Update Features and Analysis in Arcpy

Arcpy generated Point Feature Data from Ground water contamination, PFAS chemical levels and MNPCA clean up activity sites

Multiple Shapefile data sources access programmatically online and converted to points in Arcpy, then mapped with ArcGIS pro
Shown below is a dashboard of these data for the latest sampling dates where contamination data is grouped by city/township

What is Arcpy?:¶

Reminder: Arcpy is a Python library for automating GIS tasks in Arc GIS Pro

Collection of modules, functions, and classes from the ArcGIS toolbox
It allows you to perform geoprocessing, analysis, data management and mapping automation using python

In [1]:

import arcpy # allows for access to ArcGIS pro geoprocessing tools and workflow automation
import os # enables interaction with local system resources (paths to folders and files)
import requests # access data from the web
import zipfile ## need this to process and extract downloaded zipfiles later on
import pandas as pd ## use to check spreadsheet formatting


initial_dir= os.getcwd() # capture the initial directory before setting environment for arcpy
print("Initial working directory: ", initial_dir)

Initial working directory:  c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY

What we did last time¶

Created a custom function to pull a countytownship shapefile and load dataset into our local geodatabase
Perform several QC checks on attributes and geometry
Created a unique key by joining attributes
Performed Spatial Join within Arcpy

What we will do this time:¶

Update Features using Arcpy
Perform Spatial Analysis within Arcpy taking each water well's latest reading per polygon

Create and re-use Custom Functions to Save time¶

When you create a python script, the functions within those scripts can be loaded into other scripts
To import your script, do as you would any library in python
- python import my_script as ms
Now the functions within this script are available to use
- python ms.my_function()
Not used here but when multiple script hold different tools you'd be better served using a package and __init__.py setup

In [2]:

## Let's load in our custom tool
import custom_arcpy_tools as cat

Initial working directory:  c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY

In [ ]:

# note: importing the custom tool sets a variable called initial_dir to the path of the script
        # this is intentionally done to support its functionality i.e., creating folders to store data

In [3]:

cat.listFC_dataset_Attributes()

## We purposefully caused an error!
# Why? To demonstrate that the error is due to workspace not being set in this new notebook or script

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_60452\2419765190.py in <cell line: 0>()
----> 1 cat.listFC_dataset_Attributes()
      2 
      3 ## We purposefully caused an error!
      4 # Why? To demonstrate that the error is due to workspace not being set in this new notebook or script

c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\custom_arcpy_tools.py in listFC_dataset_Attributes(workspace)
     92     if not arcpy.env.workspace:
     93 
---> 94         raise ValueError("No workspace is set! Please specify a workspace") #stops the program, calls out this error
     95 
     96 

ValueError: No workspace is set! Please specify a workspace

In [ ]:

# See the ValueError? 
### Don't remember the arguments for this function? 
### Use this:
#  help(function_name)

In [4]:

help(cat.listFC_dataset_Attributes) ## use help(function_name) to get the documentation for the function

Help on function listFC_dataset_Attributes in module custom_arcpy_tools:

listFC_dataset_Attributes(workspace=None)
    List feature classes in the workspace and checks their key attributes, such as SpatialReference , 
    geometry type, and coordinate systems
    Parameters:
    -----------
    workspace: str, optional
        The file path to the workspace (e.g., geodatabase path) containing the feature classes
        If none, the function will use the current ArcPy workspace
        If no workspace is set will raise an error telling you to set a a workspace
    
    Returns:
    --------
    None , if no workspace exists
    Otherwise,    Prints the details of all feature classes in the wksp , including
                - Feature Class Name
                - spatial reference name
                - spatial reference type
                - Geometry
                - Well-known ID of the spatial reference
                Also, warns if different spatial references or coordinate systems exists in the dataset
    Raises: 
    -------
    Value Error: 
        If no wksp is set or if not feature classes are found in the workspace
    Exception:
        For general errors that may occur during processing
    
    Example:
    # To list fc in a geodatabase
    >>> listFC_dataset_Attributes(r"c:/Path/To/Your/Workspace.gdb")
    
    # To use the current wksp already set in Arcpy
    >>> listFC_dataset_Attributes()

In [5]:

# Let's change the directory to where we have a geodatabase with some feature classes to work with
# Note: % is a magic command to access local system file and folders
%cd ./02 Result

c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result

In [6]:

# list the files
%ls

 Volume in drive C is OS
 Volume Serial Number is DA19-2472

 Directory of c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result

03/21/2025  10:29 AM    <DIR>          .
03/27/2025  02:51 PM    <DIR>          ..
03/27/2025  03:52 PM    <DIR>          MN_WaterContamination.gdb
               0 File(s)              0 bytes
               3 Dir(s)  443,118,358,528 bytes free

In [ ]:

## should see a file ending with .gdb. Copy the folder path and add its name below

In [7]:

## Use the gdb name in the folder, and set the path to the gdb

###======================    Set up file paths


gdb_path = r"c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result\MN_WaterContamination.gdb"

##===================== Define the path to script and project folder

# set the folder path as the working environment, and store it for later use
try:
    arcpy.env.workspace = gdb_path
    wksp = arcpy.env.workspace
except Exception as e:
    print(f"Error setting up the path, {e}, Exception type: {type(e).__name__}") # python's built-in error messaging, {e} prints description and type(e).__name__ category

print("Working environment is here",wksp)

## Modify the env attribute to allow overwriting output files
arcpy.env.overwriteOutput= True

Working environment is here c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result\MN_WaterContamination.gdb

In [8]:

arcpy.Exists(wksp) ## same as using print statement following if not os.path.exists(gdb_path)

Out[8]:

True

In [9]:

# Now. Retry the function that failed earlier

cat.listFC_dataset_Attributes()

Workspace is set here c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result\MN_WaterContamination.gdb

Feature class: , atlas_contamination_areas, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_area_lines, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolyline, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_sites, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_sites_noca, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_source_areas, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_wells_result_sum, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels, Spatial Reference name :, GCS_North_American_1983, Spatial Ref Type : Geographic, GeometryPoint, WKID: 4269
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels_proj, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels_by_City, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , city_township_unorg, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , overlap_check1, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_WaterContamination_SpatialJoin, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 


12 Feature classes found in the workspace path

Warning Different wkid detected among feature Classes:  {26915, 4269}
Warning Different Coordinate Systems types found among Feature Classes:  {'Geographic', 'Projected'}

Data Sources:¶

Geography: MN

Input Name	file types	Coordinate System	Source
MN PFAS levels	1 excel file	GCS: NAD 83	Report
MN Groundwater contamination atlas	6 shape files	PCS: NAD 83 UTM Zone 15N	MetaData
MN Cities and townships	1 shapefile	PCS: NAD 83 UTM Zone 15N	MetaData

We have already pulled and done some initial processing of all these datasets in the previous walkthroughs
Now will go into updating features and analysis

In [10]:

# quick reminder of where our current workspace is set
print("Data Folder is here" , wksp)
# let's call it gdb for clarity
gdb=wksp

Data Folder is here c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result\MN_WaterContamination.gdb

MN City,Township, Unorganized Territory Dataset¶

Data represents boundaries of cities, townships and unorganized territories(CTU) in Minnesota
key fields
- GNIS_Feature_ID: official ID for geographic features that relates them to their Name and location in the GNIS Database
- County_GNIS_Feature_ID: official county ID that relates counties to their Name and Location in the GNIS Database
- FEATURE_NAME: Name of the city, township or unorganized territory location
Source : MN Geospatial Commons:
- url: https://gisdata.mn.gov/dataset/11860ca6-9ee4-4ff2-b30b-da9e2f13262a

In [11]:

## Count initial records
# first check the join fc: County/Township/Unorganized territory (CTU)

fc= "city_township_unorg"

print(f"Total records in {fc} feature class is:  {int(arcpy.management.GetCount(fc)[0])}")

Total records in city_township_unorg feature class is:  2743

In [12]:

## check the target input fc

for fc in arcpy.ListFeatureClasses("*wells_result_sum*"):
    print(f"Feature class: {fc}\n Total Record Count: {int(arcpy.management.GetCount(fc)[0])}")

Feature class: atlas_contamination_wells_result_sum
 Total Record Count: 17443

In [13]:

fc ="city_township_unorg"
cat.showFieldinfo(fc)

Summary of Fields in Feature Class: city_township_unorg

Name                 Type         Length   Unique_Values
 OBJECTID             | OID        | 4     | 2743      
 Shape                | Geometry   | 0     | 2743      
 GNIS_FEATU           | Integer    | 4     | 2693      
 FEATURE_NA           | String     | 254   | 2249      
 CTU_CLASS            | String     | 25    | 3         
 COUNTY_GNI           | Integer    | 4     | 87        
 COUNTY_COD           | String     | 2     | 87        
 COUNTY_NAM           | String     | 100   | 87        
 POPULATION           | Integer    | 4     | 1312      
 SHAPE_Leng           | Double     | 8     | 2743      
 Shape_Length         | Double     | 8     | 2743      
 Shape_Area           | Double     | 8     | 2743      
 Combined_GNIS_IDs    | String     | 50    | 2743      

Total Record Count: 2743, Total Geometry Count(by WKT): 2743

In [ ]:

# Number of unique geometries or shapes in the layer (polygons in this case) matches total record count
    # Each row represents a unique CTU location, as evident by the number of unique geometries and lack of overlap between them
    # Combined_GNIS_ID is the corresponding unique attribute field marking each of those unique polygons

In [15]:

cat.open_arcgis_documentation()

Out[15]:

Approach¶

Add Field --> Summarize Data to get the Latest Sampling Date by well and polygon

In [19]:

import custom_arcpy_tools as cat
cat.listFC_dataset_Attributes(wksp)

Workspace is set here c:\Projects\my_git_pages_website\Py-and-Sky-Labs\content\ArcPY\02 Result\MN_WaterContamination.gdb

Feature class: , atlas_contamination_areas, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_area_lines, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolyline, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_sites, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_sites_noca, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_source_areas, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , atlas_contamination_wells_result_sum, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels, Spatial Reference name :, GCS_North_American_1983, Spatial Ref Type : Geographic, GeometryPoint, WKID: 4269
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels_proj, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_PFAS_Levels_by_City, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , city_township_unorg, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , overlap_check1, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPolygon, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 

Feature class: , MN_WaterContamination_SpatialJoin, Spatial Reference name :, NAD_1983_UTM_Zone_15N, Spatial Ref Type : Projected, GeometryPoint, WKID: 26915
------------------------------------------------------------------------------------------------------------------------------------------------------ 


12 Feature classes found in the workspace path

Warning Different wkid detected among feature Classes:  {26915, 4269}
Warning Different Coordinate Systems types found among Feature Classes:  {'Geographic', 'Projected'}

Add a Join Key Field¶

In [23]:

fc = "MN_WaterContamination_SpatialJoin"

for field in arcpy.ListFields(fc):
    print(field.name)

OBJECTID
Shape
Join_Count
TARGET_FID
facility_c
facility_i
facility_t
facility_n
sys_loc_co
loc_name
loc_type
loc_type_2
well_statu
geologic_u
depth_of_w
bottom_of_
surf_elev
latest_sam
number_of_
result_cou
non_detect
detect_bel
exceedance
exceedan_1
exceedan_2
exceedan_3
exceedan_4
exceedan_5
exceedan_6
detect_b_1
detect_b_2
detect_b_3
detect_b_4
detect_b_5
latitude
longitude
eda_url
data_downl
GNIS_FEATU
FEATURE_NA
CTU_CLASS
COUNTY_GNI
COUNTY_COD
COUNTY_NAM
POPULATION
SHAPE_Leng
Combined_GNIS_IDs

In [ ]:

fc = "MN_WaterContamination_SpatialJoin"
newfield= "JoinKey"

try:
    if newfield not in [field.name for field in arcpy.ListFields(fc)]:

        ## a new field
        arcpy.management.AddField(fc,newfield,"TEXT",field_length=50)
        print(f"New {newfield} field added")
        with arcpy.da.UpdateCursor(fc,["sys_loc_co","Combined_GNIS_IDs", newfield]) as cursor:
            for row in cursor:
                well_id= str(row[0])
                combined_id= str(row[1])
                row[2] =  f"{well_id}_{combined_id}"
                cursor.updateRow(row)
        print("Successfully updated the table for the new field")
    else:
        print(f"{newfield} aleady exists in the target dataset {fc}")
        
except Exception as e:
    print("Error occured", e , type(e).__name__)
except arcpy.ExecuteError:
    print("Arcpy Error", arcpy.GetMessages(2))

New JoinKey field added
Successfully updated the table for the new field

Summary Statistics¶

`arcpy.analsysis.Statistics()`¶

Calculate summary statistics for fields in a table
arcpy.analysis.Statistics(in_table, out_table, statistics_fields, {case_field}, {concatenation_separator})
- Key Arguments:
  - in_table: input table with fields to be used to compute statistics
  - out_table: output table to store the calculated results
  - statistics_field: Field or fields containing attribute values to be used and statistic to be used
    - Null values are excluded
    - Can do multiple combinations of statistics and fields
    - Format: [[field, {statistic_type}],...]
  - case_field: Field or combination of fields that will be used to group the data when calculating statistics
    - if not specified the statistics are calculated for all records
    - the output will be a single record

In [ ]:

## Calculate summary stats

fc = "MN_WaterContamination_SpatialJoin"
newfield= "JoinKey" # Field to be used to summarize or group the data
statisticfield= "latest_sam" # date field

try:
    ### TOOL: arcpy.analysis.Statistics(in_table, out_table, statistics_fields, {case_field}, {concatenation_separator})
    arcpy.analysis.Statistics(fc, "MN_WaterContamination_Stats",[[statisticfield,"MAX"]], case_field= newfield)
    print("Statistics Successfully calculated for", fc)
except Exception as e:
    print("Error occured", e, type(e).__name__)
except arcpy.ExecuteError:
    print("Arcy Error", arcpy.GetMessages(2))

Statistics Successfully calculated for MN_WaterContamination_SpatialJoin

In [ ]:

# check the number of records we expect in the new table
cat.showFieldinfo(fc)

Summary of Fields in Feature Class: MN_WaterContamination_SpatialJoin

Name                 Type         Length   Unique_Values
 OBJECTID             | OID        | 4     | 17443     
 Shape                | Geometry   | 0     | 12914     
 Join_Count           | Integer    | 4     | 2         
 TARGET_FID           | Integer    | 4     | 17443     
 facility_c           | String     | 20    | 303       
 facility_i           | Double     | 8     | 303       
 facility_t           | String     | 20    | 7         
 facility_n           | String     | 60    | 303       
 sys_loc_co           | String     | 20    | 11246     
 loc_name             | String     | 80    | 3795      
 loc_type             | String     | 20    | 2         
 loc_type_2           | String     | 50    | 18        
 well_statu           | String     | 20    | 6         
 geologic_u           | String     | 254   | 73        
 depth_of_w           | Double     | 8     | 1145      
 bottom_of_           | Double     | 8     | 1202      
 surf_elev            | String     | 20    | 6199      
 latest_sam           | Date       | 8     | 2305      
 number_of_           | Double     | 8     | 106       
 result_cou           | Double     | 8     | 2167      
 non_detect           | Double     | 8     | 313       
 detect_bel           | Double     | 8     | 54        
 exceedance           | Double     | 8     | 34        
 exceedan_1           | Double     | 8     | 2098      
 exceedan_2           | String     | 10    | 1806      
 exceedan_3           | String     | 254   | 945       
 exceedan_4           | String     | 254   | 1156      
 exceedan_5           | String     | 254   | 4778      
 exceedan_6           | String     | 254   | 4742      
 detect_b_1           | String     | 254   | 2971      
 detect_b_2           | String     | 254   | 3190      
 detect_b_3           | String     | 254   | 6499      
 detect_b_4           | String     | 254   | 5210      
 detect_b_5           | String     | 10    | 2086      
 latitude             | Double     | 8     | 12313     
 longitude            | Double     | 8     | 12595     
 eda_url              | String     | 80    | 11246     
 data_downl           | String     | 121   | 11246     
 GNIS_FEATU           | Integer    | 4     | 276       
 FEATURE_NA           | String     | 254   | 269       
 CTU_CLASS            | String     | 25    | 3         
 COUNTY_GNI           | Integer    | 4     | 73        
 COUNTY_COD           | String     | 2     | 73        
 COUNTY_NAM           | String     | 100   | 73        
 POPULATION           | Integer    | 4     | 262       
 SHAPE_Leng           | Double     | 8     | 277       
 Combined_GNIS_IDs    | String     | 50    | 277       
 JoinKey              | String     | 50    | 11275     

Total Record Count: 17443, Total Geometry Count(by WKT): 12914

In [ ]:

### We expect 11275 records in the summary stats table because their are 11275 unique joinkey values
### The data is grouped to the level of unique wells for each county/township polygon

In [38]:

arcpy.Exists("MN_WaterContamination_Stats")

Out[38]:

True

In [39]:

fc = "MN_WaterContamination_Stats"
record_count = arcpy.management.GetCount(fc)[0]

print("Record Count", record_count)

Record Count 11275

In [54]:

fc =  "MN_WaterContamination_SpatialJoin" 

for field in arcpy.ListFields(fc):
    print(field.name)

OBJECTID
Shape
Join_Count
TARGET_FID
facility_c
facility_i
facility_t
facility_n
sys_loc_co
loc_name
loc_type
loc_type_2
well_statu
geologic_u
depth_of_w
bottom_of_
surf_elev
latest_sam
number_of_
result_cou
non_detect
detect_bel
exceedance
exceedan_1
exceedan_2
exceedan_3
exceedan_4
exceedan_5
exceedan_6
detect_b_1
detect_b_2
detect_b_3
detect_b_4
detect_b_5
latitude
longitude
eda_url
data_downl
GNIS_FEATU
FEATURE_NA
CTU_CLASS
COUNTY_GNI
COUNTY_COD
COUNTY_NAM
POPULATION
SHAPE_Leng
Combined_GNIS_IDs
JoinKey

Join Statistics Table to Spatial Data Layer¶

`arcpy.management.AddJoin()`¶

Join a layer to another layer or to a table based on a common field
- supports Feature layers, table views, and raster layers with attribute tables
- Result is temporary and must be saved (e.g., CopyFeatures, ExportFeatures, ExportTable)
arcpy.management.AddJoin(in_layer_or_view, in_field, join_table, join_field, {join_type}, {index_join_fields}, {rebuild_index}, {join_operation})

In [ ]:

### Join two tables based on a common field and its values

in_fc= "MN_WaterContamination_SpatialJoin" # input table
in_join_key= "JoinKey"

join_table = "MN_WaterContamination_Stats" # Join table
join_table_key= "JoinKey"

try:
    ### TOOL: arcpy.management.AddJoin(in_layer_or_view, in_field, join_table, join_field, {join_type}, {index_join_fields}, {rebuild_index}, {join_operation})
    arcpy.management.AddJoin(in_fc,in_join_key, join_table, join_table_key)

    print(f"Successfully Joined {in_fc} and {join_table}")
    print(arcpy.GetMessages(0))
    
except arcpy.ExecuteError:
    print("Arcy Error: ", arcpy.GetMessages(2))
except Exception as e:
    print("Error occured", e, type(e).__name__)

Successfully Joined MN_WaterContamination_SpatialJoin and MN_WaterContamination_Stats
Start Time: Friday, March 28, 2025 4:56:50 PM
Succeeded at Friday, March 28, 2025 4:56:50 PM (Elapsed Time: 0.06 seconds)

Select the latest water sampling dates using Select By Attributes¶

`arcpy.management.SelectLayerByAttribute()`¶

Adds updates, or removes a selection based on an attribute query
Only works on feature layers or table views!
If the query is present only those features will be used in downstream processes
arcpy.management.SelectLayerByAttribute(in_layer_or_view, {selection_type}, {where_clause}, {invert_where_clause})

In [58]:

in_fc= "MN_WaterContamination_SpatialJoin" # input table
out_lyr= "MN_WaterContamination_joined_layer"
# 
### Join two tables based on a common field and its values
in_join_key= "JoinKey"

join_table = "MN_WaterContamination_Stats" # Join table
join_table_key= "JoinKey"

try:
    ### TOOL: arcpy.management.AddJoin(in_layer_or_view, in_field, join_table, join_field, {join_type}, {index_join_fields}, {rebuild_index}, {join_operation})
    arcpy.management.MakeFeatureLayer(in_fc, out_lyr)
    
    arcpy.management.AddJoin(out_lyr,in_join_key, join_table, join_table_key)
    
    print(f"Successfully Joined {out_lyr} and {join_table}")
    print(arcpy.GetMessages(0))
    where_c = "latest_sam = MAX_latest_sam"
    arcpy.management.SelectLayerByAttribute(out_lyr, "NEW_SELECTION", where_c)
    print(f"Successfully selected features in {out_lyr}")
    print(arcpy.GetMessages(0))

    arcpy.management.CopyFeatures(out_lyr, "MN_latest_WaterSamples_Joined_lyr")
    print(f"Successfully copied features in {out_lyr}")
    print(arcpy.GetMessages(0))
    
except arcpy.ExecuteError:
    print("Arcy Error: ", arcpy.GetMessages(2))
except Exception as e:
    print("Error occured", e, type(e).__name__)

Successfully Joined MN_WaterContamination_joined_layer and MN_WaterContamination_Stats
Start Time: Friday, March 28, 2025 7:13:36 PM
Succeeded at Friday, March 28, 2025 7:13:36 PM (Elapsed Time: 0.07 seconds)
Successfully selected features in MN_WaterContamination_joined_layer
Start Time: Friday, March 28, 2025 7:13:37 PM
Succeeded at Friday, March 28, 2025 7:13:37 PM (Elapsed Time: 0.52 seconds)
Successfully copied features in MN_WaterContamination_joined_layer
Start Time: Friday, March 28, 2025 7:13:37 PM
Succeeded at Friday, March 28, 2025 7:13:38 PM (Elapsed Time: 1.24 seconds)

Savage, MN GIS

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