Local Data Search
A total of 92 results found. Show Results on Map.
| Rank | Married-Couple Family Household Percentage ▼ | County / Population |
| 1. | 67.20% | Lagrange, IN / 36,857 |
| 2. | 65.15% | Warrick, IN / 57,065 |
| 3. | 63.97% | Hancock, IN / 65,777 |
| 4. | 63.73% | Spencer, IN / 20,167 |
| 5. | 63.53% | Boone, IN / 53,931 |
| 6. | 63.38% | Harrison, IN / 36,973 |
| 7. | 63.17% | Hamilton, IN / 261,328 |
| 8. | 63.11% | Brown, IN / 14,724 |
| 9. | 62.75% | Ohio, IN / 5,871 |
| 10. | 62.62% | Hendricks, IN / 133,949 |
| 11. | 62.42% | Morgan, IN / 70,179 |
| 12. | 62.17% | Union, IN / 7,083 |
| 13. | 62.02% | Franklin, IN / 23,074 |
| 14. | 61.97% | Carroll, IN / 19,863 |
| 15. | 61.14% | Dearborn, IN / 49,608 |
| 16. | 60.83% | Pulaski, IN / 13,739 |
| 17. | 60.70% | Posey, IN / 26,244 |
| 18. | 60.23% | Dubois, IN / 41,207 |
| 19. | 60.09% | Warren, IN / 8,573 |
| 20. | 60.01% | Clay, IN / 26,682 |
| 21. | 59.95% | Newton, IN / 13,974 |
| 22. | 59.91% | Marshall, IN / 46,605 |
| 23. | 59.86% | Jasper, IN / 32,197 |
| 24. | 59.18% | Adams, IN / 33,955 |
| 25. | 59.11% | White, IN / 23,840 |
| 26. | 59.08% | Putnam, IN / 36,993 |
| 27. | 59.03% | Noble, IN / 47,729 |
| 28. | 58.11% | Whitley, IN / 32,504 |
| 29. | 57.93% | Wells, IN / 27,720 |
| 30. | 57.92% | Johnson, IN / 136,081 |
| 31. | 57.90% | Pike, IN / 12,496 |
| 32. | 57.84% | Ripley, IN / 27,378 |
| 33. | 57.75% | Rush, IN / 17,425 |
| 34. | 57.58% | Orange, IN / 19,536 |
| 35. | 57.42% | Huntington, IN / 37,890 |
| 36. | 57.38% | Jackson, IN / 42,131 |
| 37. | 57.31% | Kosciusko, IN / 76,096 |
| 38. | 57.25% | Wabash, IN / 33,004 |
| 39. | 57.21% | Owen, IN / 22,371 |
| 40. | 57.14% | Clinton, IN / 34,081 |
| 41. | 57.10% | Decatur, IN / 25,066 |
| 42. | 57.03% | Shelby, IN / 43,964 |
| 43. | 57.00% | Tipton, IN / 16,055 |
| 44. | 56.97% | Montgomery, IN / 37,828 |
| 45. | 56.64% | Bartholomew, IN / 74,681 |
| 46. | 56.17% | De Kalb, IN / 41,759 |
| 47. | 56.03% | Henry, IN / 47,481 |
| 48. | 56.02% | Porter, IN / 160,073 |
| 49. | 55.71% | Lawrence, IN / 45,891 |
| 50. | 55.62% | Steuben, IN / 33,544 |
| 51. | 55.52% | Cass, IN / 39,263 |
| 52. | 54.90% | Daviess, IN / 30,205 |
| 53. | 54.76% | Vermillion, IN / 16,301 |
| 54. | 54.64% | Elkhart, IN / 197,851 |
| 54. | 54.64% | Martin, IN / 10,067 |
| 56. | 54.57% | Miami, IN / 36,508 |
| 57. | 54.34% | Randolph, IN / 25,914 |
| 58. | 54.28% | Fulton, IN / 20,251 |
| 59. | 54.26% | Starke, IN / 23,398 |
| 60. | 53.94% | Washington, IN / 27,780 |
| 61. | 53.86% | Benton, IN / 8,723 |
| 62. | 53.83% | Howard, IN / 83,685 |
| 63. | 53.53% | Crawford, IN / 10,795 |
| 64. | 53.20% | Greene, IN / 32,715 |
| 65. | 53.12% | Fountain, IN / 17,075 |
| 66. | 53.10% | Switzerland, IN / 9,627 |
| 67. | 53.00% | Gibson, IN / 32,834 |
| 68. | 52.99% | Scott, IN / 23,646 |
| 69. | 52.76% | Jennings, IN / 28,052 |
| 70. | 52.67% | Fayette, IN / 24,313 |
| 71. | 52.09% | Floyd, IN / 73,031 |
| 72. | 51.97% | Parke, IN / 17,094 |
| 73. | 51.59% | Perry, IN / 18,872 |
| 74. | 51.47% | Sullivan, IN / 21,316 |
| 75. | 51.45% | Jay, IN / 21,270 |
| 76. | 51.08% | Blackford, IN / 13,254 |
| 77. | 50.89% | Jefferson, IN / 32,628 |
| 78. | 50.72% | Knox, IN / 37,970 |
| 79. | 50.53% | La Porte, IN / 110,102 |
| 80. | 50.50% | Grant, IN / 69,203 |
| 81. | 49.26% | Allen, IN / 348,646 |
| 82. | 49.07% | Wayne, IN / 68,151 |
| 83. | 47.89% | Madison, IN / 131,015 |
| 84. | 47.27% | St Joseph, IN / 266,400 |
| 85. | 47.16% | Clark, IN / 105,280 |
| 86. | 46.20% | Lake, IN / 491,203 |
| 87. | 45.75% | Vigo, IN / 105,434 |
| 88. | 45.68% | Delaware, IN / 115,548 |
| 89. | 45.39% | Vanderburgh, IN / 174,544 |
| 90. | 43.72% | Tippecanoe, IN / 162,527 |
| 91. | 41.53% | Monroe, IN / 127,855 |
| 92. | 38.07% | Marion, IN / 878,881 |
Please note that we only rank locations with 'Married-Couple Family Household Percentage' data. The rank above might not be a complete list. Locations without 'Married-Couple Family Household 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.