100+ datasets found
  1. National Energy Efficiency Data-Framework (NEED) report: summary of analysis...

    • gov.uk
    • s3.amazonaws.com
    Updated Aug 11, 2023
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    Department for Business, Energy & Industrial Strategy (2023). National Energy Efficiency Data-Framework (NEED) report: summary of analysis 2021 [Dataset]. https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-report-summary-of-analysis-2021
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    Dataset updated
    Aug 11, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Business, Energy & Industrial Strategy
    Description

    The National Energy Efficiency Data-Framework (NEED) was set up to provide a better understanding of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. The data framework matches data about a property together - including energy consumption and energy efficiency measures installed - at household level.

    11 August 2023 Error notice: revisions to the June 2021 Domestic NEED annual report

    We identified 2 processing errors in this edition of the Domestic NEED Annual report and corrected them. The changes are small and do not affect the overall findings of the report, only the domestic energy consumption estimates. The revisions are summarised here:

    Error 1: Local authority consumption estimates

    Error 2: Some properties incorrectly excluded from the Scotland multiple attributes tables

    • Extent of the error: These corrections primarily affect the number in sample column for all years as some properties were incorrectly excluded from the consumption estimates. There have also been revisions to the mean, median, upper and lower quartiles. Using 2019 as an example, around 80% of the updated mean and median values are within 300 kWh of what was previously published.
    • Years affected: 2017-2019
    • Countries affected: Scotland
    • Data tables affected: Multiple attributes tables: Scotland, 2019 (all tables)

    4 August 2021 Error notice: revisions to the June 2021 Domestic NEED annual report

    We identified 2 processing errors in this edition of the Domestic NEED Annual report and corrected them. The changes are small and do not affect the overall findings of the report, only the domestic energy consumption estimates. The impact of energy efficiency measures analysis remains unchanged. The revisions are summarised here:

    Error 1: Some properties incorrectly excluded from the 2019 gas consumption estimates

  2. National Energy Efficiency Data-Framework (NEED): impact of measures data...

    • gov.uk
    Updated Jun 27, 2024
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    Department for Energy Security and Net Zero (2024). National Energy Efficiency Data-Framework (NEED): impact of measures data tables 2024 [Dataset]. https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-impact-of-measures-data-tables-2024
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    Dataset updated
    Jun 27, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Energy Security and Net Zero
    Description

    Data tables for impact of measures analysis which assess the impact of installing home efficiency measures such as loft insulation on household energy consumption.

  3. Dataset: Gold standard dataset for explainability need detection in app...

    • zenodo.org
    zip
    Updated May 20, 2025
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    Martin Obaidi; Martin Obaidi (2025). Dataset: Gold standard dataset for explainability need detection in app reviews. [Dataset]. http://doi.org/10.5281/zenodo.13273192
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    zipAvailable download formats
    Dataset updated
    May 20, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Martin Obaidi; Martin Obaidi
    License

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

    Description

    We crawled 90,000 app reviews from both Google Play Store and Apple App Store, including reviews from both free and paid apps. These reviews were filtered for explainability needs, and after this process, 4,495 reviews remained. Among them, 2,185 reviews indicated an explanation need, while 2,310 did not. This resulting gold standard dataset was used to train and evaluate several machine learning models and rule-based approaches for detecting explanation needs in app reviews.

    The dataset includes both balanced and unbalanced evaluation sets, as well as the original crawled data from October 2023. In addition to machine learning approaches, rule-based methods optimized for F1 score, precision, and recall are also included.

    We provide several pre-trained machine learning models (including BERT, SetFit, AdaBoost, K-Nearest Neighbor, Logistic Regression, Naive Bayes, Random Forest, and SVM) along with training scripts and evaluation notebooks. These models can be applied directly or retrained using the included datasets.

    For further details on the structure and usage of the dataset, please refer to the README.md file within the provided ZIP archive.

  4. National Energy Efficiency Data-Framework (NEED): consumption data tables...

    • gov.uk
    Updated Jun 25, 2020
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    Department for Business, Energy & Industrial Strategy (2020). National Energy Efficiency Data-Framework (NEED): consumption data tables 2020 [Dataset]. https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-consumption-data-tables
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    Dataset updated
    Jun 25, 2020
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Business, Energy & Industrial Strategy
    Description

    Data includes consumption for a range of property characteristics such as age and type, as well as a range of household characteristics such as the number of adults and household income.

    The content covers:

    • headline consumption tables England and Wales: summary statistics on electricity and gas consumption for properties in England and Wales, broken down by various property and household characteristics
    • additional consumption tables England and Wales: detailed statistics on electricity and gas consumption for properties in England and Wales
    • local authority tables: mean and median gas and electricity consumption for each local authority in England and Wales, including number in sample, attributes, and characteristics such as floor area, number of bedrooms and property age
    • multiple attributes table: table giving summary consumption statistics by different combinations of property and household characteristics
    • headline consumption tables Scotland: summary statistics on electricity and gas consumption for properties in Scotland, broken down by various property and household characteristics
    • additional consumption tables Scotland: detailed statistics on electricity and gas consumption for properties in Scotland
    • Scotland only multiple attributes table - new in 2020
  5. Characteristics of children in need: 2015 to 2016

    • gov.uk
    Updated Mar 23, 2017
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    Department for Education (2017). Characteristics of children in need: 2015 to 2016 [Dataset]. https://www.gov.uk/government/statistics/characteristics-of-children-in-need-2015-to-2016
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    Dataset updated
    Mar 23, 2017
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Description

    This statistical first release (SFR) includes information on:

    • children in need of social services
    • children referred to social services
    • assessments undertaken and primary need at first assessment
    • section 47 enquiries (a local authority carries out one of these if they suspect a child is suffering, or likely to suffer, significant harm) and initial child protection conferences
    • children who were the subject of a child protection plan

    It is based on child-level data collected via the children in need census.

    The outcomes tables show figures that result from matching the children in need census to the national pupil database (NPD). These tables show children in need by:

    • free school meals (FSM)
    • special educational needs (SEN)
    • attainment
    • absence
    • exclusions

    The outcomes methodology document explains the matching process and calculations used in these tables.

    Children’s services statistics team - CIN

    Email mailto:CIN.Stats@education.gov.uk">CIN.Stats@education.gov.uk

    Telephone: Chris Gray 01325 340854

  6. Core housing need, by tenure including first-time homebuyer and social and...

    • ouvert.canada.ca
    • canwin-datahub.ad.umanitoba.ca
    • +4more
    csv, html, xml
    Updated Sep 10, 2024
    + more versions
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    Statistics Canada (2024). Core housing need, by tenure including first-time homebuyer and social and affordable housing status, inactive [Dataset]. https://ouvert.canada.ca/data/dataset/fa471d0c-6290-4de2-9f49-6825c90cbb2b
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    html, csv, xmlAvailable download formats
    Dataset updated
    Sep 10, 2024
    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

    Description

    Core housing need, by tenure including first-time homebuyer and social and affordable housing status, Canada, provinces and territories, populations centres, select census metropolitan areas (CMAs) and census agglomerations (CAs).

  7. Reaching Those in Need: Estimates of USDA's SNAP Program Participation Rates...

    • catalog.data.gov
    Updated May 8, 2025
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    Food and Nutrition Service (2025). Reaching Those in Need: Estimates of USDA's SNAP Program Participation Rates in 2019 [Dataset]. https://catalog.data.gov/dataset/reaching-those-in-need-estimates-of-usdas-snap-program-participation-rates-in-2019-0ed3c
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    Dataset updated
    May 8, 2025
    Dataset provided by
    Food and Nutrition Servicehttps://www.fns.usda.gov/
    Description

    This report–part of an annual series–presents estimates of the percentage of eligible persons, by state, who participated in the U.S. Department of Agriculture's Supplemental Nutrition Assistance Program (SNAP) during an average month in fiscal year (FY) 2019 and in the two previous fiscal years. SNAP eligibility criteria include maximum income and resource thresholds, as well as certain nonfinancial criteria, such as age and disability status.

  8. T

    Sweden - Self-reported unmet need for medical examination and care

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 15, 2021
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    TRADING ECONOMICS (2021). Sweden - Self-reported unmet need for medical examination and care [Dataset]. https://tradingeconomics.com/sweden/self-reported-unmet-need-for-medical-examination-care-eurostat-data.html
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Feb 15, 2021
    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
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Sweden
    Description

    Sweden - Self-reported unmet need for medical examination and care was 2.20% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Sweden - Self-reported unmet need for medical examination and care - last updated from the EUROSTAT on June of 2025. Historically, Sweden - Self-reported unmet need for medical examination and care reached a record high of 2.60% in December of 2008 and a record low of 1.30% in December of 2021.

  9. People in need in Southern and East Africa 2021

    • statista.com
    Updated Aug 2, 2022
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    Statista (2022). People in need in Southern and East Africa 2021 [Dataset]. https://www.statista.com/statistics/1238869/number-of-people-in-need-in-southern-and-east-africa/
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    Dataset updated
    Aug 2, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    East Africa, Africa, Somalia, South Sudan, Mozambique, Ethiopia, Sudan, Zimbabwe, Burundi
    Description

    Nearly 59 million people were in need of humanitarian assistance and protection in Southern and East Africa as of 2021. Ethiopia had the most critical situation, with 21.3 million inhabitants in vulnerable situations due to conflict, climate shocks, desert locust invasion, and the ongoing effects of the coronavirus (COVID-19) pandemic. In its turn, Sudan had 13.4 million people in need. The country has been facing an economic crisis, apart from dealing with the effects of record flooding levels and the COVID-19 outbreak.

  10. Effect size estimates.

    • plos.figshare.com
    xls
    Updated May 30, 2023
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    Lee Cronk; Athena Aktipis; Steven Gazzillo; Dave White; Amber Wutich; Barry Sopher (2023). Effect size estimates. [Dataset]. http://doi.org/10.1371/journal.pone.0220682.t003
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    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Lee Cronk; Athena Aktipis; Steven Gazzillo; Dave White; Amber Wutich; Barry Sopher
    License

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

    Description

    Cohen’s d for our seven main variables as calculated by the Social Science Statistics (http://socscistatistics.com) web site.

  11. Colombia: JIAF Humanitarian Needs People in Need and Severity

    • data.amerigeoss.org
    • data.humdata.org
    csv, pdf, xlsx
    Updated Jun 18, 2025
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    UN Humanitarian Data Exchange (2025). Colombia: JIAF Humanitarian Needs People in Need and Severity [Dataset]. https://data.amerigeoss.org/es/dataset/col-jiaf-humanitarian-needs-pin-and-severity
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    xlsx(805937), csv(103997), pdf(2785161)Available download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    United Nationshttp://un.org/
    United Nations Office for the Coordination of Humanitarian Affairshttp://www.unocha.org/
    License

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

    Area covered
    Colombia
    Description

    This dataset contains the overall people in need and intersectoral severity by disaggregation level which Includes administrative divisions and population groups, depending on each country's decision. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners using the Joint Intersectoral Analysis Framework(JIAF).

  12. b

    Age and Sex, by type of SEN provision and type of need

    • cityobservatory.birmingham.gov.uk
    • cityobservatorybirmingham.opendatasoft.com
    csv, excel, json
    Updated Aug 8, 2024
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    (2024). Age and Sex, by type of SEN provision and type of need [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/age-and-gender-by-type-of-sen-provision-and-type-of-need/
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    csv, json, excelAvailable download formats
    Dataset updated
    Aug 8, 2024
    License

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

    Description

    Number of pupils in state-funded nursery, primary, secondary and special schools, non-maintained special schools and AP schools by SEN provision, type of need, age and sex.

  13. Population in core housing need, by selected economic family characteristics...

    • ouvert.canada.ca
    • datasets.ai
    • +2more
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Population in core housing need, by selected economic family characteristics of persons and sex [Dataset]. https://ouvert.canada.ca/data/dataset/81851cc5-c2fa-4c62-94b4-23a406435022
    Explore at:
    csv, xml, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    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

    Description

    Number and proportion of population in core housing need, by selected economic family characteristics of persons, sex, age group and selected demographic characteristics, Canada, provinces and territories.

  14. f

    Performance metrics of the Dynamic Criticality Index models developed from...

    • plos.figshare.com
    xls
    Updated Jan 29, 2024
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    Anita K. Patel; Eduardo Trujillo-Rivera; James M. Chamberlain; Hiroki Morizono; Murray M. Pollack (2024). Performance metrics of the Dynamic Criticality Index models developed from the multi-institutional database applied to the single-site test dataset (A) and the single-site Dynamic Criticality Index models applied to the single-site test dataset (B). [Dataset]. http://doi.org/10.1371/journal.pone.0288233.t002
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    xlsAvailable download formats
    Dataset updated
    Jan 29, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Anita K. Patel; Eduardo Trujillo-Rivera; James M. Chamberlain; Hiroki Morizono; Murray M. Pollack
    License

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

    Description

    Performance metrics of the Dynamic Criticality Index models developed from the multi-institutional database applied to the single-site test dataset (A) and the single-site Dynamic Criticality Index models applied to the single-site test dataset (B).

  15. Lifeline - Safety & Security - Live - Point - Major State Government...

    • prod.testopendata.com
    Updated May 8, 2023
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    FEMA AGOL (2023). Lifeline - Safety & Security - Live - Point - Major State Government Buildings (HIFLD) [Dataset]. https://prod.testopendata.com/datasets/936268b3521a412ba46e3992ea32b82f
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    Dataset updated
    May 8, 2023
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    FEMA AGOL
    Area covered
    Description

    Note: Irreparable; Layer has been removed from HIFLDSource Item: https://www.arcgis.com/home/item.html?id=1b6e231f88814aceb30fb6ad3ff86014This dataset represents the locations of buildings or properties that are owned or leased by state level governments. It includes buildings occupied by the headquarters of cabinet level state government executive departments, legislative office buildings outside of the capitol building, offices and court rooms associated with the highest level of the judicial branch of the state government, and large multi-agency state office buildings. Because the research to create this dataset was primarily keyed off of the headquarters of cabinet level state government agencies, some state office buildings that don't house a headquarters for such an agency may have been excluded. Intentionally excluded from this dataset are government run institutions (e.g., schools, colleges, prisons, and libraries). Also excluded are state capitol buildings, as these entities are represented in other HSIP layers. State owned or leased buildings whose primary purpose is not to house state offices have also been intentionally excluded from this dataset. Examples of these include "Salt Domes", "Park Shelters", and "Highway Garages". All entities that have been verified to have no building name have had their [NAME] value set to "NO NAME". If the record in the original source data had no building name and TGS was unable to verify the building name, the [NAME] value was set to "UNKNOWN". All phone numbers in this dataset have been verified by TGS to be the main phone for the building. If the building was verified not to have a main phone number, the [TELEPHONE] field has been left blank. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 11/27/2007 and the newest record dates from 05/28/2008. Homeland Security

    Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1) There has been a natural or manmade disaster, such as a hurricane or earthquake. An assessment of what State property may be affected, and what State services may be impacted needs to be made. 2) There is a predicted natural disaster, such as a hurricane. An assessment of what State property, personnel and services might be in the disaster's predicted footprint or path needs to be made. Preparations need to be made to evacuate personnel, secure property, and arrange for alternate methods of delivering the critical services that may be affected. 3) There has been a terrorist threat against State property and/or personnel. Steps need to be taken to identify what is being threatened, counter the threat, and protect threatened personnel and property. Additional property may be impacted due to its proximity to the threatened property, or the threat may contain only a general spatial reference, and the spatial component of this dataset may need to be used to identify the threatened property

  16. Annual number of Haitians in need 2016-2025

    • statista.com
    Updated Mar 3, 2025
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    Statista (2025). Annual number of Haitians in need 2016-2025 [Dataset]. https://www.statista.com/statistics/1448355/annual-number-of-haitians-in-need/
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    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Haiti
    Description

    In 2025, the United Nations identified six million people in need in Haiti. The largest increase occurred between 2019 and 2020, when the number of people in need nearly doubled from 2.6 million to 5.1 million.

  17. Share of perceived need for nuclear power generation South Korea Q3 2023-Q1...

    • statista.com
    Updated Jun 12, 2025
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    Statista (2025). Share of perceived need for nuclear power generation South Korea Q3 2023-Q1 2025 [Dataset]. https://www.statista.com/statistics/1615666/south-korea-perceived-need-for-nuclear-power-generation/
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    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Korea
    Description

    According to a survey conducted in South Korea on energy awareness, around ** percent of respondents answered that nuclear power was a necessity as of the first quarter of 2025. Figures have seen a clear increase from the previous year.

  18. H

    Honduras HN: Unmet Need for Contraception: % of Married Women Aged 15-49

    • ceicdata.com
    Updated May 4, 2018
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    CEICdata.com (2018). Honduras HN: Unmet Need for Contraception: % of Married Women Aged 15-49 [Dataset]. https://www.ceicdata.com/en/honduras/health-statistics/hn-unmet-need-for-contraception--of-married-women-aged-1549
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    Dataset updated
    May 4, 2018
    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, 1987 - Dec 1, 2012
    Area covered
    Honduras
    Description

    Honduras HN: Unmet Need for Contraception: % of Married Women Aged 15-49 data was reported at 10.700 % in 2012. This records a decrease from the previous number of 16.800 % for 2006. Honduras HN: Unmet Need for Contraception: % of Married Women Aged 15-49 data is updated yearly, averaging 15.800 % from Dec 1987 (Median) to 2012, with 5 observations. The data reached an all-time high of 18.000 % in 1996 and a record low of 10.700 % in 2012. Honduras HN: Unmet Need for Contraception: % of Married Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Honduras – Table HN.World Bank: Health Statistics. Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.; ; Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division.; Weighted Average; Unmet need for contraception measures the capacity women have in achieving their desired family size and birth spacing. Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects.

  19. Door And Window Seals Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 5, 2024
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    Dataintelo (2024). Door And Window Seals Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/door-and-window-seals-market
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    pptx, csv, pdfAvailable download formats
    Dataset updated
    Oct 5, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Door And Window Seals Market Outlook



    The global door and window seals market size is projected to experience a robust growth trajectory, rising from USD 8.5 billion in 2023 to an estimated USD 12.4 billion by 2032, reflecting a Compound Annual Growth Rate (CAGR) of 4.2%. This growth is driven by increasing demand for energy-efficient building solutions, the rising construction activities worldwide, and the need for enhanced insulation and noise reduction in residential and commercial spaces.



    One of the primary growth factors for the door and window seals market is the increasing focus on energy efficiency. Stringent building codes and regulations aimed at reducing energy consumption have led to a surge in the adoption of high-performance door and window seals. These seals play a crucial role in minimizing air leakage, thereby reducing the energy required for heating and cooling buildings. This trend is further bolstered by the growing awareness of environmental sustainability and the need to decrease the carbon footprint of buildings.



    Technological advancements in seal materials and manufacturing processes are also contributing significantly to market growth. Innovations such as the development of more durable and flexible seal materials, like EPDM and silicone, have enhanced the performance and longevity of door and window seals. Additionally, advancements in manufacturing techniques have improved the precision and efficiency of seal production, making high-quality seals more accessible and affordable. These technological improvements are expected to continue driving market expansion.



    The expansion of the construction industry, particularly in emerging economies, is another key driver for the door and window seals market. Rapid urbanization and industrialization, coupled with increasing investments in infrastructure development, are leading to a rise in the construction of residential, commercial, and industrial buildings. This construction boom necessitates the use of effective sealing solutions to ensure the longevity and efficiency of building envelopes. As a result, the demand for door and window seals is expected to grow substantially in the coming years.



    From a regional perspective, the Asia Pacific region is anticipated to exhibit the highest growth rate in the door and window seals market. The region's growth can be attributed to the booming construction sector, driven by rapid urbanization and rising population. Countries like China and India are witnessing substantial investments in both residential and commercial construction projects, which is fueling the demand for door and window seals. Additionally, favorable government policies promoting energy efficiency and sustainable building practices are further propelling market growth in the Asia Pacific.



    Product Type Analysis



    The door and window seals market is segmented based on product type into EPDM seals, PVC seals, silicone seals, polyurethane seals, and others. Each material type offers distinct benefits and is chosen based on specific application requirements. EPDM seals, for example, are known for their excellent resistance to weathering, ozone, and UV radiation, making them suitable for harsh environmental conditions. This segment is expected to dominate the market due to its widespread use in both residential and commercial applications.



    PVC seals are another significant segment, valued for their affordability and ease of installation. These seals are commonly used in residential buildings where budget constraints are a critical consideration. Despite being less durable than EPDM and silicone, PVC seals offer adequate performance for many standard applications, making them a popular choice in cost-sensitive markets.



    Silicone seals, known for their superior flexibility and temperature resistance, are increasingly being adopted in applications that require high-performance sealing solutions. These seals are particularly favored in industrial and automotive sectors, where extreme temperature fluctuations and demanding conditions are common. The silicone seals segment is expected to witness substantial growth, driven by the increasing demand for high-quality, long-lasting seals.



    Polyurethane seals, with their excellent abrasion resistance and mechanical strength, are also gaining traction in the market. These seals are predominantly used in industrial applications where durability and performance are paramount. The growing industrialization and the need for robust sealing solutions in machinery and equipment are

  20. B

    Bolivia BO: Unmet Need for Contraception: % of Married Women Aged 15-49

    • ceicdata.com
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    CEICdata.com, Bolivia BO: Unmet Need for Contraception: % of Married Women Aged 15-49 [Dataset]. https://www.ceicdata.com/en/bolivia/social-health-statistics/bo-unmet-need-for-contraception--of-married-women-aged-1549
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    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1989 - Dec 1, 2016
    Area covered
    Bolivia
    Description

    Bolivia BO: Unmet Need for Contraception: % of Married Women Aged 15-49 data was reported at 23.200 % in 2016. This records an increase from the previous number of 20.100 % for 2008. Bolivia BO: Unmet Need for Contraception: % of Married Women Aged 15-49 data is updated yearly, averaging 23.200 % from Dec 1989 (Median) to 2016, with 7 observations. The data reached an all-time high of 35.700 % in 1989 and a record low of 20.100 % in 2008. Bolivia BO: Unmet Need for Contraception: % of Married Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Health Statistics. Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.;Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division.;Weighted average;Unmet need for contraception measures the capacity women have in achieving their desired family size and birth spacing. Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects.

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Department for Business, Energy & Industrial Strategy (2023). National Energy Efficiency Data-Framework (NEED) report: summary of analysis 2021 [Dataset]. https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-report-summary-of-analysis-2021
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National Energy Efficiency Data-Framework (NEED) report: summary of analysis 2021

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Dataset updated
Aug 11, 2023
Dataset provided by
GOV.UKhttp://gov.uk/
Authors
Department for Business, Energy & Industrial Strategy
Description

The National Energy Efficiency Data-Framework (NEED) was set up to provide a better understanding of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. The data framework matches data about a property together - including energy consumption and energy efficiency measures installed - at household level.

11 August 2023 Error notice: revisions to the June 2021 Domestic NEED annual report

We identified 2 processing errors in this edition of the Domestic NEED Annual report and corrected them. The changes are small and do not affect the overall findings of the report, only the domestic energy consumption estimates. The revisions are summarised here:

Error 1: Local authority consumption estimates

Error 2: Some properties incorrectly excluded from the Scotland multiple attributes tables

  • Extent of the error: These corrections primarily affect the number in sample column for all years as some properties were incorrectly excluded from the consumption estimates. There have also been revisions to the mean, median, upper and lower quartiles. Using 2019 as an example, around 80% of the updated mean and median values are within 300 kWh of what was previously published.
  • Years affected: 2017-2019
  • Countries affected: Scotland
  • Data tables affected: Multiple attributes tables: Scotland, 2019 (all tables)

4 August 2021 Error notice: revisions to the June 2021 Domestic NEED annual report

We identified 2 processing errors in this edition of the Domestic NEED Annual report and corrected them. The changes are small and do not affect the overall findings of the report, only the domestic energy consumption estimates. The impact of energy efficiency measures analysis remains unchanged. The revisions are summarised here:

Error 1: Some properties incorrectly excluded from the 2019 gas consumption estimates

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