Description

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The layer presents the counties of the United States in the 50 states, the District of Columbia, and Puerto Rico. Below 1:3m scale it provides detailed boundaries that are consistent with the tract, block group, and state data sets and are effective at regional and state levels. Over 1:3m the county boundaries are generalized to improve draw performance and be used effectively at a national level. Both the detailed and generalized datasets are represented as polygons with over 40 attribute fields from the 2010 Census containing population totals by age and race, along with family and household information.

Dataset Attributes

  • OBJECTID
    Number
  • Shape
    Number
  • NAME
    Text
    {"value"=>"Baltimore City", "count"=>1} (), {"value"=>"Worcester", "count"=>1} (), {"value"=>"Wicomico", "count"=>1} (), {"value"=>"Washington", "count"=>1} (), {"value"=>"Talbot", "count"=>1} (), {"value"=>"Somerset", "count"=>1} (), {"value"=>"St. Mary's", "count"=>1} (), {"value"=>"Queen Anne's", "count"=>1} (), {"value"=>"Prince George's", "count"=>1} (), {"value"=>"Montgomery", "count"=>1} ()
  • STATE_NAME
    Text
    {"value"=>"Maryland", "count"=>24} ()
  • STATE_FIPS
    Text
    {"value"=>"24", "count"=>24} ()
  • CNTY_FIPS
    Text
    {"value"=>"510", "count"=>1} (), {"value"=>"047", "count"=>1} (), {"value"=>"045", "count"=>1} (), {"value"=>"043", "count"=>1} (), {"value"=>"041", "count"=>1} (), {"value"=>"039", "count"=>1} (), {"value"=>"037", "count"=>1} (), {"value"=>"035", "count"=>1} (), {"value"=>"033", "count"=>1} (), {"value"=>"031", "count"=>1} ()
  • FIPS
    Text
    {"value"=>"24510", "count"=>1} (), {"value"=>"24047", "count"=>1} (), {"value"=>"24045", "count"=>1} (), {"value"=>"24043", "count"=>1} (), {"value"=>"24041", "count"=>1} (), {"value"=>"24039", "count"=>1} (), {"value"=>"24037", "count"=>1} (), {"value"=>"24035", "count"=>1} (), {"value"=>"24033", "count"=>1} (), {"value"=>"24031", "count"=>1} ()
  • POP2014
    Number
    20486 to 1003571
  • POP14_SQMI
    Number
    46 to 7627.4
  • POP2010
    Number
    20197 to 971777
  • POP10_SQMI
    Number
    45.9 to 7630.4
  • WHITE
    Number
    14170 to 558358
  • BLACK
    Number
    301 to 556620
  • AMERI_ES
    Number
    42 to 4258
  • ASIAN
    Number
    76 to 135451
  • HAWN_PI
    Number
    0 to 541
  • HISPANIC
    Number
    220 to 165398
  • OTHER
    Number
    39 to 73441
  • MULT_RACE
    Number
    198 to 38645
  • MALES
    Number
    9640 to 466402
  • FEMALES
    Number
    10557 to 505375
  • AGE_UNDER5
    Number
    995 to 63732
  • AGE_5_9
    Number
    978 to 64300
  • AGE_10_14
    Number
    953 to 64663
  • AGE_15_19
    Number
    1505 to 67439
  • AGE_20_24
    Number
    1598 to 70644
  • AGE_25_34
    Number
    1830 to 132393
  • AGE_35_44
    Number
    2019 to 140565
  • AGE_45_54
    Number
    2946 to 153481
  • AGE_55_64
    Number
    2920 to 118981
  • AGE_65_74
    Number
    2029 to 62541
  • AGE_75_84
    Number
    1173 to 40325
  • AGE_85_UP
    Number
  • MED_AGE
    Number
  • MED_AGE_M
    Number
  • MED_AGE_F
    Number
  • HOUSEHOLDS
    Number
  • AVE_HH_SZ
    Number
  • HSEHLD_1_M
    Number
  • HSEHLD_1_F
    Number
  • MARHH_CHD
    Number
  • MARHH_NO_C
    Number
  • MHH_CHILD
    Number
  • FHH_CHILD
    Number
  • FAMILIES
    Number
  • AVE_FAM_SZ
    Number
  • HSE_UNITS
    Number
  • VACANT
    Number
  • OWNER_OCC
    Number
  • RENTER_OCC
    Number
  • NO_FARMS12
    Number
  • AVE_SIZE12
    Number
  • CROP_ACR12
    Number
  • AVE_SALE12
    Number
  • SQMI
    Number
  • Shape_Length
    Number
  • Shape_Area
    Number

About

  • By on March 23, 2017
  • Updated 8 months ago

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