Local Data Search
A total of 92 results found. Show Results on Map.
| Rank | Percentage of Population Never Married Female Age 15 or Older ▼ | County / Population |
| 1. | 44.7% | Monroe, IN / 127,855 |
| 2. | 38.6% | Tippecanoe, IN / 162,527 |
| 3. | 33.4% | Delaware, IN / 115,548 |
| 4. | 33.3% | Marion, IN / 878,881 |
| 5. | 30.0% | St Joseph, IN / 266,400 |
| 6. | 29.7% | Lake, IN / 491,203 |
| 7. | 28.6% | Vigo, IN / 105,434 |
| 8. | 26.7% | Vanderburgh, IN / 174,544 |
| 9. | 26.6% | Allen, IN / 348,646 |
| 10. | 26.0% | Grant, IN / 69,203 |
| 11. | 24.3% | Elkhart, IN / 197,851 |
| 12. | 24.0% | Madison, IN / 131,015 |
| 13. | 24.0% | La Porte, IN / 110,102 |
| 14. | 23.6% | Putnam, IN / 36,993 |
| 15. | 23.6% | Jefferson, IN / 32,628 |
| 16. | 23.2% | Porter, IN / 160,073 |
| 17. | 23.1% | Floyd, IN / 73,031 |
| 18. | 22.8% | Wayne, IN / 68,151 |
| 19. | 22.2% | Franklin, IN / 23,074 |
| 19. | 22.2% | Clark, IN / 105,280 |
| 21. | 22.2% | Knox, IN / 37,970 |
| 22. | 21.9% | Parke, IN / 17,094 |
| 23. | 21.7% | Hamilton, IN / 261,328 |
| 24. | 21.6% | Jasper, IN / 32,197 |
| 25. | 21.6% | Johnson, IN / 136,081 |
| 26. | 21.3% | Howard, IN / 83,685 |
| 27. | 21.3% | Daviess, IN / 30,205 |
| 28. | 21.0% | Wabash, IN / 33,004 |
| 29. | 20.7% | Clinton, IN / 34,081 |
| 30. | 20.4% | Adams, IN / 33,955 |
| 31. | 20.3% | De Kalb, IN / 41,759 |
| 32. | 20.3% | Lagrange, IN / 36,857 |
| 33. | 20.2% | Dearborn, IN / 49,608 |
| 34. | 20.1% | Owen, IN / 22,371 |
| 34. | 20.1% | Huntington, IN / 37,890 |
| 36. | 20.1% | Benton, IN / 8,723 |
| 37. | 20.1% | Pulaski, IN / 13,739 |
| 38. | 20.0% | Ripley, IN / 27,378 |
| 38. | 20.0% | Bartholomew, IN / 74,681 |
| 40. | 19.9% | Hendricks, IN / 133,949 |
| 41. | 19.7% | Noble, IN / 47,729 |
| 42. | 19.7% | Marshall, IN / 46,605 |
| 43. | 19.5% | Dubois, IN / 41,207 |
| 44. | 19.4% | Jay, IN / 21,270 |
| 45. | 19.2% | Shelby, IN / 43,964 |
| 46. | 19.2% | Gibson, IN / 32,834 |
| 47. | 19.2% | Washington, IN / 27,780 |
| 48. | 19.1% | Posey, IN / 26,244 |
| 49. | 19.0% | Decatur, IN / 25,066 |
| 50. | 19.0% | Scott, IN / 23,646 |
| 51. | 18.9% | Montgomery, IN / 37,828 |
| 52. | 18.9% | Martin, IN / 10,067 |
| 53. | 18.8% | Miami, IN / 36,508 |
| 54. | 18.7% | Blackford, IN / 13,254 |
| 55. | 18.5% | Wells, IN / 27,720 |
| 55. | 18.5% | Perry, IN / 18,872 |
| 57. | 18.4% | Greene, IN / 32,715 |
| 58. | 18.3% | Steuben, IN / 33,544 |
| 59. | 18.3% | Morgan, IN / 70,179 |
| 60. | 18.2% | Starke, IN / 23,398 |
| 61. | 18.1% | Randolph, IN / 25,914 |
| 62. | 18.0% | Kosciusko, IN / 76,096 |
| 63. | 18.0% | Cass, IN / 39,263 |
| 64. | 17.9% | Boone, IN / 53,931 |
| 65. | 17.7% | Crawford, IN / 10,795 |
| 66. | 17.6% | Sullivan, IN / 21,316 |
| 67. | 17.5% | Hancock, IN / 65,777 |
| 68. | 17.4% | Clay, IN / 26,682 |
| 69. | 17.3% | Ohio, IN / 5,871 |
| 69. | 17.3% | Warrick, IN / 57,065 |
| 71. | 17.3% | Harrison, IN / 36,973 |
| 72. | 17.3% | Whitley, IN / 32,504 |
| 73. | 17.2% | Fayette, IN / 24,313 |
| 74. | 17.2% | Union, IN / 7,083 |
| 75. | 16.6% | Switzerland, IN / 9,627 |
| 76. | 16.6% | Rush, IN / 17,425 |
| 77. | 16.5% | Fulton, IN / 20,251 |
| 78. | 16.5% | Jennings, IN / 28,052 |
| 79. | 16.2% | Carroll, IN / 19,863 |
| 80. | 16.1% | Fountain, IN / 17,075 |
| 81. | 16.1% | Henry, IN / 47,481 |
| 82. | 16.0% | Lawrence, IN / 45,891 |
| 83. | 15.7% | Vermillion, IN / 16,301 |
| 84. | 15.7% | Orange, IN / 19,536 |
| 85. | 15.7% | Newton, IN / 13,974 |
| 86. | 15.5% | Warren, IN / 8,573 |
| 87. | 15.5% | Tipton, IN / 16,055 |
| 88. | 15.2% | Brown, IN / 14,724 |
| 89. | 14.8% | White, IN / 23,840 |
| 90. | 14.5% | Jackson, IN / 42,131 |
| 91. | 12.2% | Spencer, IN / 20,167 |
| 92. | 10.2% | Pike, IN / 12,496 |
Please note that we only rank locations with 'Percentage of Population Never Married Female Age 15 or Older' data. The rank above might not be a complete list. Locations without 'Percentage of Population Never Married Female Age 15 or Older' 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.