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West Virginia House Built in 2000-2010 Percentage County Rank

Based on ACS 2008-2012 data*

A total of 55 results found. Show Results on Map.

RankHouse Built in 2000-2010 Percentage ▼County / Population
1.27.6%Berkeley, WV / 104,410
2.21.5%Jefferson, WV / 53,545
3.18.0%Monongalia, WV / 96,417
4.12.7%Jackson, WV / 29,206
5.11.7%Nicholas, WV / 26,201
6.11.2%Mason, WV / 27,242
7.11.2%Putnam, WV / 55,660
8.11.2%Mingo, WV / 26,660
9.10.6%Lincoln, WV / 21,714
10.10.5%Morgan, WV / 17,507
11.10.4%Calhoun, WV / 7,613
12.10.2%Preston, WV / 33,471
13.9.8%Logan, WV / 36,508
14.9.8%Wayne, WV / 42,273
15.9.7%Greenbrier, WV / 35,572
16.9.6%Lewis, WV / 16,389
17.9.5%Boone, WV / 24,617
18.9.5%Raleigh, WV / 78,852
19.9.4%Gilmer, WV / 8,623
20.9.4%Braxton, WV / 14,531
21.9.2%Hardy, WV / 13,912
22.8.4%Wirt, WV / 5,769
23.8.4%Clay, WV / 9,432
24.8.3%Wyoming, WV / 23,668
25.8.1%Mercer, WV / 62,251
26.8.0%Pocahontas, WV / 8,750
27.8.0%Taylor, WV / 16,889
28.7.9%Cabell, WV / 96,240
29.7.8%Grant, WV / 11,929
30.7.6%Ritchie, WV / 10,391
31.7.4%Pleasants, WV / 7,630
32.7.2%Marion, WV / 56,460
32.7.2%Monroe, WV / 13,528
34.7.2%Tucker, WV / 7,109
35.7.0%Wood, WV / 86,835
36.7.0%Tyler, WV / 9,188
37.6.9%Kanawha, WV / 192,572
38.6.9%Harrison, WV / 68,959
39.6.9%Randolph, WV / 29,361
40.6.6%Upshur, WV / 24,210
41.6.3%Doddridge, WV / 8,147
42.6.2%Pendleton, WV / 7,666
43.6.0%Fayette, WV / 46,000
44.5.8%Roane, WV / 14,884
45.5.7%Summers, WV / 13,813
46.5.7%Barbour, WV / 16,472
47.5.5%Marshall, WV / 32,993
48.5.5%Hampshire, WV / 23,791
49.5.3%Mineral, WV / 28,049
49.5.3%Hancock, WV / 30,594
51.5.1%Wetzel, WV / 16,526
52.3.9%Webster, WV / 9,158
53.3.8%Ohio, WV / 44,307
54.3.7%Brooke, WV / 24,021
55.3.6%Mcdowell, WV / 21,966

Please note that we only rank locations with 'House Built in 2000-2010 Percentage' data. The rank above might not be a complete list. Locations without 'House Built in 2000-2010 Percentage' data are not listed.

*ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.


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