41 datasets found
  1. N

    Black Earth, WI Annual Population and Growth Analysis Dataset: A...

    • neilsberg.com
    csv, json
    Updated Jul 30, 2024
    + more versions
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    Neilsberg Research (2024). Black Earth, WI Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Black Earth from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/black-earth-wi-population-by-year/
    Explore at:
    json, csvAvailable 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
    Black Earth, Wisconsin
    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 Black Earth 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 Black Earth 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 Black Earth was 1,448, a 0.34% decrease year-by-year from 2022. Previously, in 2022, Black Earth population was 1,453, a decline of 1.29% compared to a population of 1,472 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Black Earth increased by 122. In this period, the peak population was 1,494 in the year 2020. 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 Black Earth is shown in this column.
    • Year on Year Change: This column displays the change in Black Earth 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 Black Earth Population by Year. You can refer the same here

  2. N

    White Earth, ND Annual Population and Growth Analysis Dataset: A...

    • neilsberg.com
    csv, json
    Updated Jul 30, 2024
    + more versions
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    Neilsberg Research (2024). White Earth, ND Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in White Earth from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/white-earth-nd-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
    White Earth, North Dakota
    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 White Earth 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 White Earth 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 White Earth was 93, a 0% decrease year-by-year from 2022. Previously, in 2022, White Earth population was 93, a decline of 4.12% compared to a population of 97 in 2021. Over the last 20 plus years, between 2000 and 2023, population of White Earth increased by 28. In this period, the peak population was 99 in the year 2020. 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 White Earth is shown in this column.
    • Year on Year Change: This column displays the change in White Earth 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 White Earth Population by Year. You can refer the same here

  3. M

    World Population Growth Rate

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). World Population Growth Rate [Dataset]. https://www.macrotrends.net/global-metrics/countries/wld/world/population-growth-rate
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    Jan 1, 1961 - Dec 31, 2023
    Area covered
    World, World
    Description

    Historical chart and dataset showing World population growth rate by year from 1961 to 2023.

  4. World Population Statistics - 2023

    • kaggle.com
    Updated Jan 9, 2024
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    Bhavik Jikadara (2024). World Population Statistics - 2023 [Dataset]. https://www.kaggle.com/datasets/bhavikjikadara/world-population-statistics-2023
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bhavik Jikadara
    License

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

    Area covered
    World
    Description
    • The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
    • China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
    • The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
    • Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
    • In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
    • This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Content

    • In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
    • Rank: Rank by Population.
    • CCA3: 3 Digit Country/Territories Code.
    • Country/Territories: Name of the Country/Territories.
    • Capital: Name of the Capital.
    • Continent: Name of the Continent.
    • 2022 Population: Population of the Country/Territories in the year 2022.
    • 2020 Population: Population of the Country/Territories in the year 2020.
    • 2015 Population: Population of the Country/Territories in the year 2015.
    • 2010 Population: Population of the Country/Territories in the year 2010.
    • 2000 Population: Population of the Country/Territories in the year 2000.
    • 1990 Population: Population of the Country/Territories in the year 1990.
    • 1980 Population: Population of the Country/Territories in the year 1980.
    • 1970 Population: Population of the Country/Territories in the year 1970.
    • Area (km²): Area size of the Country/Territories in square kilometers.
    • Density (per km²): Population Density per square kilometer.
    • Growth Rate: Population Growth Rate by Country/Territories.
    • World Population Percentage: The population percentage by each Country/Territories.
  5. Population of the world 10,000BCE-2100

    • statista.com
    Updated Aug 7, 2024
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    Statista (2024). Population of the world 10,000BCE-2100 [Dataset]. https://www.statista.com/statistics/1006502/global-population-ten-thousand-bc-to-2050/
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    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

  6. Total population worldwide 1950-2100

    • statista.com
    • ai-chatbox.pro
    Updated Feb 24, 2025
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    Statista (2025). Total population worldwide 1950-2100 [Dataset]. https://www.statista.com/statistics/805044/total-population-worldwide/
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    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolongued development arc in Sub-Saharan Africa.

  7. A

    Data from: U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana,...

    • data.amerigeoss.org
    • data.nasa.gov
    • +4more
    html, jpeg
    Updated Jul 30, 2019
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    United States[old] (2019). U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana, and Mississippi, Alpha Version [Dataset]. https://data.amerigeoss.org/hu/dataset/u-s-population-grids-summary-file-3-2000-alabama-louisiana-and-mississippi-alpha-version-b0bd8
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    html, jpegAvailable download formats
    Dataset updated
    Jul 30, 2019
    Dataset provided by
    United States[old]
    Area covered
    Mississippi, Alabama, Louisiana, United States
    Description

    The U.S. Population Grids (Summary File 3), 2000: Alabama, Louisiana, and Mississippi, Alpha Version data set contains an ARC/INFO Workspace with grids of demographic data from the year 2000 census. The grids have a resolution of 30 arc-seconds (0.0083 decimal degrees), or approximately 1 square km. The gridded variables are based on census block geography from Census 2000 TIGER/Line Files and census variables (income, poverty, education, housing age). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

  8. a

    GPWv4 Population Density, 2015

    • hub.arcgis.com
    • cloud.csiss.gmu.edu
    • +2more
    Updated Mar 14, 2018
    + more versions
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    ArcGIS StoryMaps (2018). GPWv4 Population Density, 2015 [Dataset]. https://hub.arcgis.com/maps/d314746e11834a04968e64b25c49882c
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    Dataset updated
    Mar 14, 2018
    Dataset authored and provided by
    ArcGIS StoryMaps
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    GPWv4 is a gridded data product that depicts global population data from the 2010 round of Population and Housing Censuses. The Population Density, 2015 layer represents persons per square kilometer for year 2015. Data SummaryGPWv4 is constructed from national or subnational input areal units of varying resolutions. The native grid cell size is 30 arc-seconds, or ~1 km at the equator. Separate grids are available for population count, population density, estimated land area, and data quality indicators; which include the water mask represented in this service. Population estimates are derived by extrapolating the raw census counts to estimates for the 2010 target year. The development of GPWv4 builds upon previous versions of the data set (Tobler et al., 1997; Deichmann et al., 2001; Balk et al., 2006).The full GPWv4 data collection will consist of population estimates for the years 2000, 2005, 2010, 2015, and 2020, and will include grids for estimates of total population, age, sex, and urban/rural status. However, this release consists only of total population estimates for the year 2015. This data is being released now to allow users access to the population grids.Recommended CitationCenter for International Earth Science Information Network - CIESIN - Columbia University. 2016. Gridded Population of the World, Version 4 (GPWv4): Population Density. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4NP22DQ. Accessed DAY MONTH YEAR

  9. Somalia - Population Density - Dataset - SODMA Open Data Portal

    • sodma-dev.okfn.org
    Updated May 23, 2025
    + more versions
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    sodma-dev.okfn.org (2025). Somalia - Population Density - Dataset - SODMA Open Data Portal [Dataset]. https://sodma-dev.okfn.org/dataset/worldpop-population-density-for-somalia
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    Dataset updated
    May 23, 2025
    Dataset provided by
    Open Knowledge Foundationhttp://okfn.org/
    Somali Disaster Management Agencyhttps://sodma.gov.so/
    Area covered
    Somalia
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

  10. United Republic of Tanzania - Population Density - Dataset - ADH Data Portal...

    • ckan.africadatahub.org
    Updated Jun 24, 2022
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    ckan.africadatahub.org (2022). United Republic of Tanzania - Population Density - Dataset - ADH Data Portal [Dataset]. https://ckan.africadatahub.org/dataset/united-republic-of-tanzania-population-density
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    Dataset updated
    Jun 24, 2022
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Area covered
    Tanzania
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

  11. Somalia - Population Density - Dataset - ADH Data Portal

    • ckan.africadatahub.org
    Updated Jun 24, 2022
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    ckan.africadatahub.org (2022). Somalia - Population Density - Dataset - ADH Data Portal [Dataset]. https://ckan.africadatahub.org/dataset/somalia-population-density
    Explore at:
    Dataset updated
    Jun 24, 2022
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Area covered
    Somalia
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

  12. d

    Otero County Block Groups, Total Population (2010)

    • datasets.ai
    • gimi9.com
    • +3more
    21, 55, 57
    + more versions
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    Earth Data Analysis Center, University of New Mexico, Otero County Block Groups, Total Population (2010) [Dataset]. https://datasets.ai/datasets/otero-county-block-groups-total-population-2010
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    55, 57, 21Available download formats
    Dataset authored and provided by
    Earth Data Analysis Center, University of New Mexico
    Area covered
    Otero County
    Description

    The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was reOterosed on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics were reOterosed in the summer of 2011. The data in this particular RGIS COteroringhouse table is for all Block Groups in Otero County. The table provides total counts population.

  13. u

    Bernalillo County 2010 Census Tracts

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
    + more versions
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    Earth Data Analysis Center (2011). Bernalillo County 2010 Census Tracts [Dataset]. https://gstore.unm.edu/apps/rgis/datasets/be59f00d-fb91-423f-9d8b-a46cd1b07f26/metadata/FGDC-STD-001-1998.html
    Explore at:
    zip(1), geojson(5), gml(5), shp(5), csv(5), kml(5), xls(5), json(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    West Bounding Coordinate -107.19617 East Bounding Coordinate -106.149575 North Bounding Coordinate 35.219639 South Bounding Coordinate 34.869024, Cibola County (35006)
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 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, 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.

  14. d

    Curry County Blocks, Total Population (2010)

    • datasets.ai
    • gstore.unm.edu
    • +2more
    21, 55, 57
    + more versions
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    Earth Data Analysis Center, University of New Mexico, Curry County Blocks, Total Population (2010) [Dataset]. https://datasets.ai/datasets/curry-county-blocks-total-population-2010
    Explore at:
    57, 55, 21Available download formats
    Dataset authored and provided by
    Earth Data Analysis Center, University of New Mexico
    Description

    The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was released on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics were released in the summer of 2011. The data in this particular RGIS Clearinghouse table are for all blocks in Curry County. The data table provides counts of the total population. This file, along with specific narrative descriptions and definitions (in Word and text formats) are available in a single zip file.

  15. Data from: Data sets for the identification of a global typology for coastal...

    • dataservices.gfz-potsdam.de
    Updated 2019
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    Till Sterzel; Matthias K. B. Lüdeke; Carsten Walther; Marcel Kok; Diana Sietz; Paul Lucas; Carsten Walther (2019). Data sets for the identification of a global typology for coastal urban vulnerability under rapid urbanization [Dataset]. http://doi.org/10.5880/pik.2019.020
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    Dataset updated
    2019
    Dataset provided by
    DataCitehttps://www.datacite.org/
    GFZ Data Services
    Authors
    Till Sterzel; Matthias K. B. Lüdeke; Carsten Walther; Marcel Kok; Diana Sietz; Paul Lucas; Carsten Walther
    License

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

    Area covered
    Earth
    Description

    Coastal areas are urbanizing at unprecedented rates, particularly in low- and middle-income countries. Combinations of long-standing and emerging problems in these urban areas generate vulnerability for human well-being and ecosystems alike. Based on the presented data sets a spatially explicit global systematization of these problems into typical urban vulnerability profiles can be derived for the year 2000 using largely sub-national data. We present here 11 indicator datasets for urban expansion, urban population growth, marginalization of poor populations, government effectiveness, exposures and damages to climate-related extreme events, low-lying settlement, and wetlands prevalence. Applying a standard k-means cluster analysis to this input data reveals a global typology of seven clearly distinguishable clusters, or urban profiles of vulnerability (for results see Sterzel et. al., 2019).

  16. u

    Census MAF/TIGER database

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
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    Earth Data Analysis Center (2011). Census MAF/TIGER database [Dataset]. https://gstore.unm.edu/apps/rgisarchive/datasets/5375df01-f194-433e-b224-c3c2a6ce1758/metadata/FGDC-STD-001-1998.html
    Explore at:
    json(5), kml(5), shp(5), xls(5), csv(5), zip(1), gml(5), geojson(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    West Bounding Coordinate -106.058364 East Bounding Coordinate -105.200117 North Bounding Coordinate 36.995991 South Bounding Coordinate 36.013014, Rio Arriba County (35039)
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 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, 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.

  17. w

    Socorro County Blocks, Total Population (2010)

    • data.wu.ac.at
    • datadiscoverystudio.org
    • +5more
    html, xml, zip
    Updated Jun 25, 2014
    + more versions
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    Earth Data Analysis Center, University of New Mexico (2014). Socorro County Blocks, Total Population (2010) [Dataset]. https://data.wu.ac.at/odso/data_gov/MWIyOGNlZjctZmNlNy00YmY0LTg1MmQtZWRiODgxMzkwMWNj
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    xml, zip, htmlAvailable download formats
    Dataset updated
    Jun 25, 2014
    Dataset provided by
    Earth Data Analysis Center, University of New Mexico
    Area covered
    07bad9f20d7669e5c11433193b1a56aa914bc4bc
    Description

    The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was released on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics were released in the summer of 2011. The data in this particular RGIS Clearinghouse table are for all blocks in Socorro County. The data table provides counts of the total population. This file, along with specific narrative descriptions and definitions (in Word and text formats) are available in a single zip file.

  18. u

    Census MAF/TIGER database

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Jun 6, 2011
    + more versions
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    Earth Data Analysis Center (2011). Census MAF/TIGER database [Dataset]. https://gstore.unm.edu/apps/rgisarchive/datasets/71879d09-efa7-474f-bb05-085e45d0e0d0/metadata/FGDC-STD-001-1998.html
    Explore at:
    shp(5), json(5), csv(5), zip(1), geojson(5), gml(5), kml(5), xls(5)Available download formats
    Dataset updated
    Jun 6, 2011
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Jan 2010
    Area covered
    West Bounding Coordinate -109.046221 East Bounding Coordinate -107.066694 North Bounding Coordinate 35.348446 South Bounding Coordinate 34.577576, McKinley County (35031)
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that 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) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 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, 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.

  19. Somalia - Age and sex structures - Dataset - SODMA Open Data Portal

    • sodma-dev.okfn.org
    Updated May 23, 2025
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    sodma-dev.okfn.org (2025). Somalia - Age and sex structures - Dataset - SODMA Open Data Portal [Dataset]. https://sodma-dev.okfn.org/dataset/worldpop-age-and-sex-structures-for-somalia
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    Dataset updated
    May 23, 2025
    Dataset provided by
    Open Knowledge Foundationhttp://okfn.org/
    Somali Disaster Management Agencyhttps://sodma.gov.so/
    Area covered
    Somalia
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  20. d

    Catron County Block Groups, Total Population (2010)

    • datasets.ai
    • gstore.unm.edu
    • +1more
    21, 55, 57
    + more versions
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    Earth Data Analysis Center, University of New Mexico, Catron County Block Groups, Total Population (2010) [Dataset]. https://datasets.ai/datasets/catron-county-block-groups-total-population-2010
    Explore at:
    55, 57, 21Available download formats
    Dataset authored and provided by
    Earth Data Analysis Center, University of New Mexico
    Area covered
    Catron County
    Description

    The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was released on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics were released in the summer of 2011. The data in this particular RGIS Clearinghouse table is for all Block Groups in Catron County. The table provides total counts population.

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Neilsberg Research (2024). Black Earth, WI Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Black Earth from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/black-earth-wi-population-by-year/

Black Earth, WI Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Black Earth from 2000 to 2023 // 2024 Edition

Explore at:
json, csvAvailable 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
Black Earth, Wisconsin
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 Black Earth 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 Black Earth 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 Black Earth was 1,448, a 0.34% decrease year-by-year from 2022. Previously, in 2022, Black Earth population was 1,453, a decline of 1.29% compared to a population of 1,472 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Black Earth increased by 122. In this period, the peak population was 1,494 in the year 2020. 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 Black Earth is shown in this column.
  • Year on Year Change: This column displays the change in Black Earth 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 Black Earth Population by Year. You can refer the same here

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