Title
Census Dashboards
Media
county_ethnicity_age_dashboard
Title
Decennial Census 2020 Resident Population by County, Ethnicity, and Voting Age
Media
tableau_census_county_race
Title
Decennial Census 2020 Resident Population by County, Race, and Voting Age
Media
Census Bureau Dashboards
Title
Census Bureau South Carolina Dashboards
Title
Total Resident Population by County
Data Table
COUNTY CENSUS 2000 CENSUS 2010 PERCENT CHANGE 2000 TO 2010  CENSUS 2020  PERCENT CHANGE 2010 TO 2020
Abbeville         26,167         25,417 -2.87%         24,295 -4.41%
Aiken       142,552       160,099 12.31%       168,808 5.44%
Allendale         11,211         10,419 -7.06%           8,039 -22.84%
Anderson       165,740       187,126 12.90%       203,718 8.87%
Bamberg         16,658         15,987 -4.03%         13,311 -16.74%
Barnwell         23,478         22,621 -3.65%         20,589 -8.98%
Beaufort       120,937       162,233 34.15%       187,117 15.34%
Berkeley       142,651       177,843 24.67%       229,861 29.25%
Calhoun         15,185         15,175 -0.07%         14,119 -6.96%
Charleston       309,969       350,209 12.98%       408,235 16.57%
Cherokee         52,537         55,342 5.34%         56,216 1.58%
Chester         34,068         33,140 -2.72%         32,294 -2.55%
Chesterfield         42,768         46,734 9.27%         43,273 -7.41%
Clarendon         32,502         34,971 7.60%         31,144 -10.94%
Colleton         38,264         38,892 1.64%         38,604 -0.74%
Darlington         67,394         68,681 1.91%         62,905 -8.41%
Dillon         30,722         32,062 4.36%         28,292 -11.76%
Dorchester         96,413       136,555 41.64%       161,540 18.30%
Edgefield         24,595         26,985 9.72%         25,657 -4.92%
Fairfield         23,454         23,956 2.14%         20,948 -12.56%
Florence       125,761       136,885 8.85%       137,059 0.13%
Georgetown         55,797         60,158 7.82%         63,404 5.40%
Greenville       379,616       451,225 18.86%       525,534 16.47%
Greenwood         66,271         69,661 5.12%         69,351 -0.45%
Hampton         21,386         21,090 -1.38%         18,561 -11.99%
Horry       196,629       269,291 36.95%       351,029 30.35%
Jasper         20,678         24,777 19.82%         28,791 16.20%
Kershaw         52,647         61,697 17.19%         65,403 6.01%
Lancaster         61,351         76,652 24.94%         96,016 25.26%
Laurens         69,567         66,537 -4.36%         67,539 1.51%
Lee         20,119         19,220 -4.47%         16,531 -13.99%
Lexington       216,014       262,391 21.47%       293,991 12.04%
McCormick           9,958         10,233 2.76%           9,526 -6.91%
Marion         35,466         33,062 -6.78%         29,183 -11.73%
Marlboro         28,818         28,933 0.40%         26,667 -7.83%
Newberry         36,108         37,508 3.88%         37,719 0.56%
Oconee         66,215         74,273 12.17%         78,607 5.84%
Orangeburg         91,582         92,501 1.00%         84,223 -8.95%
Pickens       110,757       119,224 7.64%       131,404 10.22%
Richland       320,677       384,504 19.90%       416,147 8.23%
Saluda         19,181         19,875 3.62%         18,862 -5.10%
Spartanburg       253,791       284,307 12.02%       327,997 15.37%
Sumter       104,646       107,456 2.69%       105,556 -1.77%
Union         29,881         28,961 -3.08%         27,244 -5.93%
Williamsburg         37,217         34,423 -7.51%         31,026 -9.87%
York       164,614       226,073 37.34%       282,090 24.78%
Total    4,012,012     4,625,364   15.29%   5,118,425   10.66%
Body

Source:  US Census Bureau P.L. 94-171 Redistricting Data

Disclaimer:  The 2020 Census data below the state level will be affected by the Census’s efforts regarding differential privacy.  The bureau has stated that the total population in each state will be “as enumerated,” but that all other levels of geography—including congressional districts down to townships and census blocks—could have some variance from the raw data. This is referred to by the Census Bureau as “injecting noise” into the data. The bureau has indicated that no “noise” will be injected into the state total population, but it is likely that noise will be injected for every other level of geography.  More noise is injected as the geography levels get smaller.