6 datasets found
  1. i

    Indiana Cities by Population

    • indiana-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Indiana Cities by Population [Dataset]. https://www.indiana-demographics.com/cities_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.indiana-demographics.com/terms_and_conditionshttps://www.indiana-demographics.com/terms_and_conditions

    Area covered
    Indiana
    Description

    A dataset listing Indiana cities by population for 2024.

  2. N

    cities in Indiana Ranked by White Population // 2025 Edition

    • neilsberg.com
    csv, json
    Updated Feb 10, 2025
    + more versions
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    Neilsberg Research (2025). cities in Indiana Ranked by White Population // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/lists/cities-in-indiana-by-white-population/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 10, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Indiana
    Variables measured
    White Population, White Population as Percent of Total White Population of Indiana, White Population as Percent of Total Population of cities in Indiana
    Measurement technique
    To measure the rank and respective trends, we initially gathered data from the five most recent American Community Survey (ACS) 5-Year Estimates. We then analyzed and categorized the data for each of the racial categories identified by the U.S. Census Bureau. Based on the required racial category classification, we calculated the rank. For geographies with no population reported for the chosen race, we did not assign a rank and excluded them from the list. It is possible that a small population exists but was not reported or captured due to limitations or variations in Census data collection and reporting. We ensured that the population estimates used in this dataset pertain exclusively to the identified racial categories and do not rely on any ethnicity classification, unless explicitly required.For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    This list ranks the 567 cities in the Indiana by White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

    • 2019-2023 American Community Survey 5-Year Estimates
    • 2018-2022 American Community Survey 5-Year Estimates
    • 2017-2021 American Community Survey 5-Year Estimates
    • 2016-2020 American Community Survey 5-Year Estimates
    • 2015-2019 American Community Survey 5-Year Estimates

    Variables / Data Columns

    • Rank by White Population: This column displays the rank of cities in the Indiana by their White population, using the most recent ACS data available.
    • cities: The cities for which the rank is shown in the previous column.
    • White Population: The White population of the cities is shown in this column.
    • % of Total cities Population: This shows what percentage of the total cities population identifies as White. Please note that the sum of all percentages may not equal one due to rounding of values.
    • % of Total Indiana White Population: This tells us how much of the entire Indiana White population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
    • 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

    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.

    Inspiration

    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/.

  3. i

    20 Richest Counties in Indiana

    • indiana-demographics.com
    Updated Jun 20, 2024
    + more versions
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    Kristen Carney (2024). 20 Richest Counties in Indiana [Dataset]. https://www.indiana-demographics.com/counties_by_population
    Explore at:
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.indiana-demographics.com/terms_and_conditionshttps://www.indiana-demographics.com/terms_and_conditions

    Area covered
    Indiana
    Description

    A dataset listing Indiana counties by population for 2024.

  4. N

    Oakland City, IN Annual Population and Growth Analysis Dataset: A...

    • neilsberg.com
    csv, json
    Updated Jul 30, 2024
    + more versions
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    Neilsberg Research (2024). Oakland City, IN Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Oakland City from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/oakland-city-in-population-by-year/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jul 30, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Oakland City
    Variables measured
    Annual Population Growth Rate, Population Between 2000 and 2023, Annual Population Growth Rate Percent
    Measurement technique
    The data presented in this dataset is derived from the 20 years data of U.S. Census Bureau Population Estimates Program (PEP) 2000 - 2023. To measure the variables, namely (a) population and (b) population change in ( absolute and as a percentage ), we initially analyzed and tabulated the data for each of the years between 2000 and 2023. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Oakland 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 Oakland 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 Oakland City was 2,260, a 0.53% decrease year-by-year from 2022. Previously, in 2022, Oakland City population was 2,272, a decline of 0.13% compared to a population of 2,275 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Oakland City decreased by 394. In this period, the peak population was 2,666 in the year 2004. 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).

    Content

    When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

    Data Coverage:

    • From 2000 to 2023

    Variables / Data Columns

    • Year: This column displays the data year (Measured annually and for years 2000 to 2023)
    • Population: The population for the specific year for the Oakland City is shown in this column.
    • Year on Year Change: This column displays the change in Oakland City population for each year compared to the previous year.
    • Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

    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.

    Inspiration

    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/.

    Recommended for further research

    This dataset is a part of the main dataset for Oakland City Population by Year. You can refer the same here

  5. State Geodatabase for Indiana

    • data.wu.ac.at
    • data.amerigeoss.org
    html, pdf, zip
    Updated Dec 7, 2015
    + more versions
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    US Census Bureau, Department of Commerce (2015). State Geodatabase for Indiana [Dataset]. https://data.wu.ac.at/schema/data_gov/MDBjYmJiMDQtMTQzMC00MWNiLWExYjYtODcwMGI2MTcxNDUy
    Explore at:
    pdf, html, zipAvailable download formats
    Dataset updated
    Dec 7, 2015
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    United States Census Bureauhttp://census.gov/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    33f5f0c63635ccde5c6eab47b1a405b18dd167d2
    Description

    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 State Geodatabase for Indiana geodatabase contains multiple layers. These layers are the Block, Block Group, Census Designated Place, Census
            Tract, Consolidated City, County, 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. 
    
            An incorporated place, or census designated 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 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. 
    
             A consolidated city is a unit of local government for which the functions of an incorporated place and its county or minor civil division (MCD) have
            merged. This action results in both the primary incorporated place and the county or MCD continuing to exist as legal entities, even though the
            county or MCD performs few or no governmental functions and has few or no elected officials. Where this occurs, and where one or more other
            incorporated places in the county or MCD continue to function as separate governments, even though they have been included in the consolidated
            government, the primary incorporated place is referred to as a consolidated city. The Census Bureau classifies the separately incorporated places
            within the consolidated city as place entities and creates a separate place (balance) record for the portion of the consolidated city not within any
            other place. The boundaries of the consolidated cities are those as of January 1, 2013, as reported through the Census Bureau's Boundary and
            Annexation Survey(BAS).
    
            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
    
  6. a

    072121 Mowle attachment 3

    • redistricting-gallery-coleg.hub.arcgis.com
    Updated Aug 7, 2021
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    louis_pino (2021). 072121 Mowle attachment 3 [Dataset]. https://redistricting-gallery-coleg.hub.arcgis.com/maps/d179e1ae00fa4a659b5febb21567121a
    Explore at:
    Dataset updated
    Aug 7, 2021
    Dataset authored and provided by
    louis_pino
    Area covered
    Description

    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

  7. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Kristen Carney (2024). Indiana Cities by Population [Dataset]. https://www.indiana-demographics.com/cities_by_population

Indiana Cities by Population

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 20, 2024
Dataset provided by
Cubit Planning, Inc.
Authors
Kristen Carney
License

https://www.indiana-demographics.com/terms_and_conditionshttps://www.indiana-demographics.com/terms_and_conditions

Area covered
Indiana
Description

A dataset listing Indiana cities by population for 2024.

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