South Carolina by county: Census 2020–2024
Every adult in South Carolina, as the Census counts them, county by county and grouped by metro area. Each person is a real combination of traits from the Census's anonymised person records, weighted so every county matches its published tables, with party lean and 2024 turnout modelled and labelled so.
46 places, by metro area / county · Team plan
Every plan can look; creating a population from a state by county or by município needs Team.
What each person has
- Age
- 18-2412%
- 25-3416%
- 35-4416%
- 45-5415%
- 55-6417%
- 65-7415%
- and 1 more
- Sex
- Man48%
- Woman52%
- Race and ethnicity
- White65%
- Black24%
- Hispanic6%
- Asian2%
- Other or more than one race3%
- Education
- No high school diploma10%
- High school diploma or GED29%
- Some college or associate's degree31%
- Bachelor's degree19%
- Graduate degree11%
- Household income
- Under $25,00012%
- $25,000–49,99916%
- $50,000–74,99916%
- $75,000–99,99914%
- $100,000–149,99919%
- $150,000 or more20%
- and 1 more
- Work
- Working58%
- Unemployed, looking for work3%
- Not in the labor force39%
- Home
- Lives in an owned home71%
- Lives in a rented home25%
- Lives in group quarters3%
- Marital status
- Married51%
- Widowed7%
- Divorced11%
- Separated2%
- Never married29%
- Children at home
- No children at home70%
- Children at home30%
- Veteran
- Not a veteran92%
- Veteran8%
- Born
- Born in the US93%
- Born abroad7%
- Health coverage
- Has health coverage89%
- No health coverage11%
- Disability
- No disability82%
- Has a disability18%
- Citizenship
- US citizen96%
- Not a US citizen4%
- Party lean (modelled)
- Democratic-leaning37%
- Republican-leaning46%
- Independent or no lean17%
- Voted in 2024 (modelled)
- Voted61%
- Did not vote35%
- Not eligible (not a citizen)4%
County by county
Adults in each county: darker has more. Point at a county for its numbers.
Error report
How close these people come to the published figures, and where they fall short.
4,160,804 adults · 209,837 Census records · 46 counties in 11 areas (metro areas and the rest of the state)
Built 2026-10-10 · records south-carolina-2024-v1
How close the people land on the Census
Each county's records are weighted until they match its American Community Survey tables. The figure is the worst county's largest gap on each table, in percentage points.
| Table | Worst county |
|---|---|
| Sex by age | 0.4 |
| Race and ethnicity | 0.4 |
| Education | 0.4 |
| Household income | 0.5 |
| Work | 0.3 |
| Owned or rented home | 0.1 |
| Citizenship | 0.0 |
A check left out of the fit: veterans
Veteran status was not used in weighting, so it shows how well the weighted people carry traits nobody fitted. Per county, the share of veterans among civilian adults lands a median 0.5 points from the Census's own figure; 95% of counties within 3.2, the worst 5.1.
What drawing a population adds
A population is a sample of these weighted people, so small counties vary from draw to draw. Largest gap per county between the people drawn and the county's records, counties with at least 30 people.
| Trait | 10,000 people | 100,000 people | ||
|---|---|---|---|---|
| Median | 95% of counties within | Median | 95% of counties within | |
| Race and ethnicity | 0.6 | 1.8 | 0.1 | 0.3 |
| Education | 3.1 | 7.8 | 0.4 | 1.0 |
| Household income | 1.2 | 5.2 | 0.1 | 0.7 |
Party lean and 2024 turnout (modelled)
No Census record says how anyone votes, so these two traits are modelled. Each person starts from what Cooperative Election Study 2024 respondents like them (race, age, education and sex, in the Census South) said and did, with turnout checked against the voter file. Each county is then calibrated so its people's turnout and Democratic-minus-Republican margin match its 2024 presidential result (MIT Election Lab). Those results count votes for president, so turnout runs a point or so under ballots cast.
| Check | Margin | Turnout |
|---|---|---|
| Each county against its 2024 result (calibrated) | median 0.0, worst 0.0 | median 0.0, worst 0.0 |
| Demographics alone, given only the statewide result | median 7.5, worst 29.4 | median 2.5, worst 13.5 |
| The same, with priors that never saw anyone from South Carolina | median 7.5, worst 29.3 | median 2.4, worst 13.6 |
Leans against South Carolina's own survey respondents
Nothing was fitted to these: the share of each lean among South Carolina's adults, as modelled and as the CES's South Carolina respondents gave it.
| Democratic | Republican | Neither | Turnout | |
|---|---|---|---|---|
| Model | 37% | 46% | 17% | |
| CES South Carolina (n=988) | 39% | 45% | 16% | |
| Priors that never saw anyone from South Carolina, applied to its 983 citizen respondents | 38% | 45% | 17% | 56% |
| CES South Carolina, citizens (n=983) | 37% | 46% | 17% | 52% |
The county totals are right by construction: that is what calibration does. The honest test is the people alone, in the table above: given only the statewide result, how far each county's people land from its margin. Counties that vote very differently from people like them elsewhere in the region land furthest; the map shows where.
Within a county, calibration moves everyone's lean by the same factor, so lean by race inside one county is the weakest part. In the smallest counties the Census's five-year estimates carry wide margins, and where more presidential votes were cast than the estimate of citizens, turnout is held at 98%.
Use these traits to include or compare groups. They are not anyone's stated party, and results are never polls of real people.
Every county (46)
| County | Area | Adults | Census gap | Veterans (Census / people) | Turnout 2024 | Margin: result / demographics alone |
|---|---|---|---|---|---|---|
| Abbeville | Small towns and rural South Carolina | 19,623 | 0.4 | 7% / 8% | 62% | −42 / −21 |
| Aiken | Augusta-Richmond County | 136,781 | 0.3 | 10% / 10% | 64% | −26 / −20 |
| Allendale | Small towns and rural South Carolina | 6,265 | 0.4 | 5% / 10% | 49% | +45 / +22 |
| Anderson | Greenville-Anderson-Greer | 162,924 | 0.4 | 8% / 8% | 62% | −47 / −27 |
| Bamberg | Small towns and rural South Carolina | 10,660 | 0.3 | 6% / 10% | 54% | +15 / +13 |
| Barnwell | Small towns and rural South Carolina | 15,651 | 0.2 | 7% / 7% | 64% | −16 / −9 |
| Beaufort | Hilton Head Island-Bluffton-Port Royal | 161,218 | 0.3 | 11% / 10% | 68% | −14 / −26 |
| Berkeley | Charleston-North Charleston | 188,513 | 0.1 | 12% / 12% | 62% | −16 / −16 |
| Calhoun | Columbia | 11,543 | 0.3 | 10% / 8% | 69% | −14 / −10 |
| Charleston | Charleston-North Charleston | 338,379 | 0.3 | 8% / 8% | 66% | +6 / −14 |
| Cherokee | Small towns and rural South Carolina | 43,773 | 0.2 | 7% / 7% | 58% | −51 / −25 |
| Chester | Charlotte-Concord-Gastonia | 24,999 | 0.4 | 8% / 7% | 63% | −17 / −16 |
| Chesterfield | Small towns and rural South Carolina | 34,075 | 0.3 | 7% / 7% | 56% | −28 / −18 |
| Clarendon | Small towns and rural South Carolina | 25,344 | 0.1 | 7% / 8% | 65% | −12 / −8 |
| Colleton | Small towns and rural South Carolina | 29,991 | 0.3 | 9% / 10% | 63% | −18 / −14 |
| Darlington | Florence | 48,664 | 0.4 | 5% / 7% | 63% | −13 / −9 |
| Dillon | Small towns and rural South Carolina | 20,814 | 0.1 | 5% / 7% | 58% | −11 / −7 |
| Dorchester | Charleston-North Charleston | 126,948 | 0.3 | 12% / 12% | 63% | −15 / −17 |
| Edgefield | Augusta-Richmond County | 22,919 | 0.2 | 8% / 7% | 63% | −32 / −16 |
| Fairfield | Columbia | 16,859 | 0.3 | 7% / 8% | 67% | +13 / +2 |
| Florence | Florence | 104,829 | 0.2 | 7% / 7% | 59% | −8 / −6 |
| Georgetown | Small towns and rural South Carolina | 53,817 | 0.4 | 9% / 9% | 71% | −20 / −21 |
| Greenville | Greenville-Anderson-Greer | 422,724 | 0.2 | 7% / 7% | 66% | −22 / −21 |
| Greenwood | Small towns and rural South Carolina | 53,936 | 0.4 | 6% / 7% | 59% | −29 / −17 |
| Hampton | Small towns and rural South Carolina | 14,343 | 0.1 | 7% / 9% | 58% | +6 / +2 |
| Horry | Myrtle Beach-Conway-North Myrtle Beach | 318,052 | 0.3 | 9% / 9% | 67% | −39 / −32 |
| Jasper | Hilton Head Island-Bluffton-Port Royal | 26,283 | 0.3 | 7% / 8% | 76% | −10 / −17 |
| Kershaw | Columbia | 52,454 | 0.3 | 10% / 12% | 65% | −28 / −21 |
| Lancaster | Charlotte-Concord-Gastonia | 81,952 | 0.3 | 8% / 7% | 69% | −25 / −23 |
| Laurens | Greenville-Anderson-Greer | 53,686 | 0.3 | 6% / 7% | 58% | −41 / −23 |
| Lee | Small towns and rural South Carolina | 13,144 | 0.2 | 6% / 10% | 63% | +18 / +11 |
| Lexington | Columbia | 234,854 | 0.5 | 9% / 9% | 65% | −33 / −25 |
| McCormick | Small towns and rural South Carolina | 8,768 | 0.4 | 9% / 10% | 70% | −17 / −15 |
| Marion | Small towns and rural South Carolina | 22,331 | 0.3 | 7% / 7% | 61% | +11 / −1 |
| Marlboro | Small towns and rural South Carolina | 20,804 | 0.2 | 6% / 7% | 50% | +2 / −4 |
| Newberry | Small towns and rural South Carolina | 30,204 | 0.3 | 7% / 7% | 62% | −34 / −18 |
| Oconee | Small towns and rural South Carolina | 65,095 | 0.3 | 8% / 8% | 67% | −52 / −35 |
| Orangeburg | Small towns and rural South Carolina | 65,403 | 0.3 | 6% / 7% | 57% | +25 / +10 |
| Pickens | Greenville-Anderson-Greer | 109,608 | 0.2 | 6% / 6% | 57% | −53 / −29 |
| Richland | Columbia | 331,148 | 0.3 | 10% / 9% | 57% | +35 / +5 |
| Saluda | Columbia | 14,935 | 0.3 | 7% / 7% | 65% | −44 / −23 |
| Spartanburg | Spartanburg | 266,567 | 0.3 | 7% / 7% | 62% | −34 / −21 |
| Sumter | Sumter | 79,902 | 0.2 | 14% / 12% | 57% | +5 / +0 |
| Union | Spartanburg | 21,295 | 0.2 | 8% / 7% | 58% | −33 / −21 |
| Williamsburg | Small towns and rural South Carolina | 24,400 | 0.2 | 5% / 7% | 60% | +22 / +11 |
| York | Charlotte-Concord-Gastonia | 224,327 | 0.3 | 7% / 7% | 70% | −19 / −21 |
Sources
- Records
- ACS PUMS 2020–2024 5-year, South Carolina, adults 18+
- Tables
- ACS 2020–2024 5-year tables B01001, B01001B/D/H/I, B15001, B19001, B23025, B25008, B26001; out of sample: B21001
- Geography
- 2020 Census tract to 2020 PUMA relationship file; tract population B01003; metro areas, OMB delineation of July 2023
- Citizenship
- ACS 2020–2024 5-year table B05003 (raked)
- Party lean
- Modelled. Priors: Cooperative Election Study 2024 common content (Harvard Dataverse doi:10.7910/DVN/X11EP6, CC0), citizen respondents in the Census South, validated 2024 vote and 7-point party ID with leaners as partisans. Calibration: 2024 county presidential returns, MIT Election Data and Science Lab (Harvard Dataverse doi:10.7910/DVN/VOQCHQ, CC0), presidential votes standing in for ballots cast.