100+ datasets found
  1. Share of Gen Z improving environmental impact in the U.S. 2022, by...

    • statista.com
    • ai-chatbox.pro
    Updated Jun 27, 2025
    + more versions
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    Statista (2025). Share of Gen Z improving environmental impact in the U.S. 2022, by demographic [Dataset]. https://www.statista.com/statistics/1356487/us-improving-environmental-impact-gen-z-by-demographic/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2021 - Jul 2022
    Area covered
    United States
    Description

    In a survey conducted from October 2021 to July 2022, respondents revealed that Gen Zers (or zoomers) cared about improving their environmental impact. Gen Zers who have attained a high education were those who found improving their environmental impact the most important, with **** percent stating they found it very important.

  2. e

    Business environment; corporate demographic dynamics in the Netherlands

    • data.europa.eu
    atom feed, json
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    Business environment; corporate demographic dynamics in the Netherlands [Dataset]. https://data.europa.eu/data/datasets/1765-ondernemingsklimaat-bedrijfsdemografische-dynamiek-in-nederland
    Explore at:
    atom feed, jsonAvailable download formats
    License

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

    Area covered
    Netherlands
    Description

    Establishment and dismantling of businesses and company demographics dynamics by industry. 1987-2004 Amended on 26 June 2009. Appearance Frequency: Stop it.

  3. Great Plains Population and Environment Data: Social and Demographic Data,...

    • icpsr.umich.edu
    ascii, sas, spss +1
    Updated Feb 7, 2007
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    Gutmann, Myron P. (2007). Great Plains Population and Environment Data: Social and Demographic Data, 1870-2000 [United States] [Dataset]. http://doi.org/10.3886/ICPSR04296.v2
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    ascii, stata, sas, spssAvailable download formats
    Dataset updated
    Feb 7, 2007
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Gutmann, Myron P.
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/4296/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/4296/terms

    Time period covered
    1870 - 2000
    Area covered
    United States, North Dakota, Texas, Kansas, Oklahoma, New Mexico, Wyoming, Nebraska, South Dakota, Montana
    Description

    The social and demographic data included in this collection consist of a single data file for each decennial year between 1870 and 2000, covering 10 of the 12 Great Plains states. Information on a variety of social and demographic topics was gathered to historically characterize populations living in counties within the United States Great Plains, in terms of: (1) urban, rural, and total population, (2) vital statistics, (3) net migration, (4) age and sex, (5) nativity and ancestry, (6) education and literacy, (7) religion, (8) industry, and (9) housing and other characteristics. These data include selected material compiled as part of the United States population census. The United States Census of Population and Housing has been conducted since 1790 on a regular schedule that is decennial. The county-level social and demographic data produced by the United States government as a result constitute a consistent series of measures capturing changes in the United States population's size, composition, and other characteristics. A subset of the variables available from the short and long-form survey questionnaires of the United States Census of Population and Housing (as compiled for counties) were extracted from previously existing digital files. Besides the decennial census of the population, county-level data were drawn from an assortment of existing digital files as well as sources that were manually digitized. Other data include compilations of county-level information gathered from various federal agencies and private organizations as well as the agriculture and economic censuses. Supplementing these compilations are manually digitized consumer market data, religious data, and vital statistics, including information about births, deaths, marriage, and divorce.

  4. d

    Wave 18, February 2011

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Ipsos (2023). Wave 18, February 2011 [Dataset]. http://doi.org/10.5683/SP2/7KMHSI
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    Feb 1, 2011
    Description

    Ipsos Global @dvisor wave 18 was conducted on February 2 and February 14, 2011. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, CB: Environmental Concern.

  5. A

    2017 Patient Demographic Environment

    • data.amerigeoss.org
    • data.wu.ac.at
    csv, json, rdf, xml
    Updated Apr 26, 2018
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    United States (2018). 2017 Patient Demographic Environment [Dataset]. https://data.amerigeoss.org/id/dataset/2017-patient-demographic-environment
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    csv, xml, rdf, jsonAvailable download formats
    Dataset updated
    Apr 26, 2018
    Dataset provided by
    United States
    Description

    This dataset shows the patient demographic environment for 2017

  6. Data and code from: Size-by-environment interactions: a neglected dimension...

    • figshare.com
    zip
    Updated Jun 2, 2023
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    Andrew Tredennick; Brittany J. Teller; Peter B. Adler; Giles Hooker; Stephen Ellner (2023). Data and code from: Size-by-environment interactions: a neglected dimension of species' responses to environmental variation [Dataset]. http://doi.org/10.6084/m9.figshare.6980054.v1
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    zipAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Andrew Tredennick; Brittany J. Teller; Peter B. Adler; Giles Hooker; Stephen Ellner
    License

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

    Description

    General InformationSee the 'ReadMe.md' in the root directory of this fileset for information on running the codes. Email Andrew Tredennick (atredenn@gmail.com) if you encounter any issues. Note that several of our IPM-based analyses take a while to run, so these codes are not presented as "source-and-get-results", but rather as guides through our analyses. They will, of course, run, but their implementation is not as seamless as the codes for fitting the models.Any updates to these materials can be accessed on the Github page for this project: https://github.com/atredennick/size-environment.Citation InformationThis file set contains data and code to reproduce the results reported in:Tredennick, A.T., B.J. Teller, Adler, P.B., Hooker, G., Ellner, S.P. (In press). Size-by-environment interactions: a neglected dimension of species' responses to environmental variation. Ecology Letters.If you use the data or code deposited here, please cite the original paper (above) as well as this fileset:Tredennick, A.T., B.J. Teller, Adler, P.B., Hooker, G., Ellner, S.P.
    (2018). Date and code from: Size-by-environment interactions: a neglected dimension of species' responses to environmental variation. Figshare. 10.6084/m9.figshare.6980054.

  7. d

    Data from: How well can body size represent effects of the environment on...

    • search.dataone.org
    • datadryad.org
    Updated Mar 31, 2025
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    Mollie E. Brooks; Marianne Mugabo; Gwendolen M. Rogers; Timothy G. Benton; Arpat Ozgul; Gwendolen M. Rodgers (2025). How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables [Dataset]. http://doi.org/10.5061/dryad.pq161
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    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Mollie E. Brooks; Marianne Mugabo; Gwendolen M. Rogers; Timothy G. Benton; Arpat Ozgul; Gwendolen M. Rodgers
    Time period covered
    Jan 1, 2015
    Description

    Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied w...

  8. U.S. adults concerned about daily activity on the environment by demographic...

    • statista.com
    Updated Feb 6, 2023
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    Statista (2023). U.S. adults concerned about daily activity on the environment by demographic 2017 [Dataset]. https://www.statista.com/statistics/729601/us-concerns-about-daily-activity-on-the-environment-by-demographic/
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    Dataset updated
    Feb 6, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    United States
    Description

    This statistic represents a 2017 survey conducted on U.S. adults regarding their concerns for their typical daily activities and their effects on the environment. Some 25 percent of female participants responded that they were not very concerned about the effects of their daily activities on the environment.

  9. d

    Data from: Partitioning variance in population growth for models with...

    • search.dataone.org
    • datadryad.org
    • +1more
    Updated Nov 29, 2023
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    Jonas Knape; Matthieu Paquet; Debora Arlt; Ineta KaÄ ergytÄ—; Tomas Pärt (2023). Partitioning variance in population growth for models with environmental and demographic stochasticity [Dataset]. http://doi.org/10.5061/dryad.98sf7m0pj
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    Dataset updated
    Nov 29, 2023
    Dataset provided by
    Dryad Digital Repository
    Authors
    Jonas Knape; Matthieu Paquet; Debora Arlt; Ineta KaÄ ergytÄ—; Tomas Pärt
    Time period covered
    Jan 1, 2023
    Description

    How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual ‘realized’ growth rates have gained in popularity. Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. We extend realized LTREs in two ways. First, we furt...

  10. d

    Data for: Environmental complexity mitigates the demographic impact of...

    • datadryad.org
    • search.dataone.org
    • +1more
    zip
    Updated Oct 24, 2023
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    David Berger (2023). Data for: Environmental complexity mitigates the demographic impact of sexual selection [Dataset]. http://doi.org/10.5061/dryad.bzkh189g8
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    zipAvailable download formats
    Dataset updated
    Oct 24, 2023
    Dataset provided by
    Dryad
    Authors
    David Berger
    Time period covered
    2023
    Description

    Data for: Environmental complexity mitigates the demographic impact of sexual selection

    https://doi.org/10.5061/dryad.bzkh189g8

    Description of the data and file structure

    The data underlying all analyses is available in the Excel file containing 5 spreadsheets, or as separate txt files, with the following names;

    "Trait-values of founding lines" (used to ordinate experimental evolution line founders and test for differences between regimes in evolution of mating traits - Fig 1B) Means for each of the six evolution lines (given by the "Evolution Regime" and "founder" columns) for the following traits: - Sperm competition success (given as the proportion of offspring sired in competition with a reference male) - Sperm production (estimated number of sperm, matured over 25h, transferred by a male to a female) - remating rate (a relative measure of the probability of remating in the first 24h following the first mating) - male-male fertility decline (the proportional decline i...

  11. g

    GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business...

    • datastore.gapmaps.com
    Updated Aug 14, 2024
    + more versions
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    GapMaps (2024). GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business Decisions | Consumer Spending Data| Demographic Data [Dataset]. https://datastore.gapmaps.com/products/gapmaps-premium-demographic-data-by-ags-usa-canada-gis-gapmaps
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    Dataset updated
    Aug 14, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Canada, United States
    Description

    GapMaps GIS Data sourced from Applied Geographic Solutions includes over 40k Demographic variables across topics including estimates & projections on population, demographics, neighborhood segmentation, consumer spending, crime index & environmental risk available at census block level.

  12. MANET: uncertainty in demographics – data on population projections

    • zenodo.org
    • data.niaid.nih.gov
    zip
    Updated Aug 19, 2024
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    Sara Giarola; Sara Giarola (2024). MANET: uncertainty in demographics – data on population projections [Dataset]. http://doi.org/10.5281/zenodo.13335264
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    zipAvailable download formats
    Dataset updated
    Aug 19, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Sara Giarola; Sara Giarola
    License

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

    Description

    This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future).

    More specifically, it contains:

    - in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME

    - in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace

    - in the `UN` folder, the demographic projections from UN

    - `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases

    - `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future

    '- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6

    This data in intended to be downloaded for use together with the package downloadable here.

    The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).

  13. n

    Global Demographic Data

    • access.earthdata.nasa.gov
    Updated Apr 21, 2017
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    (2017). Global Demographic Data [Dataset]. https://access.earthdata.nasa.gov/collections/C1214610969-SCIOPS
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    Dataset updated
    Apr 21, 2017
    Time period covered
    Jan 1, 1985 - Jan 1, 2025
    Area covered
    Earth
    Description

    The Global Demographic Data collection holds global gridded data products describing demographic information and water demand in relation to population data. Currently, water demand data are being distributed; population data will be added in the near future.

    Country-level urban, rural and total population estimate data from World Resources Institute (WRI) for the years 1985, 1995, and 2025 were gridded by the University of New Hampshire's Water Systems Analysis Groupusing methods outlined in Vorosmarty et al. (2000) for use in estimating global water resources based on climate and population changes.

    Currently available are five relative water demand (RWD) fraction data sets/ maps, produced by Vorosmarty et al. in their analysis of future water resources. The relative water demand is defined to be the total volume of water used either domestically, industrially or agriculturally (DIA) divided by the water discharge (Q). "Values of .2 to .4 indicate medium to high stress." (see Vorosmarty et al., 2000) This analysis deals only with sustainable water sources, and does not look at nonsustainable water sources, such a ground water mining. The RWD is computed on a .5 by .5 degree grid for two sentinel years: 1985 and 2025, which are two of the data sets. The ratio of the RWD for these two years provides a measure of change under scenarios of climate change only, population change only and the combination of climate change and population to produce the other three datasets. The ratio RWD values is relative to the RWD in the base year, 1985.

  14. d

    Synthetic: National Population Health Survey, 1994-1995 [Canada]: Cycle 1

    • dataone.org
    Updated Dec 28, 2023
    + more versions
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    Statistics Canada (2023). Synthetic: National Population Health Survey, 1994-1995 [Canada]: Cycle 1 [Dataset]. http://doi.org/10.5683/SP3/SYMR3E
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Statistics Canada
    Time period covered
    Jan 1, 1994 - Jan 1, 1995
    Description

    Please note: This is a Synthetic data file, also known as a Dummy file - it is not real data. This synthetic file should not be used for purposes other than to develop an test computer programs that are to be submitted by remote access. Each record in the synthetic file matches the format and content parameters of the real Statistics Canada Master File with which it is associated, but the data themselves have been 'made up'. They do NOT represent responses from real individuals and should NOT be used for actual analysis. These data are provided solely for the purpose of testing statistical package 'code' (e.g. SPSS syntax, SAS programs, etc.) in preperation for analysis using the associated Master File in a Research Data Centre, by Remote Job Submission, or by some other means of secure access. If statistical analysis 'code' works with the synthetic data, researchers can have some confidence that the same code will run successfully against the Master File data in the Resource Data Centres. In the fall of 1991, the National Health Information Council recommended that an ongoing national survey of population health be conducted. This recommendation was based on consideration of the economic and fiscal pressures on the health care systems and the requirement for information with which to improve the health status of the population in Canada. Commencing in April 1992, Statistics Canada received funding for development of a National Population Health Survey (NPHS). The NPHS collects information related to the health of the Canadian population and related socio-demographic information to: aid in the development of public policy by providing measures of the level, trend and distribution of the health status of the population, provide data for analytic studies that will assist in understanding the determinants of health, and collect data on the economic, social, demographic, occupational and environmental correlates of health. In addition the NPHS seeks to increase the understanding of the relationship between health status and health care utilization, including alternative as well as traditional services, and also to allow the possibility of linking survey data to routinely collected administrative data such as vital statistics, environmental measures, community variables, and health services utilization. The NPHS collects information related to the health of the Canadian population and related socio-demographic information. It is composed of three components: the Households, the Health Institutions, and the North components. The Household component started in 1994/1995 and is conducted every two years. The first cycle of the NPHS is both longitudinal and cross-sectional. The NPHS longitudinal sample includes 17,276 persons from all ages in 1994/1995 and these same persons will be interviewed every two years. Health Canada, Public Health Agency of Canada and provincial ministries of health use NPHS longitudinal data to plan, implement and evaluate programs and health policies to improve health and the efficiency of health services. Non-profit health organizations and researchers in the academic fields use the information to move research ahead and to improve health.

  15. a

    Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy

    • hub.arcgis.com
    • africageoportal.com
    Updated Aug 20, 2020
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    Africa GeoPortal (2020). Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy [Dataset]. https://hub.arcgis.com/maps/ffd1b8a7ffbf4b758fc15dcc0a6060c3
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    Dataset updated
    Aug 20, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    (by Joseph Kerski)This map is for use in the "What is the spatial pattern of demographic variables around the world?" activity in Section 1 of the Going Places with Spatial Analysiscourse. The map contains population characteristics by country for 2013.These data come from the Population Reference Bureau's 2014 World Population Data Sheet.The Population Reference Bureau (PRB) informs people around the world about population, health, and the environment, empowering them to use that information to advance the well-being of current and future generations.PRB analyzes complex demographic data and research to provide the most objective, accurate, and up-to-date population information in a format that is easily understood by advocates, journalists, and decision makers alike.The 2014 year's data sheet has detailed information on 16 population, health, and environment indicators for more than 200 countries. For infant mortality, total fertility rate, and life expectancy, we have included data from 1970 and 2013 to show change over time. This year's special data column is on carbon emissions.For more information about how PRB compiles its data, see: https://www.prb.org/

  16. d

    EJSCREEN Version 1, Demographic Data

    • catalog.data.gov
    • data.wu.ac.at
    Updated May 1, 2021
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    U.S. Environmental Protection Agency, Office of Policy (Point of Contact) (2021). EJSCREEN Version 1, Demographic Data [Dataset]. https://catalog.data.gov/ne/dataset/ejscreen-version-1-demographic-data
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    Dataset updated
    May 1, 2021
    Dataset provided by
    U.S. Environmental Protection Agency, Office of Policy (Point of Contact)
    Description

    This map service displays demographic data used in EJSCREEN. All demographic data were derived from American Community Survey 2006-2010 estimates. EJSCREEN is an environmental justice screening tool that provides EPA with a nationally consistent approach to screening for potential areas of EJ concern that may warrant further investigation. The EJ indexes are block group level results that combine multiple demographic factors with a single environmental variable (such as proximity to traffic) that can be used to help identify communities living with the greatest potential for negative environmental and health effects. The EJSCREEN tool is currently for internal EPA use only. It is anticipated that as users become accustomed to this new tool, individual programs within the Agency will develop program use guidelines and a community of practice will develop around them within the EPA Geoplatform. Users should keep in mind that screening tools are subject to substantial uncertainty in their demographic and environmental data, particularly when looking at small geographic areas, such as Census block groups. Data on the full range of environmental impacts and demographic factors in any given location are almost certainly not available directly through this tool, and its initial results should be supplemented with additional information and local knowledge before making any judgments about potential areas of EJ concern.

  17. BaselineDemographicSurveyaroundProposedJaitapurNuclearPowerPlantMaharashtraIndia.3.pdf...

    • figshare.com
    Updated Jun 1, 2023
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    Yojana Patil (2023). BaselineDemographicSurveyaroundProposedJaitapurNuclearPowerPlantMaharashtraIndia.3.pdf [Dataset]. http://doi.org/10.6084/m9.figshare.14174129.v2
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    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Yojana Patil
    License

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

    Description

    The present study deals with demographic survey around Jaitapur Nuclear Power Plant proposed site which comes in Ratnagiri and part of Sindhudurg District. Demography study is important for creating base line data. The study area includes 121 villages which come into 30 km radial range around JNPP. The present study focuses on the demographic characteristics and socio-economic conditions of this region. The household survey was carried out around the proposed project site

  18. a

    Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy

    • africageoportal.com
    Updated Aug 20, 2020
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    Africa GeoPortal (2020). Section 1, Exercise 1: Geography Matters: Analyzing Demographics-Copy-Copy [Dataset]. https://www.africageoportal.com/maps/ffd1b8a7ffbf4b758fc15dcc0a6060c3
    Explore at:
    Dataset updated
    Aug 20, 2020
    Dataset authored and provided by
    Africa GeoPortal
    Area covered
    Description

    (by Joseph Kerski)This map is for use in the "What is the spatial pattern of demographic variables around the world?" activity in Section 1 of the Going Places with Spatial Analysiscourse. The map contains population characteristics by country for 2013.These data come from the Population Reference Bureau's 2014 World Population Data Sheet.The Population Reference Bureau (PRB) informs people around the world about population, health, and the environment, empowering them to use that information to advance the well-being of current and future generations.PRB analyzes complex demographic data and research to provide the most objective, accurate, and up-to-date population information in a format that is easily understood by advocates, journalists, and decision makers alike.The 2014 year's data sheet has detailed information on 16 population, health, and environment indicators for more than 200 countries. For infant mortality, total fertility rate, and life expectancy, we have included data from 1970 and 2013 to show change over time. This year's special data column is on carbon emissions.For more information about how PRB compiles its data, see: https://www.prb.org/

  19. H

    Economic, demographic, and environmental metrics of countries (for 2021)

    • dataverse.harvard.edu
    Updated Mar 5, 2025
    + more versions
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    Work With Data (2025). Economic, demographic, and environmental metrics of countries (for 2021) [Dataset]. http://doi.org/10.7910/DVN/PGWRHK
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 5, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Work With Data
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The dataset contains economic, social, demographic, and environmental metrics for all countries in 2021. The cleaned and organised data comes from the World Bank and its open database.

  20. CDPHE Composite Socio-Demographic Dataset (County)

    • data.wu.ac.at
    • healthdata.gov
    • +1more
    csv, json, xml
    Updated Mar 31, 2017
    + more versions
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    Colorado Department of Public Health and Environment, American Community Survey (ACS) U.S. Census (2017). CDPHE Composite Socio-Demographic Dataset (County) [Dataset]. https://data.wu.ac.at/schema/data_colorado_gov/cmNzaC15NWs4
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    json, xml, csvAvailable download formats
    Dataset updated
    Mar 31, 2017
    Dataset provided by
    Colorado Department of Public Health and Environmenthttps://cdphe.colorado.gov/
    Description

    This county geography dataset includes selected indicators (2011-2015 5-Year Averages) pertaining to population, age, race/ethnicity, language, housing, poverty/income, education, disability, health insurance, employment, and age*race*gender groups. This dataset is assembled annually from the U.S. Census American Community Survey American Factfinder website and is maintained by the Colorado Department of Public Health and Environment.

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Statista (2025). Share of Gen Z improving environmental impact in the U.S. 2022, by demographic [Dataset]. https://www.statista.com/statistics/1356487/us-improving-environmental-impact-gen-z-by-demographic/
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Share of Gen Z improving environmental impact in the U.S. 2022, by demographic

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Dataset updated
Jun 27, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Oct 2021 - Jul 2022
Area covered
United States
Description

In a survey conducted from October 2021 to July 2022, respondents revealed that Gen Zers (or zoomers) cared about improving their environmental impact. Gen Zers who have attained a high education were those who found improving their environmental impact the most important, with **** percent stating they found it very important.

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