A total of 40 results found. Show Results on Map.
Rank | Median Other One Race Household Income ▼ | County / Population |
1. | $180,606 | Fairfield, SC / 23,804 |
2. | $60,804 | York, SC / 226,576 |
3. | $60,662 | Marion, SC / 33,038 |
4. | $53,090 | Lee, SC / 19,160 |
5. | $51,250 | Clarendon, SC / 34,746 |
6. | $50,000 | Kershaw, SC / 61,583 |
7. | $49,000 | Berkeley, SC / 179,773 |
8. | $46,049 | Jasper, SC / 24,792 |
9. | $46,042 | Florence, SC / 136,714 |
10. | $45,697 | Sumter, SC / 107,279 |
11. | $45,637 | Lexington, SC / 262,424 |
12. | $44,137 | Beaufort, SC / 162,316 |
13. | $43,750 | Spartanburg, SC / 284,540 |
14. | $39,533 | Richland, SC / 384,596 |
15. | $39,464 | Colleton, SC / 38,665 |
16. | $38,839 | Pickens, SC / 119,167 |
17. | $37,386 | Allendale, SC / 10,399 |
18. | $37,262 | Oconee, SC / 74,038 |
19. | $35,313 | Dorchester, SC / 136,836 |
20. | $35,270 | Horry, SC / 270,943 |
21. | $35,208 | Union, SC / 28,804 |
22. | $33,942 | Greenwood, SC / 69,531 |
23. | $32,761 | Greenville, SC / 452,931 |
24. | $30,947 | Dillon, SC / 31,733 |
25. | $28,338 | Newberry, SC / 37,432 |
26. | $27,765 | Lancaster, SC / 76,364 |
27. | $26,919 | Charleston, SC / 352,548 |
28. | $26,403 | Saluda, SC / 19,758 |
29. | $25,446 | Cherokee, SC / 55,351 |
30. | $25,141 | Anderson, SC / 187,228 |
31. | $23,565 | Georgetown, SC / 60,285 |
32. | $23,435 | Orangeburg, SC / 92,229 |
33. | $20,625 | Barnwell, SC / 22,523 |
34. | $20,000 | Marlboro, SC / 28,750 |
35. | $19,292 | Hampton, SC / 20,987 |
36. | $17,500 | Aiken, SC / 160,169 |
37. | $16,879 | Laurens, SC / 66,623 |
38. | $13,304 | Darlington, SC / 68,500 |
39. | $2,499 | Chester, SC / 33,028 |
39. | $2,499 | Edgefield, SC / 26,763 |
Please note that we only rank locations with 'Median Other One Race Household Income' data. The rank above might not be a complete list. Locations without 'Median Other One Race Household Income' 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.