20250228
09055900
1.0
FALSE
layer_DE_S1701_C03_002E_Clipped
002
file://\\DESKTOP-3NIS9O2\C$\Users\cdeal\OneDrive - American Institutes for Research in the Behavioral Sciences\Documents\ArcGIS\Projects\Redding\Redding.gdb
Local Area Network
Geographic
GCS_North_American_1983
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/3.1.0'><WKT>GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4269]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>1111948722.2222221</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>4269</WKID><LatestWKID>4269</LatestWKID></GeographicCoordinateSystem>
Select "\\dc1fs\DC1EHD\share\GIS Methods Group\DE CD\shapefile\tl_2023_10_tract.shp" "C:\Users\cdeal\OneDrive - American Institutes for Research in the Behavioral Sciences\Documents\ArcGIS\Projects\Redding\Redding.gdb\DE_Tracts" "GEOID <> '10003990100' And GEOID <> '10005990000' And GEOID <> '10001990000'"
AddField DE_Tracts new_ID "Double (64-bit floating point)" # # # # NULLABLE NON_REQUIRED #
CalculateField DE_Tracts new_ID !GEOID! "Python 3" # Text NO_ENFORCE_DOMAINS
JoinField DE_Tracts new_ID "\\dc1fs\DC1EHD\share\GIS Methods Group\DE CD\census_data.csv" geoID # "Select transfer fields" #
CopyFeatures DE_Tracts "C:\Users\cdeal\OneDrive - American Institutes for Research in the Behavioral Sciences\Documents\ArcGIS\Projects\Redding\Redding.gdb\layer_DE_S1701_C03_002E" # # # #
AlterField layer_DE_S1701_C03_002E S1701_C03_002E # "Children in Poverty (%)" "Double (64-bit floating point)" 8 NULLABLE DO_NOT_CLEAR
Clip layer_DE_S1701_C03_002E CityBoundaries_ExportFeature "C:\Users\cdeal\OneDrive - American Institutes for Research in the Behavioral Sciences\Documents\ArcGIS\Projects\Redding\Redding.gdb\layer_DE_S1701_C03_002E_Clipped" #
AddField layer_DE_S1701_C03_002E_Clipped NewVariable Text # # 50 # NULLABLE NON_REQUIRED #
CalculateField layer_DE_S1701_C03_002E_Clipped NewVariable 'child_pov' "Python 3" # Text NO_ENFORCE_DOMAINS
20250314
09161000
20250314
09161000
Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.1.3.41833
layer_DE_S1701_C03_002E_Clipped
Redding
Delaware
031425
clipped to Wilmington but state ranges
id=0
File Geodatabase Feature Class
dataset
EPSG
6.5(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
layer_DE_S1701_C03_002E_Clipped
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.
STATEFP
STATEFP
String
2
0
0
COUNTYFP
COUNTYFP
String
3
0
0
TRACTCE
TRACTCE
String
6
0
0
GEOID
GEOID
String
11
0
0
GEOIDFQ
GEOIDFQ
String
20
0
0
NAME
NAME
String
7
0
0
NAMELSAD
NAMELSAD
String
20
0
0
MTFCC
MTFCC
String
5
0
0
FUNCSTAT
FUNCSTAT
String
1
0
0
ALAND
ALAND
Double
8
0
0
AWATER
AWATER
Double
8
0
0
INTPTLAT
INTPTLAT
String
11
0
0
INTPTLON
INTPTLON
String
12
0
0
new_ID
new_ID
Double
8
0
0
Field1
Field1
Integer
4
0
0
DP02_0153PE
DP02_0153PE
Double
8
0
0
DP03_0025E
DP03_0025E
Double
8
0
0
geoID_1
geoID
Double
8
0
0
S2301_C02_002E
S2301_C02_002E
Double
8
0
0
S1701_C03_002E
Children in Poverty (%)
Double
8
0
0
S1701_C01_042E
S1701_C01_042E
Integer
4
0
0
S1701_C01_001E
S1701_C01_001E
Integer
4
0
0
all_pov
all_pov
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.
20250314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=