Zip Codes with the Highest Percentage of Germans in the United States

United States Report:

Percentage of Germans

#	Zip Code	Location	City	Population	% Germans	National Rank
1.	95225	38.183918, -120.898817	Burson, California	14	100.00 %	#1
2.	97909	44.243161, -117.428615	Jamieson, Oregon	49	100.00 %	#2
3.	02661	41.676348, -70.039690	South Harwich, Massachusetts	6	100.00 %	#3
4.	21560	39.563590, -78.707560	Spring Gap, Maryland	14	100.00 %	#4
5.	46513	41.362893, -86.448143	Donaldson, Indiana	56	100.00 %	#5
6.	76831	30.774588, -98.981276	Castell, Texas	12	100.00 %	#6
7.	50059	41.913646, -94.342972	Cooper, Iowa	14	100.00 %	#7
8.	59921	48.607014, -113.967218	Lake Mc Donald, Montana	2	100.00 %	#8
9.	67363	37.318966, -95.729059	Sycamore, Kansas	74	100.00 %	#10
10.	63433	39.560628, -91.184753	Ashburn, Missouri	56	100.00 %	#11
11.	45352	40.050152, -84.744321	Palestine, Ohio	170	100.00 %	#12
12.	45310	40.351490, -84.644934	Burkettsville, Ohio	132	90.09 %	#13
13.	65048	38.374157, -92.040877	Koeltztown, Missouri	144	88.75 %	#14
14.	45876	40.931740, -84.339941	Ottoville, Ohio	395	84.67 %	#15
15.	63370	39.080576, -91.223333	Olney, Missouri	41	82.85 %	#16
16.	56335	45.600957, -94.857364	Greenwald, Minnesota	163	81.95 %	#18
17.	53047	43.257124, -88.630120	Lebanon, Wisconsin	71	80.64 %	#19
18.	57420	45.313510, -100.171670	Akaska, South Dakota	92	80.23 %	#20
19.	54160	44.119267, -88.097853	Potter, Wisconsin	67	80.00 %	#21
20.	56325	45.562884, -94.947565	Elrosa, Minnesota	165	79.87 %	#22
21.	52056	42.603822, -91.072473	Luxemburg, Iowa	246	79.75 %	#23
22.	45883	40.399337, -84.636337	Saint Henry, Ohio	3,666	79.31 %	#24
23.	66962	39.606775, -97.131954	Palmer, Kansas	292	79.26 %	#25
24.	66404	39.890439, -96.172356	Baileyville, Kansas	622	78.66 %	#26
25.	17861	40.774286, -77.077739	Paxtonville, Pennsylvania	189	78.48 %	#27
26.	51444	42.007896, -94.988121	Halbur, Iowa	275	78.36 %	#28
27.	45860	40.399273, -84.516848	Maria Stein, Ohio	2,269	78.31 %	#29
28.	68774	42.812323, -97.292457	Saint Helena, Nebraska	315	77.50 %	#30
29.	46502	41.259706, -85.971725	Atwood, Indiana	62	77.41 %	#31
30.	45844	40.910907, -84.282481	Fort Jennings, Ohio	3,721	77.30 %	#32
31.	58430	47.529396, -100.269507	Denhoff, North Dakota	119	76.85 %	#33
32.	62950	37.746447, -89.560711	Jacob, Illinois	232	76.31 %	#34
33.	65076	38.363207, -92.211554	Saint Thomas, Missouri	891	76.00 %	#35
34.	62218	38.521487, -89.483560	Bartelso, Illinois	1,455	75.93 %	#36
35.	50649	42.662507, -92.910409	Kesley, Iowa	25	75.86 %	#37
36.	45828	40.483279, -84.671645	Coldwater, Ohio	6,302	75.86 %	#38
37.	47536	38.112705, -86.836185	Fulda, Indiana	38	75.00 %	#40
38.	56376	45.493374, -94.655155	Saint Martin, Minnesota	187	74.24 %	#41
39.	66412	39.907630, -96.777462	Bremen, Kansas	363	74.12 %	#42
40.	51430	42.099689, -95.025324	Arcadia, Iowa	879	74.11 %	#43
41.	62245	38.560604, -89.577161	Germantown, Illinois	2,490	74.06 %	#44
42.	63748	37.672210, -89.617350	Frohna, Missouri	1,127	74.01 %	#45
43.	52065	42.593678, -91.108655	New Vienna, Iowa	989	73.72 %	#46
44.	18936	40.220190, -75.229147	Montgomeryville, Pennsylvania	5	73.68 %	#47
45.	56331	45.678998, -94.671722	Freeport, Minnesota	1,747	73.57 %	#48
46.	68325	40.038056, -97.774758	Byron, Nebraska	284	73.07 %	#49
47.	45845	40.331338, -84.382544	Fort Loramie, Ohio	2,995	72.62 %	#50
48.	52631	40.779268, -91.610245	Houghton, Iowa	82	72.61 %	#51
49.	65001	38.282228, -92.023400	Argyle, Missouri	461	72.54 %	#52
50.	66518	39.965606, -96.550756	Oketo, Kansas	220	72.24 %	#53
51.	54978	44.794926, -88.912673	Tilleda, Wisconsin	44	71.92 %	#54
52.	50668	42.692909, -92.228832	Readlyn, Iowa	1,240	71.77 %	#55
53.	62216	38.602276, -89.602961	Aviston, Illinois	934	71.71 %	#56
54.	62462	39.238774, -88.468519	Sigel, Illinois	1,210	71.62 %	#57
55.	65016	38.564017, -91.926345	Bonnots Mill, Missouri	1,265	71.45 %	#58
56.	45853	40.985266, -84.198500	Kalida, Ohio	976	71.45 %	#59
57.	56294	44.319920, -95.219743	Wanda, Minnesota	108	71.29 %	#60
58.	62467	39.124426, -88.433806	Teutopolis, Illinois	3,664	71.27 %	#61
59.	48894	42.929669, -84.802326	Westphalia, Michigan	657	71.06 %	#62
60.	65085	38.398267, -92.060859	Westphalia, Missouri	1,061	70.69 %	#63
61.	58058	46.177154, -96.973969	Mantador, North Dakota	159	70.63 %	#64
62.	62962	37.055863, -89.329533	Miller City, Illinois	93	70.58 %	#65
63.	45846	40.405508, -84.744293	Fort Recovery, Ohio	4,306	70.51 %	#66
64.	47521	38.385436, -86.739138	Celestine, Indiana	797	70.31 %	#67
65.	47532	38.221208, -86.859736	Ferdinand, Indiana	4,593	70.22 %	#68
66.	47575	38.325177, -86.802060	Saint Anthony, Indiana	970	70.12 %	#69
67.	57331	43.474415, -98.044848	Dimock, South Dakota	476	69.87 %	#70
68.	51440	41.912966, -94.815573	Dedham, Iowa	432	69.85 %	#71
69.	52036	42.473210, -91.340719	Delaware, Iowa	188	69.53 %	#72
70.	53079	43.838714, -88.185195	Saint Cloud, Wisconsin	1,429	69.49 %	#73
71.	50680	42.447645, -92.922617	Wellsburg, Iowa	1,154	69.43 %	#74
72.	58572	46.902104, -100.298105	Sterling, North Dakota	213	69.23 %	#75
73.	68792	42.749640, -97.143921	Wynot, Nebraska	493	69.12 %	#76
74.	57466	45.223623, -99.481416	Onaka, South Dakota	182	69.10 %	#77
75.	82081	41.506324, -104.474808	Meriden, Wyoming	73	68.85 %	#78
76.	68422	40.386053, -96.701894	Pickrell, Nebraska	532	68.53 %	#79
77.	45865	40.394081, -84.366247	Minster, Ohio	4,766	68.51 %	#80
78.	43548	41.186821, -84.172615	New Bavaria, Ohio	720	68.49 %	#81
79.	47036	39.390081, -85.258420	Oldenburg, Indiana	666	68.43 %	#82
80.	45388	40.327999, -84.480220	Yorkshire, Ohio	939	68.40 %	#83
81.	62230	38.635097, -89.531001	Breese, Illinois	5,733	68.38 %	#84
82.	68324	40.559061, -96.279519	Burr, Nebraska	189	68.18 %	#85
83.	80426	39.865363, -106.949929	Burns, Colorado	89	68.05 %	#86
84.	48835	43.008196, -84.755622	Fowler, Michigan	3,420	67.87 %	#87
85.	51530	41.787452, -95.430485	Earling, Iowa	1,030	67.83 %	#88
86.	51463	41.908569, -94.921222	Templeton, Iowa	652	67.77 %	#89
87.	52767	41.566602, -90.421103	Pleasant Valley, Iowa	231	67.66 %	#90
88.	47580	38.349076, -86.764374	Schnellville, Indiana	170	67.62 %	#91
89.	67738	39.147584, -100.600529	Grinnell, Kansas	629	67.57 %	#92
90.	51578	41.719252, -95.395040	Westphalia, Iowa	137	67.54 %	#93
91.	57045	43.205008, -97.528384	Menno, South Dakota	1,138	67.38 %	#94
92.	45870	40.555793, -83.953263	New Hampshire, Ohio	85	67.24 %	#95
93.	50455	43.457863, -92.650183	Mc Intire, Iowa	510	67.19 %	#96
94.	65075	38.253165, -92.264926	Saint Elizabeth, Missouri	790	67.14 %	#97
95.	16361	41.383889, -79.345873	Tylersburg, Pennsylvania	77	67.10 %	#98
96.	56352	45.641800, -94.806359	Melrose, Minnesota	5,625	67.03 %	#99
97.	58569	46.268099, -101.199370	Shields, North Dakota	100	66.99 %	#100
98.	58460	46.326673, -99.329895	Lehr, North Dakota	305	66.98 %	#101
99.	63732	37.577851, -89.573328	Altenburg, Missouri	634	66.88 %	#102
100.	55339	44.724481, -93.939557	Hamburg, Minnesota	960	66.86 %	#103

1-100 out of 31,614 total

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% Apart./Condos
% Arabs
% Asians
% Blacks
% Bottled Gas
% Carpool to Work
% Children Under 10
% Chinese
% Coal / Coke
% College Grad.
% Construction Jobs
% Cubans
% Czechs
% Danish
% Detached
% Drive to Work
% Dutch
% Electrical
% English
% Farming Jobs
% Filipinos
% French
% French Canadians
% Fuel/Oil
% Germans
% Gov. Employees

% Greeks
% H/Income < $10k
% H/Income > $100k
% H/holds 1+ Car
% H/holds 2+ Cars
% High School Grad.
% Hispanics
% Hungarians
% In Agricultural
% In Arts
% In College
% In Construction
% In Finance
% In High School
% In IT
% In Labor Force
% In Labor Force (f)
% In Labor Force (m)
% In Manufacturing
% In Military
% In Retail Trade
% In Science
% In Social Work
% In Transportation
% Income Over $200k
% Indians (Asian)

% Irish
% Italians
% Japanese
% Korens
% Lithuanians
% Management Jobs
% Mexicans
% Natives
% No-Mortgage Prop.
% Norwegians
% Not in Labor Force
% Owner-Occupied
% Poles
% Portugese
% Poverty Level
% Poverty Level
% Production Jobs
% Properties < $200k
% Properties < $500k
% Properties > $1M
% Properties > $500k
% Pub/Transit
% Russians
% Sales Jobs
% Scotts
% Self-Employed

% Seniors Over 65
% Service Jobs
% Slovaks
% Solar Heated
% Swedes
% Swiss
% Tenant-Occupied
% Ukranians
% Unemployment Rate
% Utility Gas
% Vacant Homes
% Walk to Work
% Welsh
% West Indians
% Whites
% Wood Heated
% Work from Home
Avg. Income/H/hold
Avg. Income/Person
Avg. Population Age
Commute Time
Females / Male
Males / Female
People / Sq. Mile
Rooms / Home