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West Virginia House Built in 1960-1969 Percentage County Rank

Based on ACS 2008-2012 data*

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

RankHouse Built in 1960-1969 Percentage ▼County / Population
1.14.8%Hancock, WV / 30,594
2.14.6%Mineral, WV / 28,049
3.14.2%Hampshire, WV / 23,791
4.13.4%Wood, WV / 86,835
5.13.3%Brooke, WV / 24,021
6.12.4%Kanawha, WV / 192,572
7.12.3%Marshall, WV / 32,993
8.12.1%Cabell, WV / 96,240
9.12.0%Mason, WV / 27,242
10.11.8%Hardy, WV / 13,912
11.11.7%Jackson, WV / 29,206
12.11.4%Webster, WV / 9,158
13.11.2%Wayne, WV / 42,273
14.10.9%Ohio, WV / 44,307
15.10.8%Monongalia, WV / 96,417
16.10.6%Greenbrier, WV / 35,572
17.10.4%Wetzel, WV / 16,526
18.10.3%Randolph, WV / 29,361
19.10.2%Calhoun, WV / 7,613
20.10.2%Upshur, WV / 24,210
21.9.8%Wyoming, WV / 23,668
22.9.6%Tyler, WV / 9,188
23.9.5%Lewis, WV / 16,389
24.9.3%Lincoln, WV / 21,714
25.8.9%Harrison, WV / 68,959
26.8.8%Marion, WV / 56,460
27.8.8%Putnam, WV / 55,660
28.8.8%Summers, WV / 13,813
29.8.7%Morgan, WV / 17,507
30.8.6%Raleigh, WV / 78,852
31.8.5%Barbour, WV / 16,472
32.8.4%Gilmer, WV / 8,623
33.8.1%Taylor, WV / 16,889
34.8.1%Roane, WV / 14,884
35.8.1%Pleasants, WV / 7,630
36.7.9%Fayette, WV / 46,000
37.7.8%Jefferson, WV / 53,545
38.7.7%Clay, WV / 9,432
39.7.7%Mercer, WV / 62,251
40.7.5%Boone, WV / 24,617
41.7.5%Braxton, WV / 14,531
42.7.4%Wirt, WV / 5,769
43.6.9%Logan, WV / 36,508
44.6.5%Nicholas, WV / 26,201
45.6.5%Grant, WV / 11,929
46.6.5%Pendleton, WV / 7,666
47.6.3%Tucker, WV / 7,109
48.5.9%Monroe, WV / 13,528
49.5.7%Preston, WV / 33,471
50.5.5%Doddridge, WV / 8,147
50.5.5%Ritchie, WV / 10,391
52.5.4%Berkeley, WV / 104,410
53.5.3%Pocahontas, WV / 8,750
54.5.1%Mcdowell, WV / 21,966
55.3.2%Mingo, WV / 26,660

Please note that we only rank locations with 'House Built in 1960-1969 Percentage' data. The rank above might not be a complete list. Locations without 'House Built in 1960-1969 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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