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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 AmericanHawaiian / PacificHispanic or LatinoNative / AlaskanWhite / Caucasian
Race (Percentage)
AsianBlack / African AmericanHawaiian / 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
Immigrant Origin (Total)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
Immigrant Origin (Percentage)
AfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaAzoresBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma / MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabwe
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 AssistanceInformation & TechnologyManufacturingMining, 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
In Private SchoolNursery / 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 Largest Nepalese Community in New York

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Common Questions

What are the Top 10 Zip Codes with the Largest Nepalese Community in New York?
Top 10 Zip Codes with the Largest Nepalese Community in New York are:
#1
3,213
#2
2,726
#3
832
#4
805
#5
723
#6
583
#7
528
#8
518
#9
444
#10
442
What zip code has the Largest Nepalese Community in New York?
11373 has the Largest Nepalese Community in New York with 3,213.
What is the Total Nepalese Population in the State of New York?
Total Nepalese Population in New York is 20,109.
What is the Total Nepalese Population in the United States?
Total Nepalese Population in the United States is 191,291.

Map of Zip Codes with the Largest Nepalese Community in New York

0
4,000
Zip Codes with the Largest Nepalese Community in New York Map

Zip Codes with the Largest Nepalese Community in New York

Zip Codes with the Largest Nepalese Community in New York Chart
Zip Code Nepalese vs State vs National
1.113733,21320,109(15.98%)#1191,291(1.68%)#1
2.113772,72620,109(13.56%)#2191,291(1.43%)#2
3.1421383220,109(4.14%)#3191,291(0.43%)#22
4.1136880520,109(4.00%)#4191,291(0.42%)#25
5.1137272320,109(3.60%)#5191,291(0.38%)#33
6.1420758320,109(2.90%)#6191,291(0.30%)#44
7.1138552820,109(2.63%)#7191,291(0.28%)#52
8.1137451820,109(2.58%)#8191,291(0.27%)#55
9.1461344420,109(2.21%)#9191,291(0.23%)#76
10.1460544220,109(2.20%)#10191,291(0.23%)#77
11.1462443520,109(2.16%)#11191,291(0.23%)#81
12.1458636220,109(1.80%)#12191,291(0.19%)#101
13.1190132320,109(1.61%)#13191,291(0.17%)#114
14.1460829920,109(1.49%)#14191,291(0.16%)#130
15.1141929720,109(1.48%)#15191,291(0.16%)#132
16.1180129520,109(1.47%)#16191,291(0.15%)#134
17.1320827820,109(1.38%)#17191,291(0.15%)#143
18.1110426020,109(1.29%)#18191,291(0.14%)#156
19.1350125820,109(1.28%)#19191,291(0.13%)#159
20.1137524620,109(1.22%)#20191,291(0.13%)#168
21.1137924420,109(1.21%)#21191,291(0.13%)#171
22.1137822020,109(1.09%)#22191,291(0.12%)#191
23.1320320720,109(1.03%)#23191,291(0.11%)#208
24.1046119420,109(0.96%)#24191,291(0.10%)#224
25.1258618820,109(0.93%)#25191,291(0.10%)#232
26.1135417620,109(0.88%)#26191,291(0.09%)#248
27.1122617020,109(0.85%)#27191,291(0.09%)#254
28.1218917020,109(0.85%)#28191,291(0.09%)#257
29.1321115820,109(0.79%)#29191,291(0.08%)#289
30.1220414720,109(0.73%)#30191,291(0.08%)#320
31.1143514520,109(0.72%)#31191,291(0.08%)#327
32.1052813120,109(0.65%)#32191,291(0.07%)#363
33.1137013020,109(0.65%)#33191,291(0.07%)#366
34.1462012220,109(0.61%)#34191,291(0.06%)#388
35.1136012220,109(0.61%)#35191,291(0.06%)#389
36.1122111920,109(0.59%)#36191,291(0.06%)#399
37.1110511820,109(0.59%)#37191,291(0.06%)#404
38.1051911520,109(0.57%)#38191,291(0.06%)#418
39.1461510320,109(0.51%)#39191,291(0.05%)#459
40.104729920,109(0.49%)#40191,291(0.05%)#471
41.113629820,109(0.49%)#41191,291(0.05%)#482
42.100139320,109(0.46%)#42191,291(0.05%)#506
43.146118620,109(0.43%)#43191,291(0.04%)#553
44.100178420,109(0.42%)#44191,291(0.04%)#562
45.100448420,109(0.42%)#45191,291(0.04%)#563
46.100297820,109(0.39%)#46191,291(0.04%)#595
47.113697820,109(0.39%)#47191,291(0.04%)#599
48.124847720,109(0.38%)#48191,291(0.04%)#609
49.114327120,109(0.35%)#49191,291(0.04%)#650
50.146066720,109(0.33%)#50191,291(0.04%)#676
51.142256420,109(0.32%)#51191,291(0.03%)#697
52.120616220,109(0.31%)#52191,291(0.03%)#722
53.117565920,109(0.29%)#53191,291(0.03%)#742
54.146075720,109(0.28%)#54191,291(0.03%)#763
55.103145620,109(0.28%)#55191,291(0.03%)#766
56.132245620,109(0.28%)#56191,291(0.03%)#779
57.146235520,109(0.27%)#57191,291(0.03%)#790
58.112065120,109(0.25%)#58191,291(0.03%)#823
59.141205020,109(0.25%)#59191,291(0.03%)#843
60.130784920,109(0.24%)#60191,291(0.03%)#863
61.144564820,109(0.24%)#61191,291(0.03%)#871
62.114174720,109(0.23%)#62191,291(0.02%)#881
63.100364720,109(0.23%)#63191,291(0.02%)#883
64.119514620,109(0.23%)#64191,291(0.02%)#900
65.103014420,109(0.22%)#65191,291(0.02%)#920
66.109544420,109(0.22%)#66191,291(0.02%)#924
67.125344320,109(0.21%)#67191,291(0.02%)#946
68.136764220,109(0.21%)#68191,291(0.02%)#962
69.114214120,109(0.20%)#69191,291(0.02%)#969
70.113554020,109(0.20%)#70191,291(0.02%)#979
71.100024020,109(0.20%)#71191,291(0.02%)#980
72.112384020,109(0.20%)#72191,291(0.02%)#981
73.112153920,109(0.19%)#73191,291(0.02%)#1,004
74.132123920,109(0.19%)#74191,291(0.02%)#1,013
75.105493920,109(0.19%)#75191,291(0.02%)#1,016
76.121803820,109(0.19%)#76191,291(0.02%)#1,019
77.125243820,109(0.19%)#77191,291(0.02%)#1,030
78.135023720,109(0.18%)#78191,291(0.02%)#1,041
79.112183620,109(0.18%)#79191,291(0.02%)#1,046
80.133263520,109(0.17%)#80191,291(0.02%)#1,070
81.142213320,109(0.16%)#81191,291(0.02%)#1,093
82.112283220,109(0.16%)#82191,291(0.02%)#1,108
83.105833020,109(0.15%)#83191,291(0.02%)#1,140
84.105733020,109(0.15%)#84191,291(0.02%)#1,141
85.104672920,109(0.14%)#85191,291(0.02%)#1,155
86.148502920,109(0.14%)#86191,291(0.02%)#1,156
87.131262820,109(0.14%)#87191,291(0.01%)#1,184
88.114272820,109(0.14%)#88191,291(0.01%)#1,191
89.112252720,109(0.13%)#89191,291(0.01%)#1,198
90.129012620,109(0.13%)#90191,291(0.01%)#1,235
91.115902520,109(0.12%)#91191,291(0.01%)#1,248
92.105982520,109(0.12%)#92191,291(0.01%)#1,255
93.105142520,109(0.12%)#93191,291(0.01%)#1,263
94.148772520,109(0.12%)#94191,291(0.01%)#1,267
95.117062320,109(0.11%)#95191,291(0.01%)#1,286
96.123092320,109(0.11%)#96191,291(0.01%)#1,294
97.100012320,109(0.11%)#97191,291(0.01%)#1,295
98.112082220,109(0.11%)#98191,291(0.01%)#1,305
99.112162220,109(0.11%)#99191,291(0.01%)#1,307
100.110302220,109(0.11%)#100191,291(0.01%)#1,334
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