20240924
11360400
1.0
FALSE
Warehouse_Demos
002
file://\\PHO-US-FP02\Data\Photo Mapper\Mapping\ArcGIS Content\Projects\2024\38685_TJX_Denver_Labor&Transportation\38685_TJX_Denver_Labor&Transportation.gdb
Local Area Network
Geographic
GCS_WGS_1984
Angular Unit: Degree (0.017453)
<GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem>
ExportFeatures USA_ZipCode "Z:\Photo Mapper\Mapping\ArcGIS Content\Projects\2024\38685_TJX_Denver_Labor&Transportation\38685_TJX_Denver_Labor&Transportation.gdb\ColoradoZipCodes_WH" # NOT_USE_ALIAS "ZIP_CODE "ZIP_CODE" true true false 10 Text 0 0,First,#,USA_ZipCode,ZIP_CODE,0,9;PO_NAME "PO_NAME" true true false 100 Text 0 0,First,#,USA_ZipCode,PO_NAME,0,99;STATE "STATE" true true false 2 Text 0 0,First,#,USA_ZipCode,STATE,0,1;POPULATION "POPULATION_2022" true true false 0 Long 0 0,First,#,USA_ZipCode,POPULATION,-1,-1;POP_SQMI "POP22_SQMI" true true false 0 Double 0 0,First,#,USA_ZipCode,POP_SQMI,-1,-1;SQMI "SQMI" true true false 0 Double 0 0,First,#,USA_ZipCode,SQMI,-1,-1;Shape__Area "Shape__Area" false true true 0 Double 0 0,First,#,USA_ZipCode,Shape__Area,-1,-1;Shape__Length "Shape__Length" false true true 0 Double 0 0,First,#,USA_ZipCode,Shape__Length,-1,-1" #
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WorkspaceConnectionString>DATABASE=Z:\Photo Mapper\Mapping\ArcGIS Content\Projects\2024\38685_TJX_Denver_Labor&Transportation\38685_TJX_Denver_Labor&Transportation.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>ColoradoZipCodes_WH</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>ZipCodes</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateField ColoradoZipCodes_WH ZipCodes !ZIP_CODE! Python # Text NO_ENFORCE_DOMAINS
ExportFeatures ColoradoZipCodes_WH "Z:\Photo Mapper\Mapping\ArcGIS Content\Projects\2024\38685_TJX_Denver_Labor&Transportation\38685_TJX_Denver_Labor&Transportation.gdb\Warehouse_Demos" # NOT_USE_ALIAS "ZIP_CODE "ZIP_CODE" true true false 10 Text 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.ZIP_CODE,0,9;PO_NAME "PO_NAME" true true false 100 Text 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.PO_NAME,0,99;STATE "STATE" true true false 2 Text 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.STATE,0,1;POPULATION "POPULATION_2022" true true false 4 Long 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.POPULATION,-1,-1;POP_SQMI "POP22_SQMI" true true false 8 Double 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.POP_SQMI,-1,-1;SQMI "SQMI" true true false 8 Double 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.SQMI,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.Shape_Area,-1,-1;ZipCodes "Zip Codes" true true false 8 Double 0 0,First,#,ColoradoZipCodes_WH,ColoradoZipCodes_WH.ZipCodes,-1,-1;ObjectID "ObjectID" false true false 4 Long 0 9,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.ObjectID,-1,-1;Status "Status" true true false 1 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Status,0,0;Score "Score" true true false 8 Double 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Score,-1,-1;Match_type "Match_type" true true false 2 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Match_type,0,1;Match_addr "Match_addr" true true false 500 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Match_addr,0,499;Addr_type "Addr_type" true true false 20 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Addr_type,0,19;ZIP "ZIP" true true false 4 Long 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.ZIP,-1,-1;ZIP_Name "ZIP Name" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.ZIP_Name,0,7999;F2023_Jobs "2023 Jobs" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.F2023_Jobs,0,7999;F2024_Jobs "2024 Jobs" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.F2024_Jobs,0,7999;F2023___2024_Change "2023 - 2024 Change" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.F2023___2024_Change,0,7999;F2023___2024___Change "2023 - 2024 % Change" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.F2023___2024___Change,0,7999;Avg__Hourly_Earnings "Avg. Hourly Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Avg__Hourly_Earnings,0,7999;Median_Hourly_Earnings "Median Hourly Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Median_Hourly_Earnings,0,7999;Median_Annual_Earnings "Median Annual Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.Median_Annual_Earnings,0,7999;COL_Index "COL Index" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.COL_Index,0,7999;COL_Adjusted_Avg__Hourly_Earnings "COL Adjusted Avg. Hourly Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.COL_Adjusted_Avg__Hourly_Earnings,0,7999;COL_Adjusted_Median_Hourly_Earnings "COL Adjusted Median Hourly Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.COL_Adjusted_Median_Hourly_Earnings,0,7999;COL_Adjusted_Median_Annual_Earnings "COL Adjusted Median Annual Earnings" true true false 8000 Text 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.COL_Adjusted_Median_Annual_Earnings,0,7999;ZipCodes "Zip Codes" true true false 8 Double 0 0,First,#,ColoradoZipCodes_WH,Warehouse_LightcastData.ZipCodes,-1,-1" #
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WorkspaceConnectionString>DATABASE=Z:\Photo Mapper\Mapping\ArcGIS Content\Projects\2024\38685_TJX_Denver_Labor&Transportation\38685_TJX_Denver_Labor&Transportation.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Warehouse_Demos</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>MedianHourlyEarnings</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>JobsCount2024</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateField Warehouse_Demos MedianHourlyEarnings !Median_Hourly_Earnings! Python # Text NO_ENFORCE_DOMAINS
CalculateField Warehouse_Demos JobsCount2024 !F2024_Jobs! Python # Text NO_ENFORCE_DOMAINS
20240924
13363400
20240924
13363400
Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.3.0.52636
38685_Warehouse_Demos
38685
Warehouse
TJX
File Geodatabase Feature Class
dataset
EPSG
6.2(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
Warehouse_Demos
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
ZIP_CODE
ZIP_CODE
String
10
0
0
PO_NAME
PO_NAME
String
100
0
0
STATE
STATE
String
2
0
0
POPULATION
POPULATION_2022
Integer
4
0
0
POP_SQMI
POP22_SQMI
Double
8
0
0
SQMI
SQMI
Double
8
0
0
ZipCodes
Zip Codes
Double
8
0
0
ObjectID_1
ObjectID
Integer
4
0
0
Status
Status
String
1
0
0
Score
Score
Double
8
0
0
Match_type
Match_type
String
2
0
0
Match_addr
Match_addr
String
500
0
0
Addr_type
Addr_type
String
20
0
0
ZIP
ZIP
Integer
4
0
0
ZIP_Name
ZIP Name
String
8000
0
0
F2023_Jobs
2023 Jobs
String
8000
0
0
F2024_Jobs
2024 Jobs
String
8000
0
0
F2023___2024_Change
2023 - 2024 Change
String
8000
0
0
F2023___2024___Change
2023 - 2024 % Change
String
8000
0
0
Avg__Hourly_Earnings
Avg. Hourly Earnings
String
8000
0
0
Median_Hourly_Earnings
Median Hourly Earnings
String
8000
0
0
Median_Annual_Earnings
Median Annual Earnings
String
8000
0
0
COL_Index
COL Index
String
8000
0
0
COL_Adjusted_Avg__Hourly_Earnings
COL Adjusted Avg. Hourly Earnings
String
8000
0
0
COL_Adjusted_Median_Hourly_Earnings
COL Adjusted Median Hourly Earnings
String
8000
0
0
COL_Adjusted_Median_Annual_Earnings
COL Adjusted Median Annual Earnings
String
8000
0
0
ZipCodes_1
Zip Codes
Double
8
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20240924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==