36 datasets found
  1. d

    Strategic Measure_EOA.B.2 Distribution of Household Income

    • catalog.data.gov
    • datahub.austintexas.gov
    • +2more
    Updated Apr 25, 2025
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    data.austintexas.gov (2025). Strategic Measure_EOA.B.2 Distribution of Household Income [Dataset]. https://catalog.data.gov/dataset/strategic-measure-eoa-b-2-distribution-of-household-income
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    Dataset updated
    Apr 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. The purpose of this dataset is to track the distribution of aggregate city income between the 5 quintile of population segments. The dataset comes from the 2019 U.S. Census Bureau, American Communities Survey (5yr) Table B19082. The row levels contain total percentage of income shares by the middle 3 quintiles (20-80%) of population. This data can be used to provide insights into growth/decline of middle class. Distribution of household income (Note: This indicator can provide insights into growth/decline of middle class) View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/Distribution-of-Household-Income/i3a3-vjnc/

  2. D

    Household Types and Populations - Seattle Neighborhoods

    • data.seattle.gov
    • data-seattlecitygis.opendata.arcgis.com
    • +1more
    application/rdfxml +5
    Updated Oct 22, 2024
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    (2024). Household Types and Populations - Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/Household-Types-and-Populations-Seattle-Neighborho/8nez-wmwv
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    xml, csv, tsv, json, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 22, 2024
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on household types and population related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B11003 Family Type by Presence and Age of Own Children under 18 Years, B11005 Households by Presence of People Under 18 Years by Household Type, B11007 Households by Presence of People 65 Years and Over by Household Type, B11001 Household Type (Including Living Alone), B11002 Household Type by Relatives and Nonrelatives for Population in Households, B25003 Tenure, B25008 Total Population in Occupied Housing Units by Tenure, B09019 Household Type (Including Living Alone) by Relationship. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.


    Table created for and used in the Neighborhood Profiles application.

    Vintages: 2023


    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k <a href='https://www.census.gov/geographies/mapping-files/time-series/geo/cartographic-boundary.html' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit; margin:0px;

  3. Family Resources Survey, 2019-2020

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Apr 17, 2025
    + more versions
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    Office for National Statistics; NatCen Social Research (2025). Family Resources Survey, 2019-2020 [Dataset]. http://doi.org/10.5255/UKDA-SN-8802-2
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    Dataset updated
    Apr 17, 2025
    Dataset provided by
    Department for Work and Pensionshttps://gov.uk/dwp
    Authors
    Office for National Statistics; NatCen Social Research
    Time period covered
    Apr 1, 2019 - Mar 31, 2020
    Area covered
    United Kingdom
    Variables measured
    Families/households, National
    Measurement technique
    Telephone interview: Computer-assisted (CATI)
    Description

    Abstract copyright UK Data Service and data collection copyright owner.

    The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP.

    The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.

    The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.

    Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage.

    The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage.

    Secure Access FRS data
    In addition to the standard End User Licence (EUL) version, Secure Access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 9256. Prospective users of the Secure Access version of the FRS will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.

    FRS, HBAI and PI
    The FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503, respectively. The Secure Access versions are held under SN 7196 and 9257 (see above).


    Latest edition information
    For the second edition (April 2025), previously unpopulated IMD variables IMDE, IMDN, IMDS, IMDW, IMD_E, IMD_NI, IMD_S and IMD_W in the 'househol' file were replaced with new versions.
    Main Topics:

    Household characteristics (family composition, tenure); housing costs including rent or details of mortgage; household bills including Council Tax, buildings and contents insurance, water and sewerage rates; receipt of state support from all state benefits, including Universal Credit and Tax Credits; educational level and grants and loans; children in education; care, both those receiving care and those caring for others; childcare; occupation, employment, self-employment and earnings/wage details; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; health, restrictions on work, children's health, and disability or limiting long-standing illness; personal and occupational pension schemes; income from pensions and trusts, royalties and allowances, and other sources; children's earnings; interest and dividends from investments including National Savings products, stocks and shares; and total household assets.


    Standard Measures
    Standard Occupational Classification; Ethnicity

  4. Population in the National Accounts: distributions by household type

    • db.nomics.world
    Updated Jun 18, 2025
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    DBnomics (2025). Population in the National Accounts: distributions by household type [Dataset]. https://db.nomics.world/OECD/DSD_EGDNA_SOCDEM@DF_SOCIODEMOGRAPHIC_HHGROUP
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    Dataset updated
    Jun 18, 2025
    Authors
    DBnomics
    Description

    This dataset accompanies the tables ‘Household income and saving in the National Accounts: distributions by household type’ and ‘Household consumption in the National Accounts: distributions by household type’ and presents the number of households, individuals, and consumption units for each type of household, which is based on household composition.

       Eight types of household are shown: a) single person (adult) less than 65 years old, b) single adult aged 65 and older, c) single adult with children living at home, d) a couple (two adults) where both are less than 65 years old without children living at home, e) two adults where at least one is aged 65 or older without children living at home, f) two adults with fewer than 3 children living at home, g) two adults with at least 3 children living at home, and h) others. In this classification, an adult is defined as anyone who is 18 years old or older.<br><br>
    
       The default view of this table is for a single country (‘Reference area’ filter) and single year (‘Time period’ filter). In cases where countries appear to be greyed-out, data may be available for earlier years, and these can be selected by selecting a different start and end year in the ‘Time period’ filter. <br><br>
    
    
       For more information on the (compilation of) these results, please see the <a href="https://www.oecd.org/sdd/na/household-distributional-results-in-line-with-national-accounts-experimental-statistics.htm"> webpage on household distributional results </a>.
    
  5. a

    ABS Census - B32 Family Type By Number Of Dependent Offspring (Usually...

    • data.aurin.org.au
    Updated Mar 5, 2025
    + more versions
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    (2025). ABS Census - B32 Family Type By Number Of Dependent Offspring (Usually Resident) By Annual Parental Income (SLA) 1991 - Dataset - AURIN [Dataset]. https://data.aurin.org.au/dataset/au-govt-abs-census-b32-fam-type-by-num-dpnt-offspring-by-yr-prntal-inc-sla-1991-na
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    Dataset updated
    Mar 5, 2025
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    The 1991 Census Basic Community profiles present 57 tables containing summary characteristics of persons and/or dwellings for Statistical Local Areas (SLA) in Australia. This table contains data relating to family type by number of dependent offspring (usually resident (a)) by annual parental income. Counts are of families with offspring, based on place of enumeration on census night which excludes adjustment for under-enumeration however in determining family and household type visitors to dwellings are excluded and usual residents who are temporarily absent are included. The data is by SLA 1991 boundaries. Periodicity: 5-Yearly. This data is ABS data (cat. no. 2101.0 & original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au. For more information please refer to the 1991 Census Dictionary. Please note: (a) A maximum of 3 temporarily absent dependent offspring can be counted in each household. (b) Comprises two parent families where a parent present did not state their income or a parent was temporarily absent. (c) Comprises cases where in a two parent family, both parents did not state their income or were temporarily absent; origin a one parent family, the parent did not state their income or was temporarily absent.

  6. a

    ABS Census - T18 Family Type (LGA) 1991 - Dataset - AURIN

    • data.aurin.org.au
    Updated Mar 5, 2025
    + more versions
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    (2025). ABS Census - T18 Family Type (LGA) 1991 - Dataset - AURIN [Dataset]. https://data.aurin.org.au/dataset/au-govt-abs-census-t18-fam-type-all-fam-lga-1991-na
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    Dataset updated
    Mar 5, 2025
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    The 1991 Census Time Series Community profiles present key tables from the Basic and Expanded Community profiles where the data is comparable across the censuses for Local Government Areas (LGA) in Australia. These profiles are made up of 22 tables giving data for both persons and/or dwellings from the 1981, 1986 and 1991 censuses. This table contains data relating to family type(a)(b). Counts are of all families, based on place of enumeration on census night which; includes overseas visitors; excludes Australians overseas; and excludes adjustment for under-enumeration. The data is by LGA 1991 boundaries. Periodicity: 5-Yearly. This data is ABS data (cat. no. 2101.0 & original geographic boundary cat. no. 1261.0.30.001) used with permission from the Australian Bureau of Statistics. The tabular data was processed and supplied to AURIN by the Australian Data Archives. The cleaned, high resolution 1991 geographic boundaries are available from data.gov.au. For more information please refer to the 1991 Census Dictionary.

  7. s

    Food security: Number of households engaged in livestock by type of animal,...

    • pacific-data.sprep.org
    • pacificdata.org
    Updated Mar 7, 2025
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    SPC (2025). Food security: Number of households engaged in livestock by type of animal, by geography, sex, age, urbanisation and wealth (Kiribati, Tuvalu and Vanuatu) [Dataset]. https://pacific-data.sprep.org/dataset/food-security-number-households-engaged-livestock-type-animal-geography-sex-age
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    application/vnd.sdmx.data+csv; labels=name; version=2; charset=utf-8Available download formats
    Dataset updated
    Mar 7, 2025
    Dataset provided by
    Pacific Data Hub
    Authors
    SPC
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    [163.30859653600123, [165.58629412437483, -4.064825000073597], [182.1276999998553, [172.79513888888937, [203.00255555579437, [175.86669999977985, [178.21652777777842, [172.3784111113913, [180.12184444444463, Kiribati, Tuvalu, Vanuatu
    Description

    This dataset provides number of households engaged in livestock by type of animal, geography (2 sub-national levels), sex, age, urbanization, and wealth (index) for Kiribati, Tuvalu and Vanuatu based on Population and Housing Census (PHC). The table has been compiled as a result of a collaborative project on food security between the Pacific Community (SPC) and the Food and Agriculture Organization of the United Nations (FAO).

    Find more Pacific data on PDH.stat.

  8. V

    Child Care and Development Fund (CCDF) Administrative Data Series

    • data.virginia.gov
    • healthdata.gov
    html
    Updated Feb 3, 2025
    + more versions
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    ACF (2025). Child Care and Development Fund (CCDF) Administrative Data Series [Dataset]. https://data.virginia.gov/dataset/child-care-and-development-fund-ccdf-administrative-data-series
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    htmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    ACF
    Description

    This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines.

    The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee.

    Units of Response: United States and Territories, CCDF Family Recipients, CCDF Children Recipients

    Type of Data: Administrative

    Tribal Data: No

    Periodicity: Annual

    Demographic Indicators: Ethnicity;Household Income;Household Size;Race

    SORN: Not Applicable

    Data Use Agreement: Not Applicable

    Data Use Agreement Location: https://www.icpsr.umich.edu/rpxlogin

    Granularity: Family;Individual

    Spatial: United States

    Geocoding: Tribe

  9. V

    National Survey of Children in Nonparental Care

    • data.virginia.gov
    • healthdata.gov
    • +2more
    html
    Updated Feb 3, 2025
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    ACF (2025). National Survey of Children in Nonparental Care [Dataset]. https://data.virginia.gov/dataset/national-survey-of-children-in-nonparental-care
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    htmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    ACF
    Description

    This survey provides nationally representative estimates on the characteristics, living arrangements, and service accessibility of noninstitutionalized children who were living apart from their parents (in foster care, grandparent care or other nonparental care) and who were aged 0 to 16 years in 2011-2012. Data on the well-being of the children and of their caregivers are also available. The children’s nonparental care status was identified in a previous SLAITS survey, the 2011-2012 National Survey of Children’s Health.

    Units of Response: Caregiver

    Type of Data: Survey

    Tribal Data: No

    Periodicity: One-time

    Demographic Indicators: Disability;Ethnicity;Household Income;Household Size;Housing Status;Race;Sex

    SORN: https://www.federalregister.gov/documents/2022/09/19/2022-20139/privacy-act-of-1974-system-of-records

    Data Use Agreement: No

    Data Use Agreement Location: Unavailable

    Granularity: Household

    Spatial: United States

    Geocoding: Unavailable

  10. SAFI Survey Results

    • figshare.com
    txt
    Updated May 19, 2018
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    Philip Woodhouse; Gert Jan Veldwisch; Daniel Brockington; Hans C. Komakech; Angela Manjichi; Jean-Philippe Venot (2018). SAFI Survey Results [Dataset]. http://doi.org/10.6084/m9.figshare.6262019.v4
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    txtAvailable download formats
    Dataset updated
    May 19, 2018
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Philip Woodhouse; Gert Jan Veldwisch; Daniel Brockington; Hans C. Komakech; Angela Manjichi; Jean-Philippe Venot
    License

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

    Description

    SAFI (Studying African Farmer-Led Irrigation) is a currently running project which is looking at farming and irrigation methods. This is survey data relating to households and agriculture in Tanzania and Mozambique. The survey data was collected through interviews conducted between November 2016 and June 2017. The survey covered such things as; household features (e.g. construction materials used, number of household members), agricultural practices (e.g. water usage), assets (e.g. number and types of livestock) and details about the household members.This is a teaching version of the collected data, it is not the full dataset. The survey is split into several sections:A – General questions about when and where the survey was conducted.B - Information about the household and how long they have been living in the areaC – Details about the accommodation and other buildings on the farmD – Details about the different plots of land they grow crops onE – Details about how they irrigate the land and availability of waterF – Financial details including assets owned and sources of incomeG – Details of Financial hardshipsX – Information collected directly from the smartphone (GPS) or automatically included in the form (instanceID)key_id Added to provide a unique Id for each observation. (The InstanceID field does this as well but it is not as convenient to use)A01_interview_date, Date of InterviewA03_quest_no, Questionnaire numberA04_start, Timestamp of start of InterviewA05_end, Timestamp of end of InterviewA06_province, Province nameA07_district, District nameA08_ward, Ward nameA09_village, Village nameA11_years_farm, Number of years the household have been farming in this areaA12_agr_assoc, Does the head of the household belong to an agricultural association_note2 Possible form comment relating to the sectionB_no_membrs, How many members of the household?_members_count Internal count of membersB11_remittance_money, Is there any financial assistance from family members not living on the farmB16_years_liv, How many years have you been living in this village or neighbouring village?B17_parents_liv, Did your parents live in this village or neighbouring village?B18_sp_parents_liv, Did your spouse's parents live in this village or neighbouring village?B19_grand_liv, Did your grandparents live in this village or neighbouring village?B20_sp_grand_liv, Did your spouse's grandparents live in this village or neighbouring village?C01_respondent_roof_type, What type of roof does their house have?C02_respondent_wall_type, What type of walls does their house have (from list)C02_respondent_wall_type_other, What type of walls does their house have (not on list)C03_respondent_floor_type, What type of floor does their house have C04_window_type, Does the house have glass in at least one window?C05_buildings_in_compound, How many buildings are in the compound? Do not include stores, toilets or temporary structures.C06_rooms, How many rooms in the main house are used for sleeping?C07_other_buildings, Does the DU own any other buildings other than those on this plotD_no_plots, How many plots were cultivated in the last 12 months?D_plots_count, Internal count of plotsE01_water_use, Do you bring water to your fields, stop water leaving your fields or drain water out of any of your fields?E_no_group_count, How many plots are irrigated?E_yes_group_count, How many plots are not irrigated?E17_no_enough_water, Are there months when you cannot get enough water for your crops? Indicate which months.E18_months_no_water, Please select the monthsE19_period_use, For how long have you been using these methods of watering crops? (years)E20_exper_other, Do you have experience of such methods on other farms?E21_other_meth, Have you used other methods before?E22_res_change, Why did you change the way of watering your crops?E23_memb_assoc, Are you a member of an irrigation association?E24_resp_assoc, Do you have responsibilities in that association?E25_fees_water, Do you pay fees to use water?E26_affect_conflicts, Have you been affected by conflicts with other irrigators in the area ?_note Form comment for sectionF04_need_money, If you started or changed the way you water your crops recently, did you need any money for it?F05_money_source, Where did the money came from? (list)F05_money_source_other, Where did the money came from? (not on list)F06_crops_contr, Considering fields where you have applied water, how much do those crops contribute to your overall income?F08_emply_lab, In the most recent cultivation season, did you employ day labourers on fields?F09_du_labour, In the most recent cultivation season, did anyone in the household undertake day labour work on other farm?F10_liv_owned, What types of livestock do you own? (list)F10_liv_owned_other, What types of livestock do you own? (not on list)F_liv_count, Livestock countF12_poultry, Own poultry?F13_du_look_aftr_cows, At the present time, does the household look after cows for someone else in return for milk or money?F14_items_owned, Which of the following items are owned by the household? (list)F14_items_owned_other, Which of the following items are owned by the household? (not on list)G01_no_meals, How many meals do people in your household normally eat in a day?G02_months_lack_food, Indicate which months, In the last 12 months have you faced a situation when you did not have enough food to feed the household?G03_no_food_mitigation, When you have faced such a situation what do you do?gps:Latitude, Location latitude (provided by smartphone)gps:Longitude, Location Longitude (provided by smartphone)gps:Altitude, Location Altitude (provided by smartphone)gps:Accuracy, Location accuracy (provided by smartphone)instanceID, Unique identifier for the form data submission

  11. d

    Allegheny County Soil Type Areas

    • datasets.ai
    • data.wprdc.org
    • +7more
    15, 21, 25, 57, 8
    Updated Aug 27, 2024
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    Allegheny County / City of Pittsburgh / Western PA Regional Data Center (2024). Allegheny County Soil Type Areas [Dataset]. https://datasets.ai/datasets/allegheny-county-soil-type-areas
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    21, 15, 25, 8, 57Available download formats
    Dataset updated
    Aug 27, 2024
    Dataset authored and provided by
    Allegheny County / City of Pittsburgh / Western PA Regional Data Center
    Area covered
    Allegheny County
    Description

    This dataset contains soil type and soil classification, by area.

    If viewing this description on the Western Pennsylvania Regional Data Center’s open data portal (http://www.wprdc.org), this dataset is harvested on a weekly basis from Allegheny County’s GIS data portal (http://openac.alcogis.opendata.arcgis.com/). The full metadata record for this dataset can also be found on Allegheny County’s GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the “Explore” button (and choosing the “Go to resource” option) to the right of the “ArcGIS Open Dataset” text below.

    Category: Environment

    Organization: Allegheny County

    Department: Geographic Information Systems Group; Department of Administrative Services

    Temporal Coverage: 2000

    Data Notes:

    Coordinate System: Pennsylvania State Plane South Zone 3702; U.S. Survey Foot

    Development Notes: This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. The soil map and data used in the SSURGO product were prepared by soil scientists as part of the National Cooperative Soil Survey

    Other: none

    Related Document(s): Data Dictionary for SOIL_CODE

    Related Document(s): https://www.nrcs.usda.gov/Internet/FSE_MANUSCRIPTS/pennsylvania/PA003/0/legends.pdf - the last page includes the soil legend for this dataset.

    Frequency - Data Change: As needed

    Frequency - Publishing: As needed

    Data Steward Name: Eli Thomas

    Data Steward Email: gishelp@alleghenycounty.us

  12. National Survey of Child and Adolescent Well-Being (NSCAW)

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Nov 17, 2023
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    (2023). National Survey of Child and Adolescent Well-Being (NSCAW) [Dataset]. https://healthdata.gov/ACF/National-Survey-of-Child-and-Adolescent-Well-Being/9my6-rhui
    Explore at:
    application/rdfxml, csv, tsv, json, application/rssxml, xmlAvailable download formats
    Dataset updated
    Nov 17, 2023
    Description

    The National Survey of Child and Adolescent Well-Being (NSCAW) is a nationally representative, longitudinal survey of children and families who have been the subjects of investigation by Child Protective Services. There are currently two cohorts of available data (NSCAW I and NSCAW II) drawn from first-hand reports from children, parents, and other caregivers, as well as reports from caseworkers, teachers, and data from administrative records. NSCAW examines child and family well-being outcomes in detail and seeks to relate those outcomes to experience with the child welfare system and to family characteristics, community environment, and other factors.

    Units of Response: Children and Families in the Child Welfare System

    Type of Data: Survey

    Tribal Data: Unavailable

    Periodicity: Irregular

    Demographic Indicators: Disability;Ethnicity;Geographic Areas;Household Income;Household Size;Race

    SORN: Not Applicable

    Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

    Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/pdfs_user_guides/IntroNSCAWWave1.pdf

    Granularity: Individual

    Spatial: United States

    Geocoding: Unavailable

  13. Census of Population and Housing, 1990: Public Use Microdata Sample B (1%)

    • archive.ciser.cornell.edu
    Updated Jun 1, 2024
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    Bureau of the Census (2024). Census of Population and Housing, 1990: Public Use Microdata Sample B (1%) [Dataset]. http://doi.org/10.6077/74r9-3685
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    Dataset updated
    Jun 1, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    Bureau of the Census
    Variables measured
    HousingUnit, Individual
    Description

    The Public Use Microdata Sample (PUMS) 1-Percent Sample contains household and person records for a sample of housing units that received the "long form" of the 1990 Census questionnaire. Data items include the full range of population and housing information collected in the 1990 Census, including 500 occupation categories, age by single years up to 90, and wages in dollars up to $140,000. Each person identified in the sample has an associated household record, containing information on household characteristics such as type of household and family income. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09951.v4. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  14. V

    Characteristics and Financial Circumstances of TANF Recipients

    • data.virginia.gov
    • healthdata.gov
    • +1more
    html
    Updated Feb 3, 2025
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    ACF (2025). Characteristics and Financial Circumstances of TANF Recipients [Dataset]. https://data.virginia.gov/dataset/characteristics-and-financial-circumstances-of-tanf-recipients
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    htmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    ACF
    Description

    The Characteristics and Financial Circumstances of TANF Recipients tables provide demographic data on the age and race/ethnicity of adults and children in TANF and Separate State Program (SSP)-Maintenance-of-Effort (MOE) active families and closed cases, as well as data on the financial circumstances of TANF cash assistance recipients.

    Units of Response: TANF Recipients, States

    Type of Data: Administrative

    Tribal Data: No

    Periodicity: Annual

    Demographic Indicators: Disability;Ethnicity;Household Size;Race

    SORN: Not Applicable

    Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

    Data Use Agreement Location: Unavailable

    Granularity: State

    Spatial: United States

    Geocoding: State

  15. t

    SELECTED HOUSING CHARACTERISTICS - DP04_PIN_T - Dataset - CKAN

    • portal.tad3.org
    Updated Nov 17, 2024
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    (2024). SELECTED HOUSING CHARACTERISTICS - DP04_PIN_T - Dataset - CKAN [Dataset]. https://portal.tad3.org/dataset/selected-housing-characteristics-dp04_pin_t
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    Dataset updated
    Nov 17, 2024
    License

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

    Description

    SELECTED HOUSING CHARACTERISTICS SELECTED CHARACTERISTICS - DP04 Universe - Occupied housing units Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Complete plumbing facilities include: (a) hot and cold running water and (b) a bathtub or shower. Both facilities must be located inside the house, apartment, or mobile home, but not necessarily in the same room. Housing units are classified as lacking complete plumbing facilities when either of the two facilities is not present. A unit has complete kitchen facilities when it has all three of the following facilities: a sink with a faucet, a stove or range, and a refrigerator. All kitchen facilities must be located in the house, apartment, or mobile home, but they need not be in the same room. A housing unit having only a microwave or portable heating equipment such as a hot plate or camping stove should not be considered as having complete kitchen facilities. An icebox is not considered to be a refrigerator. Respondents are instructed to mark “Yes” if any household member has a working cell phone, smart phone, or any other type of phone device, or if the housing unit has a land line telephone in working order. Households whose service has been discontinued for nonpayment or other reasons are not counted as having telephone service available.

  16. Integrated Household Survey, January - December, 2014

    • beta.ukdataservice.ac.uk
    • datacatalogue.cessda.eu
    Updated 2015
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    Social Survey Division Office For National Statistics (2015). Integrated Household Survey, January - December, 2014 [Dataset]. http://doi.org/10.5255/ukda-sn-7839-1
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    Dataset updated
    2015
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Authors
    Social Survey Division Office For National Statistics
    Description

    The Integrated Household Survey (IHS), which ran from 2009-2014, was a composite survey combining questions asked on a number of social surveys conducted by the Office for National Statistics (ONS) to produce a dataset of 'core' variables. The ONS stopped producing IHS datasets from 2015 onwards; variables covering health, smoking prevalence, forces veterans, sexual identity and well-being will be incorporated into the Annual Population Survey - see the Which surveys (or modules) are included in the IHS? and What is the IHS? FAQ pages for further details.

    Background and history of the IHS
    The aim of the IHS was to produce high-level estimates for particular themes to a higher precision and lower geographic level than current ONS social surveys. The 'core' set contained around 100 questions, but a respondent was only asked a proportion of those depending on routing from answers to questions. The core questions were asked, where possible, at the beginning of the component surveys.
    In January 2008, a set of core questions was introduced within three ONS surveys in the General Lifestyle Survey, Living Costs and Food Survey, and the Opinions and Lifestyle Survey. In April 2008 the IHS core questions were also introduced on the English Housing Survey, bringing the family of modules on the IHS up to four. The IHS dataset for 2008-2009 was used as a pilot for the concept, developing the systems and designing the weighting methodology. The IHS data for that period have not been published as they do not provide better quality information than that within existing surveys. Hence, the earliest IHS data currently available cover 2009-2010. In April 2009 the IHS core questions were introduced on the Labour Force Survey (LFS) and Annual Population Survey (APS) questionnaires and from June 2009 the Life Opportunities Survey (LOS, which also ran from 2009-2014) was included in the IHS family of modules. With the inclusion of these new surveys the IHS became complete, with an achieved annual sample size of approximately 450,000 individuals from interviews undertaken in Great Britain and Northern Ireland. Therefore, the first IHS dataset released covers the period April 2009-March 2010, starting the IHS data series from the point that all surveys were included. The large sample size and UK-wide coverage meant that various geographical breakdowns were possible in the IHS, and it is possible to use a geographical hierarchy to drill down to lower level detail within an area. The IHS also contained data collected from the following surveys: General Lifestyle Survey; Living Costs and Food Survey; Opinions and Lifestyle Survey; English Housing Survey; Labour Force Survey; Annual Population Survey; and Life Opportunities Survey. All questions had been removed from the component surveys by 2014 and the IHS closed that year. Further information is available from the ONS Integrated Household Survey (Experimental statistics): January to December 2014 webpage.

    Available IHS data: End User Licence and Secure Access
    Users should note that there are two versions of the IHS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version (SN 8075). The Secure Access version contains more detailed variables relating to age, age of youngest dependent child, country of birth, family unit type, household and household reference person, industry class, sub-class and division, month left last job, cohabitation, country of residence history, multiple households at address, nationality, New Deal training types, National Statistics Socio-Economic Classification (NS-SEC) long version, qualifications, household relationships, minor Standard Occupational Classification (SOC) groups, sexual identity, training and working age. The more detailed geographic variables present include county, unitary/local authority, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions and Training and Enterprise Councils (TECs). Users should note that the user guide also mentions variables that are not included in either the EUL or Secure Access datasets held at the Archive.

    The EUL version contains less detailed variables. For example, the lowest geography available is Government Office Region, only major (3-digit) SOC groups are included for main, second and last job, and only industry sector for main, second and last job. Users are advised to first obtain the standard EUL version of the data before making an application for the Secure Access version to see if they are sufficient for their research requirements.

    The Special Licence version of the IHS January - December, 2014 is available under SN 7840.

  17. u

    HART (2025) - 2021 Census of Canada - Selected Characteristics of Households...

    • open.library.ubc.ca
    • borealisdata.ca
    Updated Mar 14, 2025
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    Statistics Canada (2025). HART (2025) - 2021 Census of Canada - Selected Characteristics of Households and Dwellings for Housing Need related to Federal HNA Template - Canada, all provinces and territories at the Census Division (CD) and Census Subdivision (CSD) level [custom tabulation] [Dataset]. http://doi.org/10.14288/1.0448205
    Explore at:
    Dataset updated
    Mar 14, 2025
    Authors
    Statistics Canada
    Time period covered
    Mar 10, 2025
    Area covered
    All Provinces and Territories, Canada
    Description

    Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025.

    For more information, please visit HART.ubc.ca.

    Housing Assessment Resource Tools (HART)

    This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template.

    17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension.

    The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide

    Custom order from Statistics Canada includes the following dimensions and data fields:

    Geography:
    - Country of Canada, all CDs & Country as a whole
    - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole
    - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole
    *- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000.

    Data Quality and Suppression:
    - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released.

    - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada

    - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero.

    Universe:
    Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero.

    Households examined for Core Housing Need:
    Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances.

    Data Fields:

    Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7)
    1. Total - Private households by tenure including presence of mortgage payments and subsidized housing
    2. Owner
    3. With mortgage
    4. Without mortgage
    5. Renter
    6. Subsidized housing
    7. Not subsidized housing

    Housing indicators in Core Housing Universe (12)
    1. Total - Private Households by core housing need status
    2. Households examined for core housing need
    3. Households in core housing need
    4. Below one standard only
    5. Below affordability standard only
    6. Below adequacy standard only
    7. Below suitability standard only
    8. Below 2 or more standards
    9. Below affordability and suitability
    10. Below affordability and adequacy
    11. Below suitability and adequacy
    12. Below affordability, suitability, and adequacy

    Period of construction (10)
    1. Total – Period of Construction
    2. Before 2016
    3. 1960 or before
    4. 1961 to 1980
    5. 1981 to 1990
    6. 1991 to 2000
    7. 2001 to 2005
    8. 2006 to 2010
    9. 2011 to 2015
    10. 2016 to 2021 (Note 1)
    Note 1). Includes data up to May 11, 2021.

    Structural type of dwelling and Household income as proportion to AMHI (16)
    1. Total - Structural type of dwelling
    2. Single-detached house
    3. Apartment in a building that has five or more storeys
    4. Other attached dwelling
    5. Apartment or flat in a duplex
    6. Apartment in a building that has fewer than five storeys
    7. Other single-attached house
    8. Row house
    9. Semi-detached house
    10. Movable dwelling
    11. Total – Private households by household income proportion to AMHI
    12. Households with income 20% or under of area median household income (AMHI)
    13. Households with income 21% to 50% of AMHI
    14. Households with income 51% to 80% of AMHI
    15. Households with income 81% to 120% of AMHI
    16. Households with income 121% or more of AMHI

    Selected characteristics (12)
    1. Total – Private households by presence of activity limitation (Q18e only)
    2. HH has at least one person who had an activity limitations reported for Question 18 e) only 1
    3. Total – Age of primary household maintainer
    4. 18 to 29 years
    5. Total – Private households by military service status of the HH members
    6. HH includes a person who is currently serving member and/or veteran
    11. Total – Private households by shelter cost proportion to AMHI_1
    12. Households with shelter cost 0.5% and under of AMHI
    13. Households with shelter cost 0.6% to 1.25% of AMHI
    14. Households with shelter cost 1.26% to 2% of AMHI
    15. Households with shelter cost 2.1% to 3% of AMHI
    16. Households with shelter cost 3.1% or more of AMHI*

    Median income (2)
    1. Number of households
    2. Median income of household ($)
    The household median income in the custom tabulation were estimates from a 25% sample-based data that have undergone weighting. These weights were applied to the sample data to produce estimates from the census long-form sample. The incomes used were drawn from the previous tax year, and therefore represent 2020 dollars.

    [Only in "Census 2021 - Gender Diverse HHs" file] Genderdiversity (2)
    1. Total - Gender diversity status of households
    2. HH is gender diverse


    File list (19 total):

    Original data files (18):
    1. Census 2021 - Table 1 - Median Incomes.ivt
    2. Census 2021 - Table 2 - Canada.ivt
    3. Census 2021 - Table 3 - Census Divisions.ivt
    4. Census 2021 - Table 4 - Ontario CSDs.ivt
    5. Census 2021 - Table 5 - BC CSDs.ivt
    6. Census 2021 - Table 6 - Alberta CSDs.ivt
    7. Census 2021 - Table 7 - Manitoba CSDs.ivt
    8. Census 2021 - Table 8 - Saskatchewan CSDs.ivt
    9. Census 2021 - Table 9-1 - Quebec CSDs (Part 1 of 3).ivt
    10. Census 2021 - Table 9-2 - Quebec CSDs (Part 2 of 3).ivt
    11. Census 2021 - Table 9-3 - Quebec CSDs (Part 3 of 3).ivt
    12. Census 2021 - Table 10 - Newfoundland&Labrador CSDs.ivt
    13. Census 2021 - Table 11 - PEI CSDs.ivt
    14. Census 2021 - Table 12 - Nova Scotia CSDs.ivt
    15. Census 2021 - Table 13 - New Brunswick CSDs.ivt
    16. Census 2021 - Table 14 - Yukon CSDs.ivt
    17. Census 2021 - Table 15 - NWT CSDs.ivt
    18. Census 2021 - Table 16 - Nunavut CSDs.ivt
    19. Census 2021 - Gender Diverse HHs.ivt

    Pour de plus amples renseignements, veuillez visiter HART.ubc.ca.

    Outils d'évaluation du logement ("HART")

    Cet ensemble de données contient 18 tableaux qui s’appuient sur les données

  18. u

    2006 Census of Canada - Selected Characteristics for Housing - Vancouver,...

    • open.library.ubc.ca
    • borealisdata.ca
    Updated Sep 26, 2019
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    Statistics Canada (2019). 2006 Census of Canada - Selected Characteristics for Housing - Vancouver, Toronto CMAs at the Census Tract (CT) Level [custom tabulation] 004 [Dataset]. http://doi.org/10.14288/1.0381012
    Explore at:
    Dataset updated
    Sep 26, 2019
    Authors
    Statistics Canada
    Time period covered
    Dec 31, 2006
    Area covered
    British Columbia, Ontario, Vancouver, Toronto
    Description

    This dataset includes two tables which were custom ordered from Statistics Canada. One table includes variables on housing characteristics (condominium status, total number of bedrooms, structural type and tenure), and households (household size, household type, age of primary household maintainer). One table includes information on shelter cost to income ratio and total shelter cost by tenure, household type, and household income.

    The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website:
    https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only).
    For information on how to use Beyond 20/20, please see:
    http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf
    https://wiki.ubc.ca/Library:Beyond_20/20_Guide

    Custom order from Statistics Canada

    TABLE 3 includes the following dimensions and variables:

    Geography: Toronto CMA & Vancouver CMA to the census tract level

    Age of Household maintainer: Age groups are divided into 9 year intervals starting at age 15 and ending at category 75 and above

    Condominium status: Condominium, not a condominium

    Tenure: Owner, renter

    Household size: From one person up to 5 or more persons

    Structural type:
    -Single detached house
    -Apartment with 5 or more stories
    -Other dwelling
    -Semi-detached house
    -Row house
    -Apartment, detached duplex
    -Apartment, building with fewer than 5 stories
    -Other single attached house
    -Movable dwelling

    Total number of bedrooms: From no bedrooms to 4 or more bedrooms

    Household type:
    -Census-family households
    -With children
    -Without children
    -Multiple census-family households
    -Non-census family household

    TABLE 4 includes the following dimensions and variables:

    Geography: Toronto CMA, Vancouver CMA

    Total Shelter cost: under $500 to over $3000 in intervals ranging from $250 to $500

    Tenure: Owner (with and without mortgage), renter

    Household type:
    -Census-family households
    -One-family households
    -Couple family households
    -With children
    -Without children
    -Lone-parent households
    -Multiple census-family households
    -Non-census-family households
    -One person households
    -Two person households

    Shelter cost to income ratio: less than 15%, 15-30%, 30-50%, 50% or more, not applicable

    Household income: in intervals of 10,000 up to the category of $100,000 or more

    Original file name:
    EO2969 - Table 3 Tenure and dwelling_Toronto and Vancouver 2006.ivt
    EO2969 - Table 4 (Part 1) Cost income household_Toronto and Vancouver_2006.ivt

  19. NoSQL Database Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). NoSQL Database Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-nosql-database-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    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

    NoSQL Database Market Outlook 2032



    The global NoSQL database market size was USD 5.9 Billion in 2023 and is likely to reach USD 36.6 Billion by 2032, expanding at a CAGR of 30% during 2024–2032. The market growth is attributed to the rising adoption of NoSQL databases by industries to manage large amounts of data efficiently.



    Increasing adoption of digital solutions by businesses is augmenting the NoSQL database industry. Businesses continue using the unique capabilities that NoSQL databases bring to their data management strategies. The NoSQL solutions work without any predefined schemas, thus, offering more flexibility to businesses that need to handle and manage ever-evolving data types and formats.





    The factors behind the accelerating growth of the NoSQL database market include the omnipresence of internet-related activities, a surge in big data, and others. NoSQL database solutions present exceptional scalability and offer superior performance while managing extensive datasets. Moreover, the shift from conventional SQL databases to NoSQL databases to handle big-data and real-time web application data augmented the market.



    Impact of Artificial Intelligence (AI) on the NoSQL Database Market



    Artificial Intelligence (AI) has a significant impact on the NoSQL databases market by creating a surge in data volume and variety. AI technologies, including machine learning and deep learning, generate and process vast amounts of data, necessitating efficient data management solutions. The integration of AI with NoSQL databases further enhances data analysis capabilities and enables businesses to acquire valuable insights and make informed decisions. Therefore, the rise of AI technologies is propelling the market.



    Non-Relational Databases, commonly referred to as NoSQL databases, have gained significant traction in recent years due to their ability to handle diverse data types and structures. Unlike traditional relational databases, non-relational databases do not rely on a fixed schema, which allows for greater flexibility and scalability. This adaptability is particularly beneficial for businesses dealing with large volumes of unstructured data, such as social media content, customer reviews, and multimedia files. As organizations continue to embrace digital transformation, the demand for non-relational databases is expected to rise, further driving the growth of the NoSQL database market.




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  20. British Household Panel Survey, Waves 1-18, 1991-2009: Special Licence...

    • beta.ukdataservice.ac.uk
    Updated 2019
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    Institute For Social University Of Essex (2019). British Household Panel Survey, Waves 1-18, 1991-2009: Special Licence Access, Acorn Type 2013 [Dataset]. http://doi.org/10.5255/ukda-sn-7447-1
    Explore at:
    Dataset updated
    2019
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Authors
    Institute For Social University Of Essex
    Description

    The main British Household Panel Survey (BHPS) is conducted by the ESRC UK Longitudinal Studies Centre (ULSC), together with the Institute for Social and Economic Research (ISER) at the University of Essex. In addition to conducting the BHPS and disseminating it to the research community, ISER undertakes a programme of research based on panel data, using the BHPS and other national panels to monitor and measure social change.

    The main objective of the BHPS is to further understanding of social and economic change at the individual and household level in the UK, and to identify, model and forecast such changes and their causes and consequences in relation to a range of socio-economic variables. It is conducted as a longitudinal study, where each adult member (aged 16 years and over) of a sampled household is interviewed annually. If individuals leave their original household, all adult members of their new households are interviewed. Children are also interviewed. For full details of the BHPS methodology, sampling, changes over time, and a complete set of documentation, see the main BHPS study, held at the UK Data Archive under SN 5151.

    Understanding Society:
    From Wave 19, the BHPS has been subsumed into a new longitudinal study called Understanding Society, or the United Kingdom Household Longitudinal Study (UKHLS), conducted by ISER. The BHPS Wave 19 formed part of Understanding Society Wave 2 (January 2010 - March 2011). The BHPS fieldwork period therefore moved from September-April to January-March. This means that the gap between interviews 18 and 19 for the BHPS sample ranges between 16 and 30 months rather than the standard 12 months. From Wave 2, the BHPS sample has been a permanent part of the larger study and interviews are conducted annually again. BHPS sample members have an identifier within the Understanding Society datasets, allowing BHPS users to match BHPS Wave 1-18 data to Understanding Society. The main Understanding Society study, held under SN 6614 now includes harmonised BHPS data in addition to the main Understanding Society files. Further information is available on the Understanding Society web site.


    This dataset contains Acorn geodemographic classification codes for each wave of the BHPS and a household identification serial number for file matching to the main BHPS data. This dataset is subject to restrictive access conditions, different to those for the main BHPS: see Access section below.

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data.austintexas.gov (2025). Strategic Measure_EOA.B.2 Distribution of Household Income [Dataset]. https://catalog.data.gov/dataset/strategic-measure-eoa-b-2-distribution-of-household-income

Strategic Measure_EOA.B.2 Distribution of Household Income

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Dataset updated
Apr 25, 2025
Dataset provided by
data.austintexas.gov
Description

This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. The purpose of this dataset is to track the distribution of aggregate city income between the 5 quintile of population segments. The dataset comes from the 2019 U.S. Census Bureau, American Communities Survey (5yr) Table B19082. The row levels contain total percentage of income shares by the middle 3 quintiles (20-80%) of population. This data can be used to provide insights into growth/decline of middle class. Distribution of household income (Note: This indicator can provide insights into growth/decline of middle class) View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/Distribution-of-Household-Income/i3a3-vjnc/

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