81 datasets found
  1. c

    Sidewalk to Street "Walkability" Ratio

    • s.cnmilf.com
    • gimi9.com
    • +1more
    Updated Jan 24, 2023
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    Western Pennsylvania Regional Data Center (2023). Sidewalk to Street "Walkability" Ratio [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/sidewalk-to-street-walkability-ratio
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    Dataset updated
    Jan 24, 2023
    Dataset provided by
    Western Pennsylvania Regional Data Center
    Description

    We’ve been asked to create measures of communities that are “walkable” for several projects. While there is no standard definition of what makes a community “walkable”, and the definition of “walkability” can differ from person to person, we thought an indicator that explores the total length of available sidewalks relative to the total length of streets in a community could be a good place to start. In this blog post, we describe how we used open data from SPC and Allegheny County to create a new measure for how “walkable” a community is. We wanted to create a ratio of the length of a community’s sidewalks to the length of a community’s streets as a measure of pedestrian infrastructure. A ratio of 1 would mean that a community has an equal number of linear feet of sidewalks and streets. A ratio of about 2 would mean that a community has two linear feet of sidewalk for every linear foot of street. In other words, every street has a sidewalk on either side of it. In creating a measure of the ratio of streets to sidewalks, we had to do a little bit of data cleanup. Much of this was by trial and error, ground-truthing the data based on our personal experiences walking in different neighborhoods. Since street data was not shared as open data by many counties in our region either on PASDA or through the SPC open data portal, we limited our analysis of “walkability” to Allegheny County. In looking at the sidewalk data table and map, we noticed that trails were included. While nice to have in the data, we wanted to exclude these two features from the ratio. We did this to avoid a situation where a community that had few sidewalks but was in the same blockgroup as a park with trails would get “credit” for being more “walkable” than it actually is according to our definition. We did this by removing all segments where “Trail” was in the “Type_Name” field. We also used a similar tabular selection method to remove crosswalks from the sidewalk data “Type_Name”=”Crosswalk.” We kept the steps in the dataset along with the sidewalks. In the street data obtained from Allegheny County’s GIS department, we felt like we should try to exclude limited-access highway segments from the analysis, since pedestrians are prohibited from using them, and their presence would have reduced the sidewalk/street ratio in communities where they are located. We did this by excluding street segments whose values in the “FCC” field (designating type of street) equaled “A11” or “A63.” We also removed trails from this dataset by excluding those classified as “H10.” Since documentation was sparse, we looked to see how these features were classified in the data to determine which codes to exclude. After running the data initially, we also realized that excluding alleyways from the calculations also could improve the accuracy of our results. Some of the communities with substantial pedestrian infrastructure have alleyways, and including them would make them appear to be less-”walkable” in our indicator. We removed these from the dataset by removing records with a value of “Aly” or “Way” in the “St_Type” field. We also excluded streets where the word “Alley” appeared in the street name, or “St_Name” field. The full methodology used for this dataset is captured in our blog post, and we have also included the sidewalk and street data used to create the ratio here as well.

  2. d

    Market Sale Ratio

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Mar 18, 2023
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    County of Fairfax (2023). Market Sale Ratio [Dataset]. https://catalog.data.gov/dataset/market-sale-ratio-1774f
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    Dataset updated
    Mar 18, 2023
    Dataset provided by
    County of Fairfax
    Description

    Residential market value estimates and most recent sales values for owned properties at a parcel level within Fairfax County as of the VALID_TO date in the attribute table. For methodology and a data dictionary please view the IPLS data dictionary

  3. d

    CPS2 Maximum Bonus Plot Ratio Plan - Datasets - data.wa.gov.au

    • catalogue.data.wa.gov.au
    Updated May 15, 2020
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    (2020). CPS2 Maximum Bonus Plot Ratio Plan - Datasets - data.wa.gov.au [Dataset]. https://catalogue.data.wa.gov.au/dataset/perth-cps2-maximum-bonus-plot-ratio-plan
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    Dataset updated
    May 15, 2020
    License

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

    Area covered
    Western Australia
    Description

    This dataset contains spatial boundaries for Bonus Plot Ratio Plans relating to the City of Perth Planning Scheme No.2The Maximum Bonus Plot Ratio Plan shows the total maximum bonus plot ratio that can be granted on a specific lot. This is either 20% or 50%.Bonus plot ratio may be granted under a single category or a combination of Special Residential, Residential, Heritage and Public Facilities.Definition under Schedule 4 “means the maximum percentage increase in the maximum plot ratio which is specified for a lot or part of a lot by the Maximum Bonus Plot Ratio Plan”;Please see https://perth.wa.gov.au/develop/planning-framework/planning-schemes and https://perth.wa.gov.au/develop/planning-framework/planning-policies-and-precinct-plans for more information regarding the City of Perth Planning Schemes.

  4. d

    Replication Data for The Saliency of CEO Pay Ratio

    • dataone.org
    • search.dataone.org
    Updated Dec 16, 2023
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    White, Joshua; Boone, Audra; Starkweather, Austin (2023). Replication Data for The Saliency of CEO Pay Ratio [Dataset]. https://dataone.org/datasets/sha256%3Af5399f0ccc756d38b8f8f09c95f5d50ee763f6210d7ab293f4807d394e58ff9a
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    Dataset updated
    Dec 16, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    White, Joshua; Boone, Audra; Starkweather, Austin
    Description

    Contains compressed file, "Replication Files - The Saliency of CEO Pay Ratio.zip", which contains Stata code, Stata log file of the analysis, Stata pseudo-datasets (to demonstrate format of data), and a data dictionary for “The Saliency of the CEO Pay Ratio.” Review of Finance, forthcoming.

  5. e

    90/10 decile ratio of equivalised income

    • data.europa.eu
    excel xls
    Updated Feb 6, 2022
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    Ministerium für Schule und Bildung des Landes NRW (2022). 90/10 decile ratio of equivalised income [Dataset]. https://data.europa.eu/data/datasets/9dc70859-8195-5ddc-858a-b1a71a3015b7?locale=en
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    excel xlsAvailable download formats
    Dataset updated
    Feb 6, 2022
    Dataset authored and provided by
    Ministerium für Schule und Bildung des Landes NRW
    License

    Data licence Germany – Attribution – Version 2.0https://www.govdata.de/dl-de/by-2-0
    License information was derived automatically

    Description

    Definition: The 90/10 decile ratio is a measure of the inequality of distribution. It is determined here in relation to the distribution of equivalised income. It sets the lower limit of the equivalised income of the highest-income decile (= upper limit of the 9. The ratio of the equivalised income of the lowest-income decile. Equivalised income is a weighted per capita income per household member, which is calculated by dividing household net income by the sum of the household weights of persons living in the household. The head of the household is assigned the weight = 1, for the other household members weights of < 1 are used because it is assumed that savings can be achieved through joint management. The new OECD scale is used as a scale of equivalence to determine the respective weights. After that, the head of household is assigned a weight of 1, other household members aged 14 or more a weight of 0.5 and household members under the age of 14 are assigned a weight of 0.3. In order to form the income decile, all persons are sorted according to the level of equivalised income and divided into ten equal groups. The first decile contains the 10 percent with the lowest, the tenth with the highest equivalised income.

    Data source:
    IT.NRW, Microcensus

  6. c

    4.09 Housing Inventory Ratio (dashboard)

    • s.cnmilf.com
    • data.tempe.gov
    • +1more
    Updated Mar 18, 2023
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    City of Tempe (2023). 4.09 Housing Inventory Ratio (dashboard) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/4-09-housing-inventory-ratio-dashboard-1cb98
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    Dataset updated
    Mar 18, 2023
    Dataset provided by
    City of Tempe
    Description

    This operations dashboard shows historic and current data related to this performance measure.The performance measure dashboard is available at 4.09 Housing Inventory Ratio. Data Dictionary

  7. Age Dependency Ratio

    • hub.arcgis.com
    Updated Jan 11, 2012
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    Esri U.S. Federal Datasets (2012). Age Dependency Ratio [Dataset]. https://hub.arcgis.com/datasets/5b39485c49c44e6b84af126478a4930f
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    Dataset updated
    Jan 11, 2012
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
    1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
    Population is based on the de facto definition of population, which
    counts all residents regardless of legal status or citizenship--except
    for refugees not permanently settled in the country of asylum, who are
    generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: Life expectancy at birth indicates the number of years a newborn infant
    would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

  8. V

    Virginia Ratio of Income to Poverty Level by Census Block Group (ACS 5-Year)...

    • data.virginia.gov
    csv
    Updated Jan 3, 2025
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    Office of INTERMODAL Planning and Investment (2025). Virginia Ratio of Income to Poverty Level by Census Block Group (ACS 5-Year) [Dataset]. https://data.virginia.gov/bs/dataset/activity/virginia-ratio-of-income-to-poverty-level-by-census-block-group-acs-5-year
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    csv(9463413)Available download formats
    Dataset updated
    Jan 3, 2025
    Dataset authored and provided by
    Office of INTERMODAL Planning and Investment
    Area covered
    Virginia
    Description

    2013-2023 Virginia Ratio of Income to Poverty Level in the Past 12 Months by Census Block Group. Contains estimates and margins of error.

    U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table C17002 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

    The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

    Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties.

    Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

  9. Data from: Data of the characterisation of conventional 87Sr/86Sr isotope...

    • zenodo.org
    • data.niaid.nih.gov
    bin, pdf
    Updated Jul 12, 2024
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    Anera Kazlagić; Martin Rosner; Anna Cipriani; Daniel A. Frick; Johannes Glodny; Elis J. Hoffmann; John M. Hora; Johanna Irrgeher; Federico Lugli; Thomas Magna; Thomas C. Meisel; Anette Meixner; Antonio Possolo; Axel Pramann; Michael J. Pribil; Thomas Prohaska; Anika Retzmann; Olaf Rienitz; Daniel Rutherford; Gustavo M. Paula-Santos; Michael Tatzel; Sara Widhalm; Matthias Willbold; Tea Zuliani; Jochen Vogl; Jochen Vogl; Anera Kazlagić; Martin Rosner; Anna Cipriani; Daniel A. Frick; Johannes Glodny; Elis J. Hoffmann; John M. Hora; Johanna Irrgeher; Federico Lugli; Thomas Magna; Thomas C. Meisel; Anette Meixner; Antonio Possolo; Axel Pramann; Michael J. Pribil; Thomas Prohaska; Anika Retzmann; Olaf Rienitz; Daniel Rutherford; Gustavo M. Paula-Santos; Michael Tatzel; Sara Widhalm; Matthias Willbold; Tea Zuliani (2024). Data of the characterisation of conventional 87Sr/86Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study [Dataset]. http://doi.org/10.5281/zenodo.7804445
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    pdf, binAvailable download formats
    Dataset updated
    Jul 12, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Anera Kazlagić; Martin Rosner; Anna Cipriani; Daniel A. Frick; Johannes Glodny; Elis J. Hoffmann; John M. Hora; Johanna Irrgeher; Federico Lugli; Thomas Magna; Thomas C. Meisel; Anette Meixner; Antonio Possolo; Axel Pramann; Michael J. Pribil; Thomas Prohaska; Anika Retzmann; Olaf Rienitz; Daniel Rutherford; Gustavo M. Paula-Santos; Michael Tatzel; Sara Widhalm; Matthias Willbold; Tea Zuliani; Jochen Vogl; Jochen Vogl; Anera Kazlagić; Martin Rosner; Anna Cipriani; Daniel A. Frick; Johannes Glodny; Elis J. Hoffmann; John M. Hora; Johanna Irrgeher; Federico Lugli; Thomas Magna; Thomas C. Meisel; Anette Meixner; Antonio Possolo; Axel Pramann; Michael J. Pribil; Thomas Prohaska; Anika Retzmann; Olaf Rienitz; Daniel Rutherford; Gustavo M. Paula-Santos; Michael Tatzel; Sara Widhalm; Matthias Willbold; Tea Zuliani
    License

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

    Description

    This dataset represents the electronic supplementary material (ESM) of the publication entitled "Characterisation of conventional 87Sr/86Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study", which is published in Geostandards and Geoanalytical Research under the DOI: 10.1111/GGR.12517. It consists of four files. 'ESM_Data.xlsx' contains all reported data of the participants, a description of the applied analytical procedures, basic calculations, the consensus values, and part of the uncertainty assessment. 'ESM_Figure-S1' displays a schematic on how measurements, sequences and replicates are treated for the uncertainty calculation carried out by PTB. 'ESM_Technical-protocol.pdf' is the technical protocol of the interlaboratory comparison, which has been provided to all participants together with the samples and which contains bedside others the definition of the measurand and guidelines for data assessment and calculations. 'ESM_Reporting-template.xlsx' is the Excel template which has been submitted to all participants for reporting their results within the interlaboratory comparison. Excel files with names of the the structure 'GeoReM_Material_Sr8786_Date.xlsx' represent the Rcon(87Sr/86Sr) data for a specific reference material downloaded from GeoReM at the specified date, e.g. 'GeoReM_IAPSO_Sr8786_20221115.xlsx' contains all Rcon(87Sr/86Sr) data for the IAPSO seawater standard listed in GeoReM until 15 November 2022.

  10. S

    South Korea Non Performing Loans Ratio

    • ceicdata.com
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    CEICdata.com, South Korea Non Performing Loans Ratio [Dataset]. https://www.ceicdata.com/en/indicator/korea/non-performing-loans-ratio
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    Dataset provided by
    CEICdata.com
    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, 2021 - Sep 1, 2024
    Area covered
    South Korea
    Variables measured
    Loans
    Description

    Key information about South Korea Non Performing Loans Ratio

    • South Korea Non Performing Loans Ratio stood at 0.4 % in Sep 2024, compared with the ratio of 0.4 % in the previous quarter
    • South Korea Non Performing Loans Ratio data is updated quarterly, available from Jun 2001 to Sep 2024
    • The data reached an all-time high of 3.5 % in Jun 2001 and a record low of 0.3 % in Sep 2023

    Financial Supervisory Service provides quarterly Non Performing Loans Ratio. Non Performing Loans are defined as summation of Loans overdue for more than 3 months with Non Accrual Loans. [COVID-19-IMPACT]


    Further information about South Korea Non Performing Loans Ratio

    • In the latest reports, Money Supply M2 in South Korea increased 6.2 % YoY in Nov 2024
    • South Korea Foreign Exchange Reserves was measured at 387.3 USD bn in Jan 2025
    • The Foreign Exchange Reserves equaled 7.6 Months of Import in Jan 2025
    • The country's Domestic Credit reached 3,443.0 USD bn in Nov 2024, representing an increased of 5.0 % YoY
    • Household Debt of South Korea reached 1,742.9 USD bn in Mar 2023, accounting for 93.7 % of the country's Nominal GDP

  11. d

    CPS2 Plot Ratio Plan - Datasets - data.wa.gov.au

    • catalogue.data.wa.gov.au
    Updated May 18, 2020
    + more versions
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    (2020). CPS2 Plot Ratio Plan - Datasets - data.wa.gov.au [Dataset]. https://catalogue.data.wa.gov.au/dataset/perth-cps2-plot-ratio-plan
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    Dataset updated
    May 18, 2020
    License

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

    Area covered
    Western Australia
    Description

    This dataset contains spatial boundaries for Plot Ratio Plans relating to the City of Perth Planning Scheme No.2The Plot Ratio Plan determines the development potential on each lot under the City of Perth's planning authority.Plot ratio is written as a ratio i.e. a site of 1000msq with a plot ratio of 6:1 can develop a maximum of 6000msq of floor space. Therefore the higher the plot ratio of a site the greater its development potential.Definition under Schedule 4 “Plot ratio means the ratio of the floor area of a building to the area of land within the boundaries of the lots on which that building is located;”Please see https://perth.wa.gov.au/develop/planning-framework/planning-schemes and https://perth.wa.gov.au/develop/planning-framework/planning-policies-and-precinct-plans for more information regarding the City of Perth Planning Schemes.

  12. J

    Jamaica JM: External Debt: DOD: Stocks: Concessional

    • ceicdata.com
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    CEICdata.com, Jamaica JM: External Debt: DOD: Stocks: Concessional [Dataset]. https://www.ceicdata.com/en/jamaica/external-debt-debt-outstanding-debt-ratio-and-debt-service/jm-external-debt-dod-stocks-concessional
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    Dataset provided by
    CEICdata.com
    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, 2005 - Dec 1, 2016
    Area covered
    Jamaica
    Variables measured
    External Debt
    Description

    Jamaica JM: External Debt: DOD: Stocks: Concessional data was reported at 1.061 USD bn in 2016. This records a decrease from the previous number of 1.129 USD bn for 2015. Jamaica JM: External Debt: DOD: Stocks: Concessional data is updated yearly, averaging 1.061 USD bn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 1.636 USD bn in 1995 and a record low of 19.205 USD mn in 1970. Jamaica JM: External Debt: DOD: Stocks: Concessional data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank: External Debt: Debt Outstanding, Debt Ratio and Debt Service. Concessional external debt conveys information about the borrower's receipt of aid from official lenders at concessional terms as defined by the Development Assistance Committee (DAC) of the OECD. Concessional debt is defined as loans with an original grant element of 25 percent or more. The grant element of a loan is the grant equivalent expressed as a percentage of the amount committed. It is used as a measure of the overall cost of borrowing. The grant equivalent of a loan is its commitment (present) value, less the discounted present value of its contractual debt service; conventionally, future service payments are discounted at 10 percent. Loans from major regional development banks--African Development Bank, Asian Development Bank, and the Inter-American Development Bank--and from the World Bank are classified as concessional according to each institution's classification and not according to the DAC definition, as was the practice in earlier reports. Long-term debt outstanding and disbursed is the total outstanding long-term debt at year end. Long-term external debt is defined as debt that has an original or extended maturity of more than one year and that is owed to nonresidents and repayable in currency, goods, or services. Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

  13. World Bank - Age and Population

    • hub.arcgis.com
    Updated Jan 11, 2012
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    Esri U.S. Federal Datasets (2012). World Bank - Age and Population [Dataset]. https://hub.arcgis.com/datasets/5b39485c49c44e6b84af126478a4930f_2/data?geometry=-180%2C-89.982%2C180%2C62.747
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    Dataset updated
    Jan 11, 2012
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    This map service, derived from World Bank data, shows various characteristics of the Health topic. The World Bank Group provides financing, state-of-the-art analysis, and policy advice to help countries expand access to quality, affordable health care; protects people from falling into poverty or worsening poverty due to illness; and promotes investments in all sectors that form the foundation of healthy societies.Age Dependency Ratio: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Age Dependency Ratio Old: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population. Data from 1960 – 2012.Birth/Death Rate: Crude birth/death rate indicates the number of births/deaths occurring during the year, per
    1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Data spans from 1960 – 2008.Total Fertility: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Data shown is for 1960 - 2008.Population Growth: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage.
    Population is based on the de facto definition of population, which
    counts all residents regardless of legal status or citizenship--except
    for refugees not permanently settled in the country of asylum, who are
    generally considered part of the population of the country of origin. Data spans from 1960 – 2009.Life Expectancy: Life expectancy at birth indicates the number of years a newborn infant
    would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Data spans from 1960 – 2008.Population Female: Female population is the percentage of the population that is female. Population is based on the de facto definition of population. Data from 1960 – 2009.For more information, please visit: World Bank Open Data. _Other International User Community content that may interest you World Bank World Bank Age World Bank Health

  14. Ratio of new immigrant arrivals (2001 – 2016) to older immigrant arrivals...

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +2more
    esri rest, fgdb/gdb +3
    Updated Jan 31, 2022
    + more versions
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    Statistics Canada (2022). Ratio of new immigrant arrivals (2001 – 2016) to older immigrant arrivals (before 2001) by census subdivision, 2016 [Dataset]. https://open.canada.ca/data/en/dataset/f2d07de2-9c7b-4848-ba87-ab7fa5fcace9
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    html, wms, esri rest, fgdb/gdb, mxdAvailable download formats
    Dataset updated
    Jan 31, 2022
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Jan 1, 2016
    Description

    This service shows the ratio of immigrants who arrived between 2001 and 2016 to immigrants who arrived before 2001, by census subdivision, 2016. The data is a custom extraction from the 2016 Census - 25% sample data. This data pertains to persons in private households who are immigrants by their period of immigration. 'Immigrant' includes persons who are, or who have ever been, landed immigrants or permanent residents. Such persons have been granted the right to live in Canada permanently by immigration authorities. Immigrants who have obtained Canadian citizenship by naturalization are included in this category. In the 2016 Census of Population, 'Immigrant' includes immigrants who landed in Canada on or prior to May 10, 2016. 'Period of immigration' refers to the period in which the immigrant first obtained landed immigrant or permanent resident status. For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'. For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

  15. L

    Laos Non Performing Loans Ratio

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Laos Non Performing Loans Ratio [Dataset]. https://www.ceicdata.com/en/indicator/laos/non-performing-loans-ratio
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    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, 2021 - Sep 1, 2024
    Area covered
    Laos
    Description

    Key information about Laos Non Performing Loans Ratio

    • Laos Non Performing Loans Ratio stood at 1.8 % in Sep 2024, compared with the ratio of 1.9 % in the previous quarter
    • Laos Non Performing Loans Ratio data is updated quarterly, available from Dec 2017 to Sep 2024
    • The data reached an all-time high of 3.2 % in Jun 2020 and a record low of 1.4 % in Dec 2023

    The Bank of the Lao PDR provides quarterly Non Performing Loans Ratio. Non Performing Loans are defined as loans overdue for more than 90 days

  16. Price-to-rent ratio in selected countries worldwide 2024

    • statista.com
    • flwrdeptvarieties.store
    Updated Jan 28, 2025
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    Statista (2025). Price-to-rent ratio in selected countries worldwide 2024 [Dataset]. https://www.statista.com/statistics/458543/price-to-income-ratio-of-housing-worldwide/
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    Dataset updated
    Jan 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Turkey, Russia, Portugal, and Latvia were the countries with the highest house price-to-rent-ratio in the ranking in the second quarter of 2024. In all three countries, the ratio exceeded 160 index points, meaning that house price growth had outpaced rents by over 60 percent between 2015 and 2024. What does the house-price-to-rent ratio show? The house-price-to-rent-ratio measures the evolution of house prices compared to rents. It is generally calculated by dividing the median house price by the median annual rent. In this statistic, the values have been normalized with 100 equaling the 2015 ratio. Consequentially, a value under 100 means that rental rates have risen more than house prices. When all OECD countries are considered as a whole, the gap between house prices and rents was wider than in the Euro area. Measures of housing affordability The national house-price-to-rent ratio may not fully reflect the cost of housing in a particular country, as it does not capture the price variations that can exist between different regions. It also does not take into consideration the relationship between incomes and housing costs, which is measured by the house-price-to-income and household-rent-to-income ratios. Taking both these factors into account uncovers vast differences in housing affordability between different regions and different professions.

  17. J

    Japan JP: Employment Coefficient

    • ceicdata.com
    Updated Jan 15, 2025
    + more versions
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    CEICdata.com (2025). Japan JP: Employment Coefficient [Dataset]. https://www.ceicdata.com/en/japan/employment-and-unemployment-forecast-oecd-member-annual/jp-employment-coefficient
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    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, 2015 - Dec 1, 2026
    Area covered
    Japan
    Variables measured
    Unemployment
    Description

    Japan JP: Employment Coefficient data was reported at 1.000 Ratio in 2026. This stayed constant from the previous number of 1.000 Ratio for 2025. Japan JP: Employment Coefficient data is updated yearly, averaging 1.000 Ratio from Dec 1985 (Median) to 2026, with 42 observations. The data reached an all-time high of 1.000 Ratio in 2026 and a record low of 1.000 Ratio in 2026. Japan JP: Employment Coefficient data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Employment and Unemployment: Forecast: OECD Member: Annual. CLF-Employment coefficient ratio of total employment, SNA definition to LFS definition OECD calculation, see OECD Economic Outlook database documentation

  18. T

    Togo TG: External Debt: DOD: Stocks: Concessional

    • ceicdata.com
    Updated Feb 6, 2021
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    CEICdata.com (2021). Togo TG: External Debt: DOD: Stocks: Concessional [Dataset]. https://www.ceicdata.com/en/togo/external-debt-debt-outstanding-debt-ratio-and-debt-service/tg-external-debt-dod-stocks-concessional
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    Dataset updated
    Feb 6, 2021
    Dataset provided by
    CEICdata.com
    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, 2005 - Dec 1, 2016
    Area covered
    Togo
    Description

    Togo TG: External Debt: DOD: Stocks: Concessional data was reported at 828.617 USD mn in 2016. This records an increase from the previous number of 698.505 USD mn for 2015. Togo TG: External Debt: DOD: Stocks: Concessional data is updated yearly, averaging 590.477 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 1.280 USD bn in 2009 and a record low of 31.396 USD mn in 1970. Togo TG: External Debt: DOD: Stocks: Concessional data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Togo – Table TG.World Bank: External Debt: Debt Outstanding, Debt Ratio and Debt Service. Concessional external debt conveys information about the borrower's receipt of aid from official lenders at concessional terms as defined by the Development Assistance Committee (DAC) of the OECD. Concessional debt is defined as loans with an original grant element of 25 percent or more. The grant element of a loan is the grant equivalent expressed as a percentage of the amount committed. It is used as a measure of the overall cost of borrowing. The grant equivalent of a loan is its commitment (present) value, less the discounted present value of its contractual debt service; conventionally, future service payments are discounted at 10 percent. Loans from major regional development banks--African Development Bank, Asian Development Bank, and the Inter-American Development Bank--and from the World Bank are classified as concessional according to each institution's classification and not according to the DAC definition, as was the practice in earlier reports. Long-term debt outstanding and disbursed is the total outstanding long-term debt at year end. Long-term external debt is defined as debt that has an original or extended maturity of more than one year and that is owed to nonresidents and repayable in currency, goods, or services. Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

  19. d

    Compendium – Mortality from potentially avoidable or amenable causes

    • digital.nhs.uk
    csv, xls
    Updated Jul 21, 2022
    + more versions
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    (2022). Compendium – Mortality from potentially avoidable or amenable causes [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-mortality/current/mortality-from-potentially-avoidable-or-amenable-causes
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    csv(3.3 MB), xls(606.1 kB)Available download formats
    Dataset updated
    Jul 21, 2022
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 1995 - Dec 31, 2020
    Description

    Mortality from causes considered amenable to health care (see “Numerator data” in the indicator specification for definition). As from the November 2005 Compendium release this indicator is one of three indicators that replace the ‘mortality from potentially avoidable causes’ indicator published in previous Compendia. To help reduce deaths from causes considered amenable to health care. Causes of death are included if there is evidence that they are amenable to healthcare interventions and – given timely, appropriate, and high quality care – death rates should be low among the age groups specified. Healthcare intervention includes preventing disease onset as well as treating disease. Two additional indicators are provided: ‘mortality from causes considered amenable to health care (exc Ischaemic heart disease)’ and ‘mortality from causes other than those considered amenable to health care’. The difference between amenable and non-amenable causes in their trends over time may provide evidence of the increasing (or decreasing) effectiveness of health care. Legacy unique identifier: P00364

  20. SORCE SOLSTICE Level 3 MgII Core-to-Wing Ratio 24 Hour Means V018...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Dec 7, 2023
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    SORCE SOLSTICE Level 3 MgII Core-to-Wing Ratio 24 Hour Means V018 (SOR3SOLD_MGII_018) at GES DISC [Dataset]. https://catalog.data.gov/dataset/sorce-solstice-level-3-mgii-core-to-wing-ratio-24-hour-means-v018-sor3sold-mgii-018-at-ges
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    Dataset updated
    Dec 7, 2023
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The SORCE SOLSTICE Level 3 MgII Core to Wing Ratio 24 Hour Means product consists of daily averages of the magnesium II core-to-wing index from the SOLSTICE instrument. The SOLSTICE instrument makes measurements during each daytime orbit portion, 15 orbits per day. This product has solar spectra averaged for a day. The spectral resolution of SOLSTICE is 0.1 nm, allowing the Mg-II doublet to be fully resolved and modeled with Gaussians. The Mg-II core-to-wing ratio is used as a measurement of solar activity. The Mg-II data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date (calendar and Julian Day), the core/wing ratio, and the absolute uncertainty. The rows are arranged with one daily average measurment, repeating for each day for the length of the measurement period.

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Western Pennsylvania Regional Data Center (2023). Sidewalk to Street "Walkability" Ratio [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/sidewalk-to-street-walkability-ratio

Sidewalk to Street "Walkability" Ratio

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Dataset updated
Jan 24, 2023
Dataset provided by
Western Pennsylvania Regional Data Center
Description

We’ve been asked to create measures of communities that are “walkable” for several projects. While there is no standard definition of what makes a community “walkable”, and the definition of “walkability” can differ from person to person, we thought an indicator that explores the total length of available sidewalks relative to the total length of streets in a community could be a good place to start. In this blog post, we describe how we used open data from SPC and Allegheny County to create a new measure for how “walkable” a community is. We wanted to create a ratio of the length of a community’s sidewalks to the length of a community’s streets as a measure of pedestrian infrastructure. A ratio of 1 would mean that a community has an equal number of linear feet of sidewalks and streets. A ratio of about 2 would mean that a community has two linear feet of sidewalk for every linear foot of street. In other words, every street has a sidewalk on either side of it. In creating a measure of the ratio of streets to sidewalks, we had to do a little bit of data cleanup. Much of this was by trial and error, ground-truthing the data based on our personal experiences walking in different neighborhoods. Since street data was not shared as open data by many counties in our region either on PASDA or through the SPC open data portal, we limited our analysis of “walkability” to Allegheny County. In looking at the sidewalk data table and map, we noticed that trails were included. While nice to have in the data, we wanted to exclude these two features from the ratio. We did this to avoid a situation where a community that had few sidewalks but was in the same blockgroup as a park with trails would get “credit” for being more “walkable” than it actually is according to our definition. We did this by removing all segments where “Trail” was in the “Type_Name” field. We also used a similar tabular selection method to remove crosswalks from the sidewalk data “Type_Name”=”Crosswalk.” We kept the steps in the dataset along with the sidewalks. In the street data obtained from Allegheny County’s GIS department, we felt like we should try to exclude limited-access highway segments from the analysis, since pedestrians are prohibited from using them, and their presence would have reduced the sidewalk/street ratio in communities where they are located. We did this by excluding street segments whose values in the “FCC” field (designating type of street) equaled “A11” or “A63.” We also removed trails from this dataset by excluding those classified as “H10.” Since documentation was sparse, we looked to see how these features were classified in the data to determine which codes to exclude. After running the data initially, we also realized that excluding alleyways from the calculations also could improve the accuracy of our results. Some of the communities with substantial pedestrian infrastructure have alleyways, and including them would make them appear to be less-”walkable” in our indicator. We removed these from the dataset by removing records with a value of “Aly” or “Way” in the “St_Type” field. We also excluded streets where the word “Alley” appeared in the street name, or “St_Name” field. The full methodology used for this dataset is captured in our blog post, and we have also included the sidewalk and street data used to create the ratio here as well.

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