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A dataset listing Indiana counties by population for 2024.
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Context
The dataset tabulates the data for the Indiana, PA population pyramid, which represents the Indiana population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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 Indiana Population by Age. You can refer the same here
The 2020 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, 2020, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.
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Estimate, Median Age by Sex, Total Population (5-year estimate) in Indiana County, PA was 39.50000 Years of Age in January of 2023, according to the United States Federal Reserve. Historically, Estimate, Median Age by Sex, Total Population (5-year estimate) in Indiana County, PA reached a record high of 40.20000 in January of 2019 and a record low of 38.10000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate, Median Age by Sex, Total Population (5-year estimate) in Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
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U.S. Census Bureau QuickFacts statistics for Floyd County, Indiana. 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.
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License information was derived automatically
Context
The dataset tabulates the data for the Young township, Indiana County, Pennsylvania population pyramid, which represents the Young township population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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 Young township Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population Estimate, Total, Not Hispanic or Latino, American Indian and Alaska Native Alone (5-year estimate) in Indiana County, PA was 14.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Population Estimate, Total, Not Hispanic or Latino, American Indian and Alaska Native Alone (5-year estimate) in Indiana County, PA reached a record high of 196.00000 in January of 2018 and a record low of 14.00000 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Estimate, Total, Not Hispanic or Latino, American Indian and Alaska Native Alone (5-year estimate) in Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
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. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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 and beyond, 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.
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U.S. Census Bureau QuickFacts statistics for Hancock County, Indiana. 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.
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License information was derived automatically
Context
The dataset tabulates the data for the Center township, Indiana County, Pennsylvania population pyramid, which represents the Center township population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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 Center township Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Percent of Population Below the Poverty Level (5-year estimate) in Indiana County, PA was 12.80% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Indiana County, PA reached a record high of 18.20 in January of 2012 and a record low of 12.80 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
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U.S. Census Bureau QuickFacts statistics for Gibson County, Indiana. 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.
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A dataset listing Indiana cities 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 data for the Banks township, Indiana County, Pennsylvania population pyramid, which represents the Banks township population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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 Banks township Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population Estimate, Total, Not Hispanic or Latino, Black or African American Alone (5-year estimate) in Indiana County, PA was 1941.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Population Estimate, Total, Not Hispanic or Latino, Black or African American Alone (5-year estimate) in Indiana County, PA reached a record high of 2210.00000 in January of 2011 and a record low of 1744.00000 in January of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Estimate, Total, Not Hispanic or Latino, Black or African American Alone (5-year estimate) in Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Indiana County, PA was 661.00000 Persons in January of 2023, according to the United States Federal Reserve. Historically, Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Indiana County, PA reached a record high of 999.00000 in January of 2016 and a record low of 661.00000 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Population Estimate, Total, Not Hispanic or Latino, Asian Alone (5-year estimate) in Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
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Equifax Subprime Credit Population for Indiana County, PA was 18.61% in January of 2025, according to the United States Federal Reserve. Historically, Equifax Subprime Credit Population for Indiana County, PA reached a record high of 29.62 in October of 1999 and a record low of 18.26 in July of 2024. Trading Economics provides the current actual value, an historical data chart and related indicators for Equifax Subprime Credit Population for Indiana County, PA - last updated from the United States Federal Reserve on June of 2025.
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From the 2022 TIGER/Line Technical Documentation:Census blocks are statistical areas bounded on all sides by visible features (e.g., streets, roads, streams, and railroad tracks), and by non-visible boundaries (e.g., city, town, township, county limits, and short line-of-sight extensions of streets and roads). Generally, census blocks are small in area (e.g., a block in a city). Census blocks in suburban and rural areas may be large, irregular, and bounded by a variety of features (e.g., roads, streams, and/or transmission line rights-of-way). In remote areas, census blocks may encompass hundreds of square miles. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas. Blocks do not cross the boundaries of any entity for which the Census Bureau tabulates data. (See Figures 12 and 13). Census Block Numbers—Census blocks are numbered uniquely within the boundaries of each state, county, census tract with a 4-character census block number. The first character of the tabulation block number identifies the block group. A block number can only be unique by using the decennial census state (STATEFP
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U.S. Census Bureau QuickFacts statistics for Cass County, Indiana. 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.
This is a comment on the preliminary Congressional Commission redistricting map. Along with providing feedback on that map, it offers a draft alternative that better meets the criteria of the Colorado Constitution. As background, I participated in redistricting initiatives in South Bend, Indiana, in the mid-1980s and for Indiana legislative seats after the 1990 census. I didn’t engage with redistricting during the rest of my 20-year military career. After retiring, and while serving as Public Trustee for El Paso County, I participated in redistricting efforts at the county and city level. I also stood for El Paso County Clerk in 2010. I have lived in Colorado since 2000. The draft alternative map is created using Dave’s Redistricting App (DRA) and can be found at https://davesredistricting.org/join/346f297c-71d1-4443-9110-b92e3362b105. I used DRA because it was more user-friendly in that it allows selection by precinct and by city or town, while the tool provided by the commission seems to allow only selection by census block (or larger clusters). The two tools also use slightly different population estimates, but this will be resolved when the 2020 data are released in August. These comments acknowledge that any map created using estimated populations will need to change to account for the actual census data.
Description of Draft Alternative
My process started by
identifying large-scale geographic communities of interest within Colorado: the Western Slope/mountain areas, the Eastern Plains, Colorado Springs/El Paso County, the North Front Range, and Denver Metro. Two smaller geographic communities of interest are Pueblo and the San Luis Valley—neither is nearly large enough to sustain a district and both are somewhat distinct from their neighboring communities of interest. A choice thus must be made about which other communities of interest to group them with. El Paso County is within 0.3% of the optimal population, so it is set as District 5. The true Western Slope is not large enough to sustain a district, even with the obvious addition of Jackson County. Rather than including the San Luis Valley with the Western Slope, the preliminary commission map extends the Western Slope district to include all of Fremont County (even Canon City, Florence, and Penrose), Clear Creek County, and some of northern Boulder County. The draft alternative District 3 instead adds the San Luis Valley, the Upper Arkansas Valley (Lake and Chaffee Counties, and the western part of Fremont County), Park and Teller Counties, and Custer County. The draft alternative District 4 is based on the Eastern Plains. In the south, this includes the rest of Fremont County (including Canon City), Pueblo, and the Lower Arkansas Valley. In the north, this includes all of Weld County, retaining it as an intact political subdivision. This is nearly enough population to form a complete district; it is rounded out by including the easternmost portions of Adams and Arapahoe Counties. All of Elbert County is in this district; none of Douglas County is. The draft alternative District 2 is placed in the North Front Range and includes Larimer, Boulder, Gilpin, and Clear Creek Counties. This is nearly enough population to form a complete district, so it is rounded out by adding Evergreen and the rest of Coal Creek in Jefferson County. The City and County of Denver (and the Arapahoe County enclave municipalities of Glendale and Holly Hills) forms the basis of draft alternative District 1. This is a bit too large to form a district, so small areas are shaved off into neighboring districts: DIA (mostly for compactness), Indian Creek, and part of Marston. This leaves three districts to place in suburban Denver. The draft alternative keeps Douglas County intact, as well as the city of Aurora, except for the part that extends into Douglas County. The map prioritizes the county over the city as a political subdivision. Draft alternative District 6, anchored in Douglas County, extends north into Arapahoe County to include suburbs like Centennial, Littleton, Englewood, Greenwood Village, and Cherry Hills Village. This is not enough population, so the district extends west into southern Jefferson County to include Columbine, Ken Caryl, and Dakota Ridge. The northwestern edge of this district would run along Deer Creek Road, Pleasant Park Road, and Kennedy Gulch Road. Draft alternative District 8, anchored in Aurora, includes the rest of western Arapahoe County and extends north into Adams County to include Commerce City, Brighton (except the part in Weld County), Thornton, and North Washington. In the draft alternative, this district includes a sliver of Northglenn east of Stonehocker Park. While this likely would be resolved when final population totals are released, this division of Northglenn is the most notable division of a city within a single county other than the required division of Denver. Draft alternative District 7 encompasses what is left: The City and County of Broomfield; Westminster, in both Jefferson and Adams Counties; Federal Heights, Sherrelwood, Welby, Twin Lakes, Berkley, and almost all of Northglenn in western Adams County; and Lakewood, Arvada, Golden, Wheat Ridge, Morrison, Indian Hills, Aspen Park, Genesee, and Kittredge in northern Jefferson County. The border with District 2 through the communities in the western portion of Jefferson County would likely be adjusted after final population totals are released.
Comparison of Maps
Precise Population Equality
The preliminary commission
map has exact population equality. The draft alternative map has a variation of 0.6% (4,239 persons). Given that the maps are based on population estimates, and that I left it at the precinct and municipality level, this aspect of the preliminary map is premature to pinpoint. Once final population data are released, either map would need to be adjusted. It would be simple to tweak district boundaries to achieve any desired level of equality. That said, such precision is a bit of a fallacy: errors in the census data likely exceed the 0.6% in the draft map, the census data will be a year out of date when received, and relative district populations will fluctuate over the next 10 years. Both the “good-faith effort†and “as practicable†language leave room for a bit of variance in service of other goals. The need to “justify any variance†does not mean “no variance will be allowed.†For example, it may be better to maintain unity in a community of interest or political subdivision rather than separate part of it for additional precision. The major sticking point here is likely to be El Paso County: given how close it seems to be to the optimal district size, will it be worth it to divide the county or one of its neighbors to achieve precision? The same question would be likely to apply among the municipalities in Metro Denver.
Contiguity
The draft alternative map
meets this requirement. The preliminary commission map violates the spirit if not the actual language of this requirement. While its districts are connected by land, the only way to travel to all parts of preliminary Districts 3 and 4 without leaving the districts would be on foot. There is no road connection between the parts of Boulder County that are in District 3 and the rest of that district in Grand County without leaving the district and passing through District 2 in either Gilpin or Larimer Counties. There also is no road connection between some of the southwestern portions of Mineral County and the rest of District 4 without passing through Archuleta or Hinsdale Counties in District 3.
Voting Rights Act
The preliminary staff
analysis assumes it would be possible to create a majority-minority district; they are correct, it can be done via a noncompact district running from the west side of Denver up to Commerce City and Brighton and down to parts of northeastern Denver and northern Aurora. Such a district would go against criteria for compactness, political subdivisions, and even other definitions of communities of interest. Staff asserts that the election of Democratic candidates in this area suffices for VRA. Appendix B is opaque regarding the actual non-White or Hispanic population in each district, but I presume that if they had created a majority-minority district they would have said so. In the draft alternative map, District 8 (Aurora, Commerce City, Brighton, and Thornton) has a 39.6% minority population and District 1 (Denver) has a 34.9% minority population. The proposals are similar in meeting this criterion.
Communities of Interest
Staff presented a long list
of communities of interest. While keeping all of these intact would be ideal, drawing a map requires compromises based on geography and population. Many communities of interest overlap with each other, especially at their edges. This difficulty points to a reason to focus on existing subdivisions (county, city, and town boundaries): those boundaries are stable and overlap with shared public policy concerns. The preliminary commission map chooses to group the San Luis Valley, as far upstream as Del Norte and Creede, with Pueblo and the Eastern Plains rather than with the Western Slope/Mountains. To balance the population numbers, the preliminary commission map thus had to reach east in northern and central Colorado. The commission includes Canon City and Florence
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A dataset listing Indiana counties by population for 2024.