Zip Codes with the Highest Percentage of Population Working from Home in the United States

United States Report:

Percentage of Population Working from Home

#	Zip Code	Location	City	Population	% Work from Home	National Rank
1.	18936	40.220190, -75.229147	Montgomeryville, Pennsylvania	5	100.00 %	#1
2.	89017	37.679878, -115.407429	Hiko, Nevada	130	100.00 %	#3
3.	72133	34.174795, -91.567555	Reydell, Arkansas	23	100.00 %	#4
4.	75434	33.425661, -95.391682	Cunningham, Texas	68	100.00 %	#5
5.	69219	42.687956, -101.037101	Nenzel, Nebraska	9	100.00 %	#6
6.	44690	40.616168, -81.692005	Winesburg, Ohio	67	85.00 %	#7
7.	98243	48.620140, -123.022775	Deer Harbor, Washington	141	81.39 %	#8
8.	59276	48.952233, -105.212453	Whitetail, Montana	71	76.92 %	#9
9.	99667	61.806241, -151.742977	Skwentna, Alaska	161	76.92 %	#10
10.	98833	48.627386, -120.446510	Mazama, Washington	96	75.00 %	#11
11.	81522	38.739630, -108.983003	Gateway, Colorado	61	73.07 %	#12
12.	57650	45.820761, -103.003917	Ralph, South Dakota	68	71.42 %	#13
13.	80862	38.924013, -103.055131	Wild Horse, Colorado	68	70.83 %	#14
14.	72711	36.404265, -94.071008	Avoca, Arkansas	26	70.00 %	#15
15.	59343	45.688683, -105.464483	Olive, Montana	135	68.96 %	#16
16.	26327	39.122071, -80.954106	Berea, West Virginia	67	66.66 %	#17
17.	68010	41.256275, -96.122902	Boys Town, Nebraska	775	65.71 %	#19
18.	98297	48.700506, -123.028733	Waldron, Washington	104	65.51 %	#20
19.	97909	44.243161, -117.428615	Jamieson, Oregon	49	64.70 %	#21
20.	57758	44.980444, -102.784344	Mud Butte, South Dakota	146	64.58 %	#22
21.	95250	38.244806, -120.417301	Sheep Ranch, California	87	63.63 %	#23
22.	59424	47.394232, -110.005500	Coffee Creek, Montana	22	63.63 %	#24
23.	56741	49.310491, -94.850100	Oak Island, Minnesota	31	63.15 %	#25
24.	97920	44.046768, -117.730036	Westfall, Oregon	37	62.50 %	#26
25.	57547	43.483939, -101.458224	Long Valley, South Dakota	161	62.50 %	#27
26.	59244	48.578706, -106.336522	Larslan, Montana	112	62.29 %	#28
27.	59332	45.346722, -104.828559	Hammond, Montana	186	62.13 %	#29
28.	97908	44.317558, -117.885909	Ironside, Oregon	74	61.76 %	#31
29.	88033	32.158215, -107.128065	Fairacres, New Mexico	49	61.53 %	#33
30.	83446	44.391011, -112.209911	Spencer, Idaho	26	61.53 %	#34
31.	57644	45.430009, -102.120481	Meadow, South Dakota	308	61.15 %	#35
32.	85922	33.557802, -109.275383	Blue, Arizona	36	60.00 %	#37
33.	59311	45.203101, -104.417307	Alzada, Montana	202	59.43 %	#38
34.	59545	48.950383, -111.111186	Whitlash, Montana	39	57.89 %	#39
35.	57457	45.877277, -99.154299	Longlake, South Dakota	125	57.14 %	#40
36.	88051	32.999133, -108.920356	Mule Creek, New Mexico	91	56.00 %	#41
37.	54834	45.742262, -91.476654	Edgewater, Wisconsin	15	55.55 %	#42
38.	57737	44.476477, -102.538899	Enning, South Dakota	49	54.16 %	#43
39.	57651	45.475472, -103.148843	Reva, South Dakota	150	53.42 %	#44
40.	57537	44.544939, -101.076340	Hayes, South Dakota	134	53.33 %	#45
41.	69354	42.490539, -103.218623	Marsland, Nebraska	65	52.77 %	#46
42.	59351	45.912524, -105.692352	Volborg, Montana	77	52.50 %	#47
43.	84621	39.073692, -111.884175	Axtell, Utah	203	52.50 %	#48
44.	59535	47.973035, -109.260996	Lloyd, Montana	97	52.30 %	#49
45.	59260	48.804563, -106.052603	Richland, Montana	142	51.72 %	#50
46.	83657	44.186914, -116.347219	Ola, Idaho	171	51.35 %	#51
47.	57272	45.083412, -97.481118	Wallace, South Dakota	223	50.64 %	#52
48.	58620	46.503569, -103.310980	Amidon, North Dakota	209	50.51 %	#53
49.	57755	45.846200, -103.331974	Ludlow, South Dakota	153	50.00 %	#54
50.	44850	41.034840, -82.677374	New Haven, Ohio	124	50.00 %	#55
51.	83463	45.599557, -113.910883	Gibbonsville, Idaho	53	50.00 %	#56
52.	04683	44.207632, -68.781091	Sunset, Maine	6	50.00 %	#57
53.	85263	33.735320, -111.688945	Rio Verde, Arizona	1,437	48.30 %	#58
54.	82243	41.974686, -104.395244	Veteran, Wyoming	130	48.27 %	#59
55.	87943	33.277286, -107.767367	Winston, New Mexico	169	47.36 %	#60
56.	79330	33.039383, -101.173427	Justiceburg, Texas	60	47.36 %	#61
57.	65484	37.375913, -92.234415	Huggins, Missouri	182	47.05 %	#63
58.	82837	44.790905, -106.198347	Leiter, Wyoming	28	47.05 %	#64
59.	58542	46.037412, -100.055829	Hague, North Dakota	413	46.78 %	#65
60.	59444	48.691083, -111.312762	Galata, Montana	210	46.75 %	#66
61.	58549	46.479104, -99.929710	Kintyre, North Dakota	267	46.72 %	#67
62.	57571	43.114752, -99.094968	Saint Charles, South Dakota	58	46.42 %	#69
63.	82061	41.445182, -105.161358	Horse Creek, Wyoming	21	46.15 %	#70
64.	67673	39.165730, -98.797503	Waldo, Kansas	143	46.00 %	#71
65.	57420	45.313510, -100.171670	Akaska, South Dakota	92	45.94 %	#72
66.	57585	43.557965, -100.384935	Wood, South Dakota	237	45.71 %	#73
67.	19435	40.327484, -75.569174	Frederick, Pennsylvania	73	45.45 %	#74
68.	83677	45.052143, -115.517963	Yellow Pine, Idaho	45	45.00 %	#75
69.	58564	46.277147, -101.372036	Raleigh, North Dakota	166	44.54 %	#77
70.	78001	28.261342, -99.294419	Artesia Wells, Texas	41	44.44 %	#78
71.	84762	37.460877, -112.759879	Duck Creek Village, Utah	94	44.44 %	#79
72.	81081	37.065471, -104.155847	Trinchera, Colorado	73	44.44 %	#80
73.	83821	48.620392, -116.848771	Coolin, Idaho	230	44.08 %	#81
74.	58430	47.529396, -100.269507	Denhoff, North Dakota	119	43.75 %	#82
75.	80754	40.790259, -103.666954	Stoneham, Colorado	147	43.67 %	#83
76.	57649	45.526333, -102.900156	Prairie City, South Dakota	232	43.51 %	#84
77.	57467	44.829333, -99.186772	Orient, South Dakota	316	43.44 %	#85
78.	57540	44.461425, -99.607861	Holabird, South Dakota	132	43.42 %	#86
79.	58627	47.239896, -103.262066	Fairfield, North Dakota	143	43.18 %	#87
80.	57576	43.944029, -100.269373	Vivian, South Dakota	216	42.97 %	#88
81.	69157	42.168783, -100.413195	Purdum, Nebraska	108	42.85 %	#89
82.	69161	42.130306, -100.721767	Seneca, Nebraska	194	42.74 %	#90
83.	59537	48.853029, -107.936993	Loring, Montana	126	42.35 %	#91
84.	58641	46.667130, -102.486272	Lefor, North Dakota	107	42.10 %	#92
85.	58847	47.861374, -102.887795	Keene, North Dakota	258	41.90 %	#93
86.	58013	46.057851, -97.353266	Cayuga, North Dakota	184	41.79 %	#94
87.	59025	45.118822, -106.673672	Decker, Montana	96	41.77 %	#95
88.	97711	44.748677, -120.748099	Ashwood, Oregon	95	41.66 %	#96
89.	95637	38.830739, -122.196202	Guinda, California	226	41.26 %	#98
90.	82242	42.697234, -104.138077	Van Tassell, Wyoming	51	41.02 %	#99
91.	97033	45.197868, -120.580572	Kent, Oregon	74	40.90 %	#100
92.	97710	42.133464, -118.579797	Fields, Oregon	86	40.90 %	#101
93.	59058	47.025164, -107.805201	Mosby, Montana	40	40.74 %	#102
94.	57271	44.739380, -97.522039	Vienna, South Dakota	463	40.72 %	#103
95.	57256	45.236003, -97.202744	Ortley, South Dakota	98	40.54 %	#104
96.	59062	45.170138, -106.088702	Otter, Montana	79	40.00 %	#105
97.	58856	48.581390, -103.724351	Zahl, North Dakota	127	40.00 %	#106
98.	99695	61.426177, -150.677083	Anchorage, Alaska	35	40.00 %	#107
99.	59074	46.429258, -109.299461	Ryegate, Montana	604	40.00 %	#108
100.	58440	46.300153, -99.153841	Fredonia, North Dakota	213	39.77 %	#109

1-100 out of 31,697 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