Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota

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Shortest Commute | Female
Population
Families and Households
Female Fertility
Female Fertility (Unmarried)
Race (Community Size)
Race (Percentage)
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
Income
Income (Families)
Income (Households)
Poverty
Poverty (Families)
Unemployment
Employment Occupations
Employment Industries
Employer Class
Commute Time
Commute Means
School Enrollment
Education by Degree Field
Occupancy
Finances
Physical Characteristics
North Dakota
Compare Zip Codes
Comparison Subject

Map of Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota

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Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota Map

Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota

Zip Code Commute Time vs State vs National
1.5870700:05:2200:16:11(-10.8)#100:24:50(-19.5)#125
2.5870500:05:3600:16:11(-10.6)#200:24:50(-19.2)#140
3.5840500:05:3900:16:11(-10.5)#300:24:50(-19.2)#142
4.5820200:07:0300:16:11(-9.13)#400:24:50(-17.8)#224
5.5807600:07:2100:16:11(-8.82)#500:24:50(-17.5)#238
6.5877800:07:3000:16:11(-8.68)#600:24:50(-17.3)#249
7.5832400:07:5500:16:11(-8.26)#700:24:50(-16.9)#277
8.5876500:08:0500:16:11(-8.10)#800:24:50(-16.8)#297
9.5827100:08:2400:16:11(-7.77)#900:24:50(-16.4)#327
10.5864600:09:0500:16:11(-7.09)#1000:24:50(-15.7)#395
11.5842100:09:1800:16:11(-6.88)#1100:24:50(-15.5)#425
12.5836700:09:2100:16:11(-6.83)#1200:24:50(-15.5)#432
13.5875200:09:2300:16:11(-6.80)#1300:24:50(-15.5)#436
14.5844100:09:2300:16:11(-6.79)#1400:24:50(-15.5)#438
15.5849500:09:4800:16:11(-6.37)#1500:24:50(-15.0)#491
16.5833500:09:5200:16:11(-6.32)#1600:24:50(-15.0)#500
17.5885200:09:5200:16:11(-6.30)#1700:24:50(-15.0)#502
18.5843800:10:0700:16:11(-6.06)#1800:24:50(-14.7)#555
19.5852300:10:2700:16:11(-5.72)#1900:24:50(-14.4)#604
20.5802700:10:3000:16:11(-5.68)#2000:24:50(-14.3)#613
21.5804000:10:3100:16:11(-5.66)#2100:24:50(-14.3)#621
22.5834100:10:3600:16:11(-5.57)#2200:24:50(-14.2)#637
23.5862300:10:3700:16:11(-5.56)#2300:24:50(-14.2)#640
24.5874600:11:1000:16:11(-5.01)#2400:24:50(-13.7)#761
25.5871100:11:1500:16:11(-4.93)#2500:24:50(-13.6)#776
26.5830100:11:2300:16:11(-4.79)#2600:24:50(-13.4)#816
27.5810500:11:2400:16:11(-4.77)#2700:24:50(-13.4)#822
28.5863900:11:5100:16:11(-4.33)#2800:24:50(-13.0)#967
29.5860100:11:5100:16:11(-4.32)#2900:24:50(-13.0)#971
30.5876900:11:5500:16:11(-4.26)#3000:24:50(-12.9)#996
31.5856200:11:5900:16:11(-4.20)#3100:24:50(-12.9)#1,015
32.5835600:12:0500:16:11(-4.10)#3200:24:50(-12.8)#1,048
33.5836800:12:0700:16:11(-4.06)#3300:24:50(-12.7)#1,057
34.5853100:12:0800:16:11(-4.04)#3400:24:50(-12.7)#1,066
35.5827300:12:1100:16:11(-4.00)#3500:24:50(-12.7)#1,076
36.5856500:12:1100:16:11(-3.99)#3600:24:50(-12.6)#1,078
37.5822000:12:1200:16:11(-3.98)#3700:24:50(-12.6)#1,082
38.5848200:12:1500:16:11(-3.92)#3800:24:50(-12.6)#1,092
39.5825700:12:1900:16:11(-3.85)#3900:24:50(-12.5)#1,112
40.5878800:12:3000:16:11(-3.68)#4000:24:50(-12.3)#1,152
41.5843300:12:3700:16:11(-3.56)#4100:24:50(-12.2)#1,185
42.5843600:12:3800:16:11(-3.54)#4200:24:50(-12.2)#1,195
43.5864000:12:3900:16:11(-3.52)#4300:24:50(-12.2)#1,202
44.5824100:12:3900:16:11(-3.52)#4400:24:50(-12.2)#1,203
45.5807200:12:4000:16:11(-3.50)#4500:24:50(-12.2)#1,209
46.5841300:12:4200:16:11(-3.47)#4600:24:50(-12.1)#1,221
47.5842500:12:4500:16:11(-3.43)#4700:24:50(-12.1)#1,241
48.5850100:13:0000:16:11(-3.18)#4800:24:50(-11.8)#1,343
49.5837000:13:0300:16:11(-3.13)#4900:24:50(-11.8)#1,360
50.5823700:13:1000:16:11(-3.01)#5000:24:50(-11.7)#1,406
51.5880100:13:1400:16:11(-2.93)#5100:24:50(-11.6)#1,433
52.5807500:13:1600:16:11(-2.90)#5200:24:50(-11.6)#1,446
53.5823000:13:2200:16:11(-2.80)#5300:24:50(-11.5)#1,485
54.5824900:13:2300:16:11(-2.78)#5400:24:50(-11.4)#1,492
55.5864900:13:2400:16:11(-2.78)#5500:24:50(-11.4)#1,494
56.5856100:13:3700:16:11(-2.56)#5600:24:50(-11.2)#1,565
57.5820400:13:3800:16:11(-2.53)#5700:24:50(-11.2)#1,581
58.5843000:13:4500:16:11(-2.43)#5800:24:50(-11.1)#1,634
59.5870100:13:4600:16:11(-2.40)#5900:24:50(-11.1)#1,650
60.5840100:14:0000:16:11(-2.17)#6000:24:50(-10.8)#1,766
61.5831600:14:0500:16:11(-2.09)#6100:24:50(-10.8)#1,801
62.5831100:14:0900:16:11(-2.02)#6200:24:50(-10.7)#1,844
63.5810200:14:1700:16:11(-1.90)#6300:24:50(-10.6)#1,906
64.5870300:14:1900:16:11(-1.85)#6400:24:50(-10.5)#1,921
65.5820300:14:2100:16:11(-1.83)#6500:24:50(-10.5)#1,928
66.5834400:14:2300:16:11(-1.80)#6600:24:50(-10.5)#1,953
67.5876300:14:2700:16:11(-1.73)#6700:24:50(-10.4)#1,988
68.5853800:14:2900:16:11(-1.69)#6800:24:50(-10.3)#2,014
69.5878400:14:3100:16:11(-1.65)#6900:24:50(-10.3)#2,039
70.5820100:14:3200:16:11(-1.64)#7000:24:50(-10.3)#2,043
71.5883500:14:3200:16:11(-1.64)#7100:24:50(-10.3)#2,045
72.5873000:14:3700:16:11(-1.55)#7200:24:50(-10.2)#2,103
73.5822200:14:4300:16:11(-1.46)#7300:24:50(-10.1)#2,165
74.5877500:14:5400:16:11(-1.28)#7400:24:50(-9.94)#2,276
75.5857700:14:5400:16:11(-1.27)#7500:24:50(-9.93)#2,281
76.5805400:15:0600:16:11(-1.08)#7600:24:50(-9.74)#2,386
77.5857300:15:1000:16:11(-1.01)#7700:24:50(-9.67)#2,425
78.5862600:15:2200:16:11(-0.810)#7800:24:50(-9.47)#2,554
79.5870400:15:2800:16:11(-0.703)#7900:24:50(-9.36)#2,643
80.5850300:15:2900:16:11(-0.689)#8000:24:50(-9.35)#2,651
81.5873600:15:4000:16:11(-0.508)#8100:24:50(-9.17)#2,756
82.5831800:15:4000:16:11(-0.503)#8200:24:50(-9.16)#2,759
83.5841500:15:4100:16:11(-0.494)#8300:24:50(-9.15)#2,767
84.5827400:15:4200:16:11(-0.477)#8400:24:50(-9.13)#2,783
85.5810300:15:4800:16:11(-0.380)#8500:24:50(-9.04)#2,867
86.5878300:15:5500:16:11(-0.258)#8600:24:50(-8.92)#2,955
87.5847400:15:5700:16:11(-0.224)#8700:24:50(-8.88)#2,980
88.5835100:16:0400:16:11(-0.116)#8800:24:50(-8.77)#3,079
89.5850400:16:0600:16:11(-0.076)#8900:24:50(-8.73)#3,111
90.5864500:16:0800:16:11(-0.038)#9000:24:50(-8.70)#3,142
91.5826500:16:1500:16:11(+0.066)#9100:24:50(-8.59)#3,222
92.5844300:16:1500:16:11(+0.066)#9200:24:50(-8.59)#3,228
93.5826700:16:1700:16:11(+0.104)#9300:24:50(-8.55)#3,254
94.5827000:16:2000:16:11(+0.163)#9400:24:50(-8.50)#3,308
95.5804500:16:2200:16:11(+0.184)#9500:24:50(-8.47)#3,324
96.5863400:16:2500:16:11(+0.245)#9600:24:50(-8.41)#3,379
97.5831300:16:2500:16:11(+0.245)#9700:24:50(-8.41)#3,381
98.5885400:16:2600:16:11(+0.264)#9800:24:50(-8.39)#3,402
99.5846300:16:2900:16:11(+0.312)#9900:24:50(-8.35)#3,458
100.5810400:16:3100:16:11(+0.338)#10000:24:50(-8.32)#3,490

Common Questions

What are the Top 10 Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota?
Top 10 Zip Codes with the Shortest Median Commute Time to Work for Females in North Dakota are:
#1
00:05:22
#2
00:05:36
#3
00:05:39
#4
00:07:03
#5
00:07:21
#6
00:07:30
#7
00:07:55
#8
00:08:05
#9
00:08:24
#10
00:09:05
What zip code has the Shortest Median Commute Time to Work for Females in North Dakota?
58707 has the Shortest Median Commute Time to Work for Females in North Dakota with 00:05:22.
What is the Median Commute Time to Work for Females in the State of North Dakota?
Median Commute Time to Work for Females in North Dakota is 00:16:11.
What is the Median Commute Time to Work for Females in the United States?
Median Commute Time to Work for Females in the United States is 00:24:50.