57 datasets found
  1. Top 20 Countries' Population as Of 2020

    • kaggle.com
    Updated Feb 26, 2021
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    Baasim Ahmed (2021). Top 20 Countries' Population as Of 2020 [Dataset]. https://www.kaggle.com/baasimahmed/top-20-countries-population-as-of-2020/tasks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 26, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Baasim Ahmed
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    There's a story behind every dataset and here's your opportunity to share yours.

    Content

    What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

    Acknowledgements

    We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research. Credits and Information Taken by https://www.worldometers.info/world-population/

    Inspiration

    Your data will be in front of the world's largest data science community. What questions do you want to see answered?

  2. T

    POPULATION by Country in ASIA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2017
    + more versions
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    TRADING ECONOMICS (2017). POPULATION by Country in ASIA [Dataset]. https://tradingeconomics.com/country-list/population?continent=asia
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    May 26, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    Asia
    Description

    This dataset provides values for POPULATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  3. o

    Geonames - All Cities with a population > 1000

    • public.opendatasoft.com
    • data.smartidf.services
    • +2more
    csv, excel, geojson +1
    Updated Mar 10, 2024
    + more versions
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    (2024). Geonames - All Cities with a population > 1000 [Dataset]. https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/
    Explore at:
    csv, json, geojson, excelAvailable download formats
    Dataset updated
    Mar 10, 2024
    License

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

    Description

    All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

  4. Most Educated Country in the World

    • kaggle.com
    Updated Apr 6, 2024
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    Shahriar Kabir (2024). Most Educated Country in the World [Dataset]. https://www.kaggle.com/datasets/shahriarkabir/most-educated-country-in-the-world
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 6, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shahriar Kabir
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    Description:

    This dataset presents the tertiary education rates of the top ten most educated countries in the world. These countries have been ranked based on their tertiary education rates, showcasing their commitment to fostering educated populations and their global prominence in various fields. The dataset highlights the percentage of the population with completed tertiary education for each of these leading nations. With South Korea leading the pack at 69.29%, followed by Canada, Japan, Luxembourg, Ireland, Russia, Lithuania, the United Kingdom, the Netherlands, and Norway, this dataset provides valuable insights into global education trends and the impact of education on socioeconomic development.

    Columns:

    Country: Name of the country Tertiary_Education_Rate: Percentage of the population with completed tertiary education Potential Applications:

    • Comparative analysis of tertiary education rates among the top educated countries
    • Understanding the correlation between education levels and socioeconomic indicators
    • Identifying factors contributing to high educational attainment in leading nations
    • Benchmarking educational policies and initiatives against top-performing countries
  5. Countries population by year 2020

    • kaggle.com
    Updated Jun 19, 2020
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    Mohamed Fadl (2020). Countries population by year 2020 [Dataset]. https://www.kaggle.com/eng0mohamed0nabil/population-by-country-2020/activity
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 19, 2020
    Dataset provided by
    Kaggle
    Authors
    Mohamed Fadl
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    World Population World Population and top 20 Countries Live Clock. Population in the past, present, and future. Milestones. Global Growth Rate. World population by Region and by Religion. Population Density, Fertility Rate, Median Age, Migrants. All-time population total.

  6. H

    Switzerland - Population Density

    • data.humdata.org
    geotiff
    Updated Jun 10, 2025
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    WorldPop (2025). Switzerland - Population Density [Dataset]. https://data.humdata.org/dataset/1cdb9f8c-a8e2-49b8-9e20-d1addc550b19?force_layout=desktop
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    geotiffAvailable download formats
    Dataset updated
    Jun 10, 2025
    Dataset provided by
    WorldPop
    Area covered
    Switzerland
    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

  7. Estimates of the population for the UK, England, Wales, Scotland, and...

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Oct 8, 2024
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    Office for National Statistics (2024). Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
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    xlsxAvailable download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom, England, Ireland
    Description

    National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

  8. World-population2023

    • kaggle.com
    Updated Jan 29, 2023
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    Dinar khan (2023). World-population2023 [Dataset]. https://www.kaggle.com/dinarkhan/worldpopulation2023/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 29, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Dinar khan
    Area covered
    World
    Description

    The increased world population is among the fierce problems the world is facing right now and it will get uncontrolled in the coming future if proper steps for its betterment were not taken immediately. This world has observed the fastest growth during the 20th century. In the 1950s world population was 2.7 billion, By the end of this year it will cross 8 billion. This dataset is uploaded with the assumption to use your Data Science, Machine learning, and Predictive analytics skills and answer the following questions. 1. Which countries have the highest growth rate. 2. What are the densely populated countries in the world. 3. Keeping in view all the variables in mind which countries should take serious steps to control their population.

  9. A

    ‘Country Socioeconomic Status Scores: 1880-2010’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 24, 2018
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2018). ‘Country Socioeconomic Status Scores: 1880-2010’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-country-socioeconomic-status-scores-1880-2010-3da0/latest
    Explore at:
    Dataset updated
    Nov 24, 2018
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Country Socioeconomic Status Scores: 1880-2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sdorius/globses on 14 February 2022.

    --- Dataset description provided by original source is as follows ---

    This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the world’s people live in a country with a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

    See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

    VARIABLE DESCRIPTIONS: UNID: ISO numeric country code (used by the United Nations) WBID: ISO alpha country code (used by the World Bank) SES: Socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) country: Short country name year: Survey year SES: Socioeconomic status score (1-99) for each of 174 countries gdppc: GDP per capita: Single time-series (imputed) yrseduc: Completed years of education in the adult (15+) population popshare: Total population shares

    DATA SOURCES: The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita: 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. Maddison population data in 000s; GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls. 2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm 3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/ Total Population 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
    2. United Nations Population Division. 2009.

    --- Original source retains full ownership of the source dataset ---

  10. Afrobarometer Survey 2019-2021, Merged 34 Country - Africa

    • datafirst.uct.ac.za
    Updated Oct 9, 2024
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    Michigan State University (MSU) (2024). Afrobarometer Survey 2019-2021, Merged 34 Country - Africa [Dataset]. https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/991
    Explore at:
    Dataset updated
    Oct 9, 2024
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    University of Cape Town (UCT)
    Institute for Development Studies (IDS)
    Michigan State University (MSU)
    Institute for Empirical Research in Political Economy (IREEP)
    Ghana Centre for Democratic Development (CDD)
    Time period covered
    2019 - 2021
    Area covered
    Africa
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countires and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, and Round 4 (2008) 20 countries.The survey covered 34 countries in Round 5 (2011-2013), 36 countries in Round 6 (2014-2015), and 34 countries in Round 7 (2016-2018). Round 8 covered 34 African countries. The 34 countries covered in Round 8 (2019-2021) are:

    Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Côte d'Ivoire, eSwatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

    Geographic coverage

    The survey has national coverage in the following 34 African countries: Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Côte d'Ivoire, eSwatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

    Analysis unit

    Households and individuals

    Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    Kind of data

    Sample survey data

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalised settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewers alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

    Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

    Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found in Section 5 of the Afrobarometer Round 5 Survey Manual

    Mode of data collection

    Face-to-face

    Research instrument

    The questionnaire for Round 3 addressed country-specific issues, but many of the same questions were asked across surveys. The survey instruments were not standardized across all countries and the following features should be noted:

    • In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

    • This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

    • Response options also varied on some questions, and where applicable, these differences are also noted.

  11. Afrobarometer Survey 2025 - Cameroon

    • datacatalog.ihsn.org
    • microdata.worldbank.org
    Updated Jun 18, 2025
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    Ghana Centre for Democratic Development (CDD) (2025). Afrobarometer Survey 2025 - Cameroon [Dataset]. https://datacatalog.ihsn.org/catalog/12960
    Explore at:
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    University of Nairobi in Kenya
    Institute for Development Studies (IDS)
    Ghana Centre for Democratic Development (CDD)
    Time period covered
    2025
    Area covered
    Cameroon
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, Round 7 (2016-2018) 34 countries, Round 8 (2019-2021), and Round 9 (2021-2023). The survey covers about 40 countries in Round 10.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Universe

    Citizens of Cameroon who are 18 years and older

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    Cameroon - Sample size: 1,200 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and urban-rural location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual - Weighting: Weighted to account for individual selection probabilities - Sampling frame: 2005 population census

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The Round 10 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

    Response rate

    Response rate was 52.8%.

    Sampling error estimates

    The sample size yields country-level results with a margin of error of +/-3 percentage points at a 95% confidence level.

  12. f

    20 Richest Counties in Florida

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

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

    Area covered
    Florida
    Description

    A dataset listing Florida counties by population for 2024.

  13. g

    20 Richest Counties in Georgia

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

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

    Area covered
    Georgia
    Description

    A dataset listing Georgia counties by population for 2024.

  14. Country Socioeconomic Status Scores: 1880-2010

    • kaggle.com
    Updated Apr 18, 2017
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    sdorius (2017). Country Socioeconomic Status Scores: 1880-2010 [Dataset]. https://www.kaggle.com/sdorius/globses/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 18, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    sdorius
    Description

    This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the world’s people live in a country with a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

    See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

    VARIABLE DESCRIPTIONS: UNID: ISO numeric country code (used by the United Nations) WBID: ISO alpha country code (used by the World Bank) SES: Socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) country: Short country name year: Survey year SES: Socioeconomic status score (1-99) for each of 174 countries gdppc: GDP per capita: Single time-series (imputed) yrseduc: Completed years of education in the adult (15+) population popshare: Total population shares

    DATA SOURCES: The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita: 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. Maddison population data in 000s; GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls. 2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm 3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/ Total Population 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
    2. United Nations Population Division. 2009.

  15. w

    20 Richest Counties in Washington

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

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

    Area covered
    Washington
    Description

    A dataset listing Washington counties by population for 2024.

  16. Afrobarometer Survey 2016-2018, Merged Round 7 Data (34 Countries) - Benin,...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Apr 27, 2021
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    Institute for Empirical Research in Political Economy (IREEP) (2021). Afrobarometer Survey 2016-2018, Merged Round 7 Data (34 Countries) - Benin, Burkina Faso, Botswana, Côte d'Ivoire, Cameroon, Cabo Verde, Gabon, Ghana, Guinea, Gambia, The, Kenya, Liberia, Lesotho, Morocco, Madagas... [Dataset]. https://microdata.worldbank.org/index.php/catalog/3805
    Explore at:
    Dataset updated
    Apr 27, 2021
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    Institute for Development Studies (IDS)
    Michigan State University (MSU)
    Institute for Empirical Research in Political Economy (IREEP)
    University of Cape Town (UCT, South Africa)
    Ghana Centre for Democratic Development (CDD)
    Time period covered
    2016 - 2018
    Area covered
    Burkina Faso, Benin, Cameroon, Guinea, Gabon, Cabo Verde, Lesotho, Ghana, Botswana, Liberia
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, and Round 6 (2014-2015) 36 countries. The survey covered 34 countries in Round 7 (2016-2018).

    Geographic coverage

    The survey has national coverage in the following 34 African countries: Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Côte d'Ivoire, eSwatini, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, São Tomé and Príncipe, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia and Zimbabwe.

    Analysis unit

    Individuals

    Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

    Data weights For some national surveys, data are weighted to correct for over or under-sampling or for household size. "Withinwt" should be turned on for all national -level descriptive statistics in countries that contain this weighting variable. It is included as the last variable in the data set, with details described in the codebook. For merged data sets, "Combinwt" should be turned on for cross-national comparisons of descriptive statistics. Note: this weighting variable standardizes each national sample as if it were equal in size.

    Further information on sampling protocols, including full details of the methodologies used for each stage of sample selection, can be found at https://afrobarometer.org/surveys-and-methods/sampling-principles

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire for Round 7 addressed country-specific issues, but many of the same questions were asked across surveys. The survey instruments were not standardized across all countries and the following features should be noted:

    • In the seven countries that originally formed the Southern Africa Barometer (SAB) - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe - a standardized questionnaire was used, so question wording and response categories are the generally the same for all of these countries. The questionnaires in Mali and Tanzania were also essentially identical (in the original English version). Ghana, Uganda and Nigeria each had distinct questionnaires.

    • This merged dataset combines, into a single variable, responses from across these different countries where either identical or very similar questions were used, or where conceptually equivalent questions can be found in at least nine of the different countries. For each variable, the exact question text from each of the countries or groups of countries ("SAB" refers to the Southern Africa Barometer countries) is listed.

    • Response options also varied on some questions, and where applicable, these differences are also noted.

  17. United States US: Income Share Held by Highest 20%

    • ceicdata.com
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    CEICdata.com, United States US: Income Share Held by Highest 20% [Dataset]. https://www.ceicdata.com/en/united-states/poverty/us-income-share-held-by-highest-20
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 1979 - Dec 1, 2016
    Area covered
    United States
    Description

    United States US: Income Share Held by Highest 20% data was reported at 46.900 % in 2016. This records an increase from the previous number of 46.400 % for 2013. United States US: Income Share Held by Highest 20% data is updated yearly, averaging 46.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 41.200 % in 1979. United States US: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  18. Afrobarometer Survey 2021 - Sudan

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Apr 19, 2023
    + more versions
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    University of Cape Town (UCT, South Africa) (2023). Afrobarometer Survey 2021 - Sudan [Dataset]. https://catalog.ihsn.org/catalog/study/SDN_2021_AFB-R8_v01_M
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    Dataset updated
    Apr 19, 2023
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    Institute for Development Studies (IDS)
    Michigan State University (MSU)
    Institute for Empirical Research in Political Economy (IREEP)
    University of Cape Town (UCT, South Africa)
    Ghana Centre for Democratic Development (CDD)
    Time period covered
    2021
    Area covered
    Sudan
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Universe

    Citizens of Sudan who are 18 years and older

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

    Sudan - Sample size: 1,800 - Sampling Frame: 2008 National Population and Housing Census, produced by the Sudan National Bureau of Statistics, updated in 2020 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and rural-urban location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

    The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

    Response rate

    Outcome rates: - Contact rate: 90% - Response rate: 88%

    Sampling error estimates

    The sample size yields country-level results with a margin of error of +/-2.3 percentage points at a 95% confidence level.

  19. Afrobarometer Survey 2022 - South Africa

    • microdata.worldbank.org
    Updated Jun 11, 2025
    + more versions
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    Institute for Empirical Research in Political Economy (IREEP) (2025). Afrobarometer Survey 2022 - South Africa [Dataset]. https://microdata.worldbank.org/index.php/catalog/6751
    Explore at:
    Dataset updated
    Jun 11, 2025
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    Institute for Development Studies (IDS)
    Michigan State University (MSU)
    Institute for Empirical Research in Political Economy (IREEP)
    University of Cape Town (UCT, South Africa)
    Ghana Centre for Democratic Development (CDD)
    Time period covered
    2022
    Area covered
    South Africa
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, Round 7 (2016-2018) 34 countries, and Round 8 (2019-2021). The survey covered 39 countries in Round 9 (2021-2023).

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Universe

    Citizens of South Africa who are 18 years and older

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    South Africa - Sample size: 1,582 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and urban-rural location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual - Weighting: Weighted to account for individual selection probabilities

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The Round 9 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

    The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

    Response rate

    Response rate was 85%.

    Sampling error estimates

    The sample size yields country-level results with a margin of error of +/-2.5 percentage points at a 95% confidence level.

  20. Population estimates, quarterly

    • www150.statcan.gc.ca
    • moropho.click
    • +3more
    Updated Jun 18, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Population estimates, quarterly [Dataset]. http://doi.org/10.25318/1710000901-eng
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    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

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Baasim Ahmed (2021). Top 20 Countries' Population as Of 2020 [Dataset]. https://www.kaggle.com/baasimahmed/top-20-countries-population-as-of-2020/tasks
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Top 20 Countries' Population as Of 2020

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Feb 26, 2021
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Baasim Ahmed
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

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