Local Data Search
A total of 92 results found. Show Results on Map.
| Rank | Married-Couple Family Household Percentage ▼ | County / Population |
| 1. | 67.09% | Lagrange, IN / 37,284 |
| 2. | 64.60% | Warrick, IN / 59,643 |
| 3. | 64.08% | Jasper, IN / 33,369 |
| 4. | 63.38% | Hamilton, IN / 276,098 |
| 5. | 62.81% | Hendricks, IN / 145,880 |
| 6. | 62.78% | Warren, IN / 8,490 |
| 7. | 62.69% | Spencer, IN / 20,948 |
| 8. | 62.46% | Franklin, IN / 23,108 |
| 9. | 62.32% | Boone, IN / 56,823 |
| 10. | 61.32% | White, IN / 24,612 |
| 11. | 60.63% | Hancock, IN / 69,778 |
| 12. | 60.61% | Clay, IN / 26,908 |
| 13. | 60.56% | Morgan, IN / 69,033 |
| 14. | 59.48% | Posey, IN / 25,840 |
| 15. | 59.44% | Tipton, IN / 15,917 |
| 16. | 59.30% | Dubois, IN / 41,995 |
| 17. | 59.26% | Harrison, IN / 39,102 |
| 18. | 58.73% | Ripley, IN / 28,702 |
| 19. | 58.61% | Putnam, IN / 37,995 |
| 20. | 58.49% | Wells, IN / 27,677 |
| 21. | 58.46% | Johnson, IN / 140,033 |
| 22. | 58.44% | Adams, IN / 34,343 |
| 23. | 58.41% | Kosciusko, IN / 77,328 |
| 24. | 58.38% | Ohio, IN / 6,093 |
| 25. | 58.30% | Union, IN / 7,449 |
| 26. | 58.25% | Parke, IN / 17,251 |
| 27. | 58.23% | Pulaski, IN / 13,395 |
| 28. | 57.66% | Daviess, IN / 31,604 |
| 29. | 57.56% | Brown, IN / 15,181 |
| 30. | 57.37% | Wabash, IN / 32,804 |
| 31. | 57.27% | Newton, IN / 14,199 |
| 32. | 57.03% | Fulton, IN / 20,762 |
| 33. | 56.99% | Steuben, IN / 34,116 |
| 34. | 56.97% | Rush, IN / 17,349 |
| 35. | 56.91% | Dearborn, IN / 49,904 |
| 36. | 56.81% | Marshall, IN / 47,045 |
| 37. | 56.45% | Whitley, IN / 33,234 |
| 38. | 56.44% | Carroll, IN / 20,105 |
| 39. | 56.32% | Noble, IN / 47,547 |
| 40. | 55.90% | Pike, IN / 12,849 |
| 41. | 55.80% | Greene, IN / 33,032 |
| 42. | 55.76% | Owen, IN / 21,583 |
| 43. | 55.69% | Gibson, IN / 33,437 |
| 44. | 55.61% | Orange, IN / 19,828 |
| 45. | 55.46% | Decatur, IN / 25,772 |
| 46. | 55.42% | Montgomery, IN / 38,207 |
| 47. | 55.26% | Porter, IN / 164,386 |
| 48. | 55.22% | Lawrence, IN / 46,131 |
| 49. | 55.13% | Perry, IN / 19,408 |
| 50. | 55.04% | Huntington, IN / 37,144 |
| 51. | 54.91% | Sullivan, IN / 21,379 |
| 52. | 54.56% | Miami, IN / 36,850 |
| 53. | 54.51% | Elkhart, IN / 198,214 |
| 54. | 54.47% | Bartholomew, IN / 77,297 |
| 55. | 54.29% | Crawford, IN / 10,702 |
| 56. | 54.23% | Randolph, IN / 26,101 |
| 57. | 54.05% | De Kalb, IN / 42,218 |
| 58. | 53.77% | Fountain, IN / 17,212 |
| 59. | 53.57% | Starke, IN / 23,310 |
| 60. | 53.36% | Washington, IN / 28,162 |
| 61. | 53.15% | Jennings, IN / 28,373 |
| 62. | 52.97% | Jackson, IN / 42,414 |
| 63. | 52.80% | Martin, IN / 10,300 |
| 64. | 52.73% | Henry, IN / 49,381 |
| 65. | 52.55% | Clinton, IN / 33,179 |
| 66. | 52.54% | Switzerland, IN / 10,509 |
| 67. | 52.13% | Shelby, IN / 44,435 |
| 68. | 51.99% | Scott, IN / 24,044 |
| 69. | 51.85% | Benton, IN / 8,816 |
| 70. | 51.84% | Vermillion, IN / 16,224 |
| 71. | 51.74% | Cass, IN / 38,875 |
| 72. | 51.72% | Jay, IN / 21,353 |
| 73. | 51.64% | Howard, IN / 82,914 |
| 74. | 51.24% | Blackford, IN / 12,742 |
| 75. | 50.81% | Jefferson, IN / 32,501 |
| 76. | 50.58% | Floyd, IN / 74,601 |
| 77. | 49.96% | Knox, IN / 38,392 |
| 78. | 49.79% | Fayette, IN / 24,220 |
| 79. | 48.97% | La Porte, IN / 111,335 |
| 80. | 48.88% | Grant, IN / 69,886 |
| 81. | 48.73% | Allen, IN / 355,940 |
| 82. | 48.40% | Clark, IN / 110,100 |
| 83. | 47.68% | Wayne, IN / 68,797 |
| 84. | 46.84% | Madison, IN / 131,244 |
| 84. | 46.84% | St Joseph, IN / 266,785 |
| 86. | 45.68% | Lake, IN / 495,230 |
| 87. | 45.42% | Vigo, IN / 107,805 |
| 88. | 44.38% | Delaware, IN / 117,459 |
| 89. | 43.75% | Tippecanoe, IN / 173,317 |
| 90. | 43.08% | Vanderburgh, IN / 179,610 |
| 91. | 38.71% | Monroe, IN / 138,048 |
| 92. | 37.76% | Marion, IN / 904,535 |
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.