https://www.southdakota-demographics.com/terms_and_conditionshttps://www.southdakota-demographics.com/terms_and_conditions
A dataset listing South Dakota cities by population for 2024.
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License information was derived automatically
Context
This list ranks the 354 cities in the North Dakota by Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Watford City population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Watford City across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Watford City was 6,020, a 2.36% increase year-by-year from 2022. Previously, in 2022, Watford City population was 5,881, an increase of 0.17% compared to a population of 5,871 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Watford City increased by 4,591. In this period, the peak population was 7,817 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Watford City Population by Year. You can refer the same here
https://www.northdakota-demographics.com/terms_and_conditionshttps://www.northdakota-demographics.com/terms_and_conditions
A dataset listing North Dakota zip codes by population for 2024.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the South Dakota population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of South Dakota across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2024, the population of South Dakota was 924,669, a 0.69% increase year-by-year from 2023. Previously, in 2023, South Dakota population was 918,305, an increase of 0.94% compared to a population of 909,723 in 2022. Over the last 20 plus years, between 2000 and 2024, population of South Dakota increased by 168,962. In this period, the peak population was 924,669 in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Dakota Population by Year. You can refer the same here
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Valley City city, North Dakota. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
https://www.northdakota-demographics.com/terms_and_conditionshttps://www.northdakota-demographics.com/terms_and_conditions
A dataset listing the 20 richest cities in North Dakota for 2024, including information on rank, city, county, population, average income, and median income.
This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Bismarck city, North Dakota. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de446306https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de446306
Abstract (en): Summary File 3 contains sample data, which is the information compiled from the questions asked of a sample of all people and housing units in the United States. Population items include basic population totals as well as counts for the following characteristics: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals and counts for urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, and monthly rent and shelter costs. The Summary File 3 population tables are identified with a "P" prefix and the housing tables are identified with an "H," followed by a sequential number. The "P" and "H" tables are shown for the block group and higher level geography, while the "PCT" and "HCT" tables are shown for the census tract and higher level geography. There are 16 "P" tables, 15 "PCT" tables, and 20 "HCT" tables that bear an alphabetic suffix on the table number, indicating that they are repeated for nine major race and Hispanic or Latino groups. There are 484 population tables and 329 housing tables for a total of 813 unique tables. All persons in housing units in North Dakota in 2000. 2006-01-12 All files were removed from dataset 82 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 81 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 80 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 79 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 78 and flagged as study-level files, so that they will accompany all downloads. (1) The data are provided in 77 segments [files] per state. The segments are the Geographic Header, Tables P1-P14, P15-P24, P25-P37, P38-P46, P47-P50, P51-P67, P68-P91, P92-P138, P139-P145C, P145D-P145H, P145I-P146F, P146G-P147I, P148A-P149D, P149E-P150I, P151A-P154D, P154E-P159G, P159H-P160E, P16OF-P160I, PCT1-PCT8, PCT9-PCT15, PCT16-PCT17, PCT18-PCT19, PCT20-PCT24, PCT25-PCT27, PCT28-PCT32, PCT33-PCT34, PCT35-PCT37, PCT38-PCT43, PCT44-PCT48, PCT49-PCT51, PCT52-PCT56, PCT57-PCT61, PCT62A-PCT63C, PCT63D-PCT64H, PCT64I-PCT66C, PCT66D-PCT67E, PCT67F-PCT68C, PCT68D-PCT68H, PCT68I-PCT69I, PCT70A-PCT70I, PCT71A-PCT71E, PCT71F-PCT71I, PCT72A-PCT72B, PCT72C-PCT72D, PCT72E-PCT72F, PCT72G-PCT72H, PCT72I-PCT73A, PCT73B-PCT73C, PCT73D-PCT73E, PCT73F-PCT73G, PCT73H-PCT73I, PCT74A-PCT75C, PCT75D-PCT75G, PCT75H-PCT76D, PCT76E-PCT76I, H1-H18, H19-H26, H27-H44, H45-H68, H69-H86, H87-H104, H105-H121, HCT1-HCT3, HCT4, HCT5, HCT6-HCT7, HCT8-HCT14, HCT15-HCT17, HCT18-HCT23, HCT24-HCT31C, HCT31D-HCT36D, HCT36E-HCT40I, HCT41A-HCT43I, HCT44A-HCT44G, HCT44H-HCT47F, and HCT47G-HCT48I. The Geographic Header is in fixed-format ASCII and the tables are in comma-delimited ASCII format. (2) The codebook is provided by the principal investigator as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.
This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.
The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Valley City population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Valley City across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Valley City was 6,551, a 0.18% decrease year-by-year from 2022. Previously, in 2022, Valley City population was 6,563, a decline of 0.06% compared to a population of 6,567 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Valley City decreased by 202. In this period, the peak population was 6,753 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Valley City Population by Year. You can refer the same here
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Grand Forks city, North Dakota. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Resident Population in Rapid City, SD (MSA) (RPCPOP) from 2000 to 2024 about Rapid City, SD, residents, population, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Table containing authoritative population values for Sioux Falls, South Dakota.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Resident Population in Sioux City, IA-NE-SD (MSA) (SICPOP) from 2000 to 2024 about Sioux City, SD, NE, IA, residents, population, and USA.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Minot city, North Dakota. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated or updated as part of the the 2023 BAS or the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
The 2015 TIGER Geodatabases are extracts of selected nation based and state based geographic and cartographic information from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. The geodatabases include feature class layers of information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The geodatabases do not contain any sensitive data. The 2015 TIGER Geodatabases are designed for use with Esriâ s ArcGIS.
The 2015 State Geodatabase for North Dakota contains multiple layers. These layers are the Block, Block Group, Census Designated Place, Census
Tract, County Subdivision and Incorporated Place layers.
Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered
within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same
decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that
census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and
Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses
county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban
areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas.
The BG boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the
2010 Census.
The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to
previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people.
When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living
conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by
highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to
population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable
features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to
allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and
county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may
consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities
that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that
include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American
Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little
or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial
park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD),
which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state,
but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have
other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated
to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state
in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide
with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial
census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily
have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population.
The boundaries of most incorporated places in this shapefile are as of January 1, 2013, as reported through the Census Bureau's Boundary and
Annexation Survey (BAS). Limited updates that occurred after January 1, 2013, such as newly incorporated places, are also included. The boundaries
of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.
The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no
counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The
latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri,
Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary
divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data
presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data
presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto
Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin
Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities.
The boundaries for counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and
Annexation Survey (BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included.
County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include
legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census,
the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs
for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical
unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county
subdivisions. The boundaries of most legal MCDs are as of January 1, 2013, as reported through the Census Bureau's Boundary and Annexation Survey
(BAS).
The boundaries of all CCDs, delineated in 21 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program
(PSAP) for the 2010 Census.
https://www.southdakota-demographics.com/terms_and_conditionshttps://www.southdakota-demographics.com/terms_and_conditions
A dataset listing South Dakota cities by population for 2024.