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Demographic Comparison
Population
Highest PopulationHighest Population DensityLowest Population DensityMale / Female RatioFemale / Male RatioOldest PopulationOldest Population | MaleOldest Population | FemaleYoungest PopulationYoungest Population | MaleYoungest Population | Female
Families and Households
Largest Family SizeLargest Household SizeSmallest Family SizeSmallest Household Size
Female Fertility
Highest Birth Rate | All WomenHighest Birth Rate | Women 15-19Highest Birth Rate | Women 35+Highest Birth Rate | Below PovertyHighest Birth Rate | Public IncomeHighest Birth Rate | In Labor ForceLowest Birth Rate | All WomenLowest Birth Rate | Women 15-19Lowest Birth Rate | Women 35+Lowest Birth Rate | Below PovertyLowest Birth Rate | Public IncomeLowest Birth Rate | In Labor Force
Female Fertility (Unmarried)
Highest Illegitimacy | All WomenHighest Illegitimacy | Women 15-19Highest Illegitimacy | Women 35+Lowest Illegitimacy | All WomenLowest Illegitimacy | Women 15-19Lowest Illegitimacy | Women 35+
Race (Community Size)
AsianBlack / African AmericanHawaian / PacificHispanic or LatinoNative / AlaskanWhite / Caucasian
Race (Percentage)
AsianBlack / African AmericanHawaian / PacificHispanic or LatinoNative / AlaskanWhite / Caucasian
Ancestry (Community Size)
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Ancestry (Percentage)
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian / Chaldean / SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian / ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Economic Comparison
Income
Highest Per Capita IncomeHighest Earnings | MaleHighest Earnings | FemaleHighest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini IndexLowest Per Capita IncomeLowest Earnings | MaleLowest Earnings | FemaleLowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index
Income (Families)
Highest Family IncomeLowest Family IncomeFamily Income | $0-10kFamily Income | $100k+Family Income | $200k+
Income (Households)
Highest Household IncomeLowest Household IncomeHousehold Income | $0-10kHousehold Income | $200k+Household Income | $100k+
Poverty
Highest PovertyHighest Poverty | MaleHighest Poverty | FemaleHighest Poverty | Female 18-24Highest Poverty | Female 25-34Highest Poverty | Child 0-5Highest Poverty | Child 0-16Highest Poverty | Boys 0-16Highest Poverty | Girls 0-16Highest Poverty | Seniors 65+Highest Poverty | Seniors 75+ Lowest PovertyLowest Poverty | MaleLowest Poverty | FemaleLowest Poverty | Child 0-5Lowest Poverty | Child 0-16Lowest Poverty | Boys 0-16Lowest Poverty | Girls 0-16Lowest Poverty | Seniors 65+Lowest Poverty | Seniors 75+
Poverty (Families)
Highest Family PovertyHighest Poverty | Married CoupleHighest Poverty | Single MaleHighest Poverty | Single FemaleHighest Poverty | Single FatherHighest Poverty | Single MotherLowest Family PovertyLowest Poverty | Married CoupleLowest Poverty | Single MaleLowest Poverty | Single FemaleLowest Poverty | Single FatherLowest Poverty | Single Mother
Unemployment
Highest UnemploymentHighest Unemployment | MaleHighest Unemployment | FemaleHighest Unemployment | Youth < 25Highest Unemployment | Senior > 65Lowest UnemploymentLowest Unemployment | MaleLowest Unemployment | FemaleLowest Unemployment | Youth < 25Lowest Unemployment | Senior > 65
Employment Occupations
Architecture & EngineeringArts, Media & EntertainmentBusiness & FinancialCleaning & MaintenanceCommunity & Social Service Computer & MathematicsComputer, Engineering & ScienceConstruction & ExtractionEducation Instruction & LibraryEducation, Arts & MediaFarming, Fishing & ForestryFirefighting & PreventionFood Preparation & ServingHealth Diagnosing & TreatingHealth TechnologistsHealthcare SupportInstallation, Maintenance & RepairLaw EnforcementLegal Services & SupportLife, Physical & Social ScienceManagementMaterial MovingOffice & AdministrationPersonal Care and ServiceProductionSales & RelatedSecurity & ProtectionTransportation
Employment Industries
Accommodation & Food ServicesAdministrative & Support ServicesAgriculture, Fishing & HuntingArts, Entertainment & RecreationConstructionEducational ServicesEnterprise ManagementFinance & InsuranceHealth Care & Social AssistanceInformationManufacturingMining, Quarrying, & ExtractionProfessional & Scientific ServicesPublic AdministrationReal Estate, Rental & LeasingRetail TradeTransportation & WarehousingUtilitiesWholesale Trade
Employer Class
Private Company EmployeesSelf-Employed / IncorporatedSelf-Employed / Not IncorporatedNot-for-profit OrganizationsLocal Government EmployeesState Government EmployeesFederal Government EmployeesUnpaid Family Workers
Commute Time
Longest CommuteLongest Commute | MaleLongest Commute | FemaleShortest CommuteShortest Commute | MaleShortest Commute | Female
Commute Means
Drive | AloneDrive | CarpoolPublic TransitTaxi / CabWalk to WorkWork from Home
Education Comparison
School Enrollment
Nursery / PreschoolKindergartenElementary SchoolMiddle SchoolHigh SchoolCollegeUniversity
Education by Degree Field
Computers and MathematicsBio, Nature & AgriculturalPhysical and Health SciencesPsychologySocial SciencesEngineeringMultidisciplinary StudiesScience and EngineeringBusinessEducationLiterature and LanguagesLiberal Arts and HistoryVisual and Performing ArtsCommunicationsArts and Humanities
Housing Comparison
Occupancy
Highest Owner-OccupiedHighest Renter-OccupiedLowest Owner-OccupiedLowest Renter-Occupied
Finances
Highest Median Housing CostsHighest Property PricesHighest Owner Housing CostsHighest Renter Housing CostsHighest Housing Costs / IncomeLowest Median Housing CostsLowest Property PricesLowest Owner Housing CostsLowest Renter Housing CostsLowest Housing Costs / Income
Physical Characteristics
Detached Home ResidencyCondo/Apartment ResidencyUtility Gas HeatingBottled Gas / LP HeatingElectrical HeatingFuel Oil HeatingCoal / Coke HeatingFuel-less HeatingHouseholds without a CarsHouseholds with 1 or more CarsHouseholds with 2 or more CarsHouseholds with 3 or more Cars

Zip Codes with the Highest Percentage of Danish Population in Arizona

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Common Questions

What are the Top 10 Zip Codes with the Highest Percentage of Danish Population in Arizona?
Top 10 Zip Codes with the Highest Percentage of Danish Population in Arizona are:
#1
(8.09%)
#2
85923,
(6.61%)
#3
85939,
(6.51%)
#4
85328,
(5.45%)
#5
86338,
(4.77%)
#6
86022,
(4.31%)
#7
85640,
(4.02%)
#8
85937,
(3.96%)
#9
85324,
(3.86%)
#10
85925,
(3.77%)
What is the Perentage of Danish Population in the State of Arizona?
Perentage of Danish Population in Arizona is 0.61%.
What is the Perentage of Danish Population in the United States?
Perentage of Danish Population in the United States is 0.39%.

Percentage of Danish Population by Zip Code in Arizona

Zip CodeDanishvs. Statevs. National
1.86032, Arizona8.09%0.61%(+7.48)#10.39%(+7.70)#251
2.85923, 6.61%0.61%(+6.01)#20.39%(+6.22)#348
3.85939, 6.51%0.61%(+5.90)#30.39%(+6.12)#365
4.85328, 5.45%0.61%(+4.84)#40.39%(+5.06)#478
5.86338, 4.77%0.61%(+4.17)#50.39%(+4.38)#590
6.86022, 4.31%0.61%(+3.71)#60.39%(+3.92)#706
7.85640, 4.02%0.61%(+3.42)#70.39%(+3.63)#785
8.85937, 3.96%0.61%(+3.36)#80.39%(+3.57)#805
9.85324, 3.86%0.61%(+3.25)#90.39%(+3.47)#833
10.85925, 3.77%0.61%(+3.16)#100.39%(+3.38)#860
11.85934, 3.25%0.61%(+2.65)#110.39%(+2.86)#1,044
12.86021, 3.04%0.61%(+2.43)#120.39%(+2.65)#1,159
13.86334, 3.03%0.61%(+2.43)#130.39%(+2.64)#1,162
14.86017, 2.95%0.61%(+2.35)#140.39%(+2.56)#1,204
15.85554, 2.93%0.61%(+2.32)#150.39%(+2.54)#1,215
16.85920, 2.90%0.61%(+2.30)#160.39%(+2.51)#1,230
17.85137, 2.68%0.61%(+2.08)#170.39%(+2.29)#1,335
18.85739, 2.50%0.61%(+1.90)#180.39%(+2.11)#1,453
19.85929, 2.32%0.61%(+1.71)#190.39%(+1.93)#1,622
20.85536, 2.27%0.61%(+1.67)#200.39%(+1.88)#1,666
21.85928, 2.16%0.61%(+1.56)#210.39%(+1.77)#1,762
22.85749, 2.13%0.61%(+1.52)#220.39%(+1.74)#1,787
23.86025, 1.96%0.61%(+1.35)#230.39%(+1.57)#1,990
24.86333, 1.92%0.61%(+1.31)#240.39%(+1.53)#2,033
25.85901, 1.85%0.61%(+1.24)#250.39%(+1.46)#2,120
26.85045, 1.80%0.61%(+1.19)#260.39%(+1.41)#2,200
27.85325, 1.71%0.61%(+1.10)#270.39%(+1.32)#2,358
28.86432, 1.66%0.61%(+1.05)#280.39%(+1.27)#2,448
29.86327, 1.61%0.61%(+1.00)#290.39%(+1.22)#2,534
30.85028, 1.59%0.61%(+0.99)#300.39%(+1.20)#2,555
31.85118, 1.59%0.61%(+0.98)#310.39%(+1.20)#2,563
32.85120, 1.53%0.61%(+0.92)#320.39%(+1.14)#2,695
33.85622, 1.51%0.61%(+0.91)#330.39%(+1.12)#2,722
34.85205, 1.50%0.61%(+0.90)#340.39%(+1.11)#2,751
35.85375, 1.47%0.61%(+0.86)#350.39%(+1.08)#2,840
36.85213, 1.46%0.61%(+0.86)#360.39%(+1.07)#2,858
37.85262, 1.44%0.61%(+0.83)#370.39%(+1.05)#2,906
38.85715, 1.36%0.61%(+0.75)#380.39%(+0.97)#3,091
39.85373, 1.34%0.61%(+0.74)#390.39%(+0.95)#3,131
40.85258, 1.30%0.61%(+0.70)#400.39%(+0.91)#3,232
41.85123, 1.30%0.61%(+0.69)#410.39%(+0.91)#3,262
42.85614, 1.30%0.61%(+0.69)#420.39%(+0.91)#3,269
43.85203, 1.29%0.61%(+0.68)#430.39%(+0.90)#3,296
44.85747, 1.28%0.61%(+0.67)#440.39%(+0.89)#3,315
45.85390, 1.28%0.61%(+0.67)#450.39%(+0.89)#3,325
46.86301, 1.26%0.61%(+0.66)#460.39%(+0.87)#3,351
47.86442, 1.26%0.61%(+0.65)#470.39%(+0.87)#3,371
48.85630, 1.25%0.61%(+0.65)#480.39%(+0.86)#3,395
49.85396, 1.25%0.61%(+0.64)#490.39%(+0.86)#3,415
50.85284, 1.21%0.61%(+0.60)#500.39%(+0.82)#3,552
51.85637, 1.20%0.61%(+0.59)#510.39%(+0.81)#3,581
52.85650, 1.20%0.61%(+0.59)#520.39%(+0.81)#3,587
53.85212, 1.20%0.61%(+0.59)#530.39%(+0.81)#3,597
54.85050, 1.18%0.61%(+0.58)#540.39%(+0.79)#3,643
55.85297, 1.18%0.61%(+0.57)#550.39%(+0.79)#3,656
56.85543, 1.15%0.61%(+0.55)#560.39%(+0.76)#3,749
57.85250, 1.14%0.61%(+0.53)#570.39%(+0.75)#3,817
58.85296, 1.13%0.61%(+0.53)#580.39%(+0.74)#3,834
59.86324, 1.12%0.61%(+0.52)#590.39%(+0.73)#3,870
60.85348, 1.10%0.61%(+0.50)#600.39%(+0.71)#3,959
61.85298, 1.10%0.61%(+0.49)#610.39%(+0.71)#3,985
62.85145, 1.09%0.61%(+0.49)#620.39%(+0.70)#4,000
63.86351, 1.08%0.61%(+0.48)#630.39%(+0.69)#4,051
64.85295, 1.07%0.61%(+0.46)#640.39%(+0.68)#4,124
65.85658, 1.06%0.61%(+0.46)#650.39%(+0.67)#4,133
66.85755, 1.05%0.61%(+0.45)#660.39%(+0.66)#4,171
67.85142, 1.04%0.61%(+0.44)#670.39%(+0.65)#4,200
68.85248, 1.03%0.61%(+0.43)#680.39%(+0.64)#4,249
69.85606, 1.03%0.61%(+0.42)#690.39%(+0.64)#4,261
70.85209, 1.02%0.61%(+0.41)#700.39%(+0.63)#4,325
71.85924, 1.02%0.61%(+0.41)#710.39%(+0.63)#4,338
72.85194, 1.01%0.61%(+0.40)#720.39%(+0.62)#4,372
73.85351, 1.00%0.61%(+0.40)#730.39%(+0.61)#4,388
74.85253, 1.00%0.61%(+0.39)#740.39%(+0.61)#4,398
75.85085, 1.00%0.61%(+0.39)#750.39%(+0.61)#4,416
76.86406, 0.98%0.61%(+0.38)#760.39%(+0.59)#4,481
77.85615, 0.98%0.61%(+0.37)#770.39%(+0.59)#4,487
78.86404, 0.97%0.61%(+0.36)#780.39%(+0.58)#4,552
79.85128, 0.96%0.61%(+0.36)#790.39%(+0.57)#4,576
80.86004, 0.96%0.61%(+0.35)#800.39%(+0.57)#4,587
81.85206, 0.96%0.61%(+0.35)#810.39%(+0.57)#4,608
82.85641, 0.95%0.61%(+0.35)#820.39%(+0.56)#4,621
83.85257, 0.95%0.61%(+0.34)#830.39%(+0.56)#4,642
84.85234, 0.95%0.61%(+0.34)#840.39%(+0.56)#4,643
85.85750, 0.94%0.61%(+0.34)#850.39%(+0.55)#4,655
86.85251, 0.93%0.61%(+0.33)#860.39%(+0.54)#4,690
87.86040, 0.93%0.61%(+0.32)#870.39%(+0.54)#4,722
88.86440, 0.92%0.61%(+0.32)#880.39%(+0.54)#4,738
89.85320, 0.91%0.61%(+0.30)#890.39%(+0.52)#4,791
90.86336, 0.89%0.61%(+0.28)#900.39%(+0.50)#4,892
91.86444, 0.88%0.61%(+0.27)#910.39%(+0.49)#4,954
92.85268, 0.88%0.61%(+0.27)#920.39%(+0.49)#4,974
93.85204, 0.87%0.61%(+0.26)#930.39%(+0.48)#5,001
94.86305, 0.87%0.61%(+0.26)#940.39%(+0.48)#5,013
95.85367, 0.86%0.61%(+0.26)#950.39%(+0.47)#5,039
96.85737, 0.86%0.61%(+0.25)#960.39%(+0.47)#5,086
97.85342, 0.86%0.61%(+0.25)#970.39%(+0.47)#5,087
98.85024, 0.85%0.61%(+0.24)#980.39%(+0.46)#5,125
99.85044, 0.85%0.61%(+0.24)#990.39%(+0.46)#5,136
100.85603, 0.84%0.61%(+0.24)#1000.39%(+0.45)#5,159
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