHMLT2007', 'Small Multi-Storey Home built >= 2007': 'SMSHBGE2007', 'Small Multiplex built < 2007': 'SMBLT2007', 'Small Multiplex built >= 2007': 'SMBGE2007', 'Small Offices': 'SmallOffices', 'Small Retail': 'SmallRetail', 'Small Schools': 'SmallSchools', 'Small Single Storey Home built < 2007': 'SSSHBLT2007', 'Small Single Storey Home built >= 2007': 'SSSHBGE2007', 'UNDEFINED': 'UNDEFINED', 'Very Small Apartments Mixed': 'VerySmallAptMixed'} # add fields if necessary addfields = True if addfields: AddFields(fc, dct_flds) # create list of fields flds = [fld_name] for fld in dct_flds.values(): flds.append(fld) # loop through data with arcpy.da.UpdateCursor(fc, flds) as curs: for row in curs: archetype = row[0] # calculate statistics dct_cnts = GetStats(archetype, dct_flds) # set row stats values for fld_name, cnt in dct_cnts.items(): i = flds.index(fld_name) row[i] = cnt # write updated row curs.updateRow(row) def AddFields(fc, dct_flds): # Add the fields mentioned in the dictionary for description, fld_name in dct_flds.items(): if not FieldExists(fc, fld_name): arcpy.AddField_management(fc, fld_name, "LONG") def FieldExists(fc, fld_name): # Check if field exists if len(arcpy.ListFields(fc, fld_name)) == 0: return False else: return True def GetStats(archetype, dct_flds): # get the stats from the archetype dct_cnts = {} archetypes = archetype.split(";") for description in archetypes: if description in dct_flds: fld_name = dct_flds[description] if fld_name in dct_cnts: dct_cnts[fld_name] += 1 else: dct_cnts[fld_name] = 1 else: # oops, value not defined in dct_flds, report this print('{} is not included in dct_flds'.format(description)) pass return dct_cnts if __name__ == '__main__': main()   This script points on line 6 to the data you shared.  I noticed that the featureclass did not have any output fields defined, so I added code to add the new fields if they don't exist. Please note that there are a large number of UNDEFINED values in the fields. Below some statistics of what was found in the data: Description Count Output Field name Large Multi-Storey Home built < 2007 272 LMSHBLT2007 Large Multi-Storey Home built >= 2007 160 LMSHBGE2007 Large Multiplex built < 2007 1708 LMBLT2007 Large Multiplex built >= 2007 1548 LMBGE2007 Large Retail 60 LargeRetail Large Schools 12 LargeSchools Large Single Storey Home built < 2007 2852 LSSHBLT2007 Large Single Storey Home built >= 2007 44 LSSHBGE2007 Medium Apartments Mixed 40 MediumAptMixed Medium Offices 8 MediumOffices Small Apartments Mixed 72 SmallAptMixed Small Multi-Storey Home built < 2007 1980 SMSHMLT2007 Small Multi-Storey Home built >= 2007 424 SMSHBGE2007 Small Multiplex built < 2007 2484 SMBLT2007 Small Multiplex built >= 2007 392 SMBGE2007 Small Offices 20 SmallOffices Small Retail 132 SmallRetail Small Schools 28 SmallSchools Small Single Storey Home built < 2007 6668 SSSHBLT2007 Small Single Storey Home built >= 2007 4 SSSHBGE2007 UNDEFINED 552 UNDEFINED Very Small Apartments Mixed 224 VerySmallAptMixed   Let me know if you have any questions. I will try to send the FGDB by private message (if it fits)... ... View more