Enemy Swim, SD

Data Snapshot: Enemy Swim, SD

Enemy Swim is a city in South Dakota with a population of 291 residents based on U.S. Census Bureau ACS 2023 estimates. Median household income here reaches $29,125 per year, while the poverty rate sits at 50.0%. The median resident age is 20.2 years. About 26.7% of adults hold a bachelor's degree or higher, while 21.1% of working-age residents are in the labor force.

On a cost-of-living index where 100 equals the national average, South Dakota registers 88.6 (Below Average) per BEA Regional Price Parities 2024. HUD Fair Market Rent for a typical two-bedroom in this state is $990 per month. Average monthly utility bills run around $200 based on EIA 2023 residential energy data. FEMA's National Risk Index rates natural-hazard exposure at 26.8 out of 100 (Very Low).

According to the U.S. Census Bureau's 2023 American Community Survey (ACS) 5-year estimates, PlainCities renders standardized city-level demographic, income, education, employment, and housing indicators across more than 19,000 incorporated places nationwide. Population counts and median household income figures are sourced directly from Census Table B01003 and B19013 respectively, with poverty rates from B17001 and cost-of-living adjustments from the Bureau of Economic Analysis (BEA) Regional Price Parities (RPP) 2024 release. Every value displayed in this snapshot links back to the official upstream tables and is refreshed on the ACS annual release cadence (typically December of the survey year + 1).

Methodology: city boundaries follow the Census Bureau's place-level geography (incorporated places, census-designated places, and consolidated city-county governments), with FIPS codes ensuring consistent identifiers across decennial and annual surveys. Cost-of-living comparisons use BEA's Regional Price Parities (RPP) indexed to the national average (100), enabling cross-city purchasing-power comparisons. See our methodology page for full source attribution, refresh cadence, and known data quality limitations including margin-of-error disclosure and sample-size thresholds.