Annual house price data based on a sub-sample of the Regulated Mortgage Survey.

The American Community Survey (ACS) is a nationwide survey conducted by the U.S. Census Bureau that is designed to provide communities a fresh look at how they are changing. It is a critical element in the Census Bureau's reengineered decennial census program, incorporating the detailed socioeconomic and housing questions that were previously asked on the decennial census long form into the ACS questionnaire. The ACS now collects and produces this detailed population and housing information every year instead of every ten years. Data are collected on an on-going basis throughout the year and are released each year for large geographic areas, those with 65,000 persons or more. However, sample sizes are not large enough for annual releases that cover smaller areas, those with less than 65,000 persons. Data that are suitable for areas with 20,000 to 65,000 persons are accumulated over three years and termed a three-year period estimate, the first of which was for the 2005-2007 period. Data that are suitable for areas with less than 20,000 persons are accumulated over five years and termed a five-year period estimate, the first of which was for the 2005-2009 period. The data in this series of RGIS Clearinghouse tables are for all New Mexico counties and are based on the 2005-2009 ACS Five-Year Period Estimates collected between January 2005 and December 2009. These data tables are a summary of all major housing topics published through the ACS, providing information about the condition of housing, and illuminating various financial characteristics of the housing stock. Major topics include housing occupancy, year structure built, rooms and bedrooms, housing tenure (owners and renters), year householder moved into unit, vehicles available, type of house heating fuel, units without complete plumbing and kitchen facilities or without telephone service, occupants per room, home value, mortgage status, monthly owner costs, owner costs as a percentage of household income, gross rent, and gross rent as a percentage of household income. Percentages are shown along with numeric estimates for most data items. Because the data are based on a sample the Census Bureau also provides information about the magnitude of sampling error. Consequently, the estimated margin of error (MOE) is shown next to each data item. Each housing topic is covered in a separate file in both Excel and CSV formats. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

This dataset provides information on Tempe's subsidized housing program. Tempe has a fixed number of Housing Choice Vouchers (HCVs) based on our HUD contract, which represents the maximum number of families that the Housing Authority could assist. Congress and HUD do not fund the program to assist all of the families we are allotted to assist. We can only assist the number of families we have the budget to assist. HUD provides an initial funding amount based on what they anticipate they will allocate to housing assistance payments. The actual amount of funding received is subject to change depending on Federal Budget priorities, Congressional approval and many other factors. Expenditures are reported monthly, as HUD requires expenses to be posted in the month they were incurred rather than the month the expense was paid. The performance measure dashboard is available at 3.05 Subsidized Housing.Additional InformationSource: Manually maintained data, Housing Pro and QuickbooksContact: Irma Hollamby CainContact Phone: 480-858-2264Data Source Type: ExcelPreparation Method: Monthly values are calculated by determining the month each of the expenditures was for and retroactively accruing the funding use to the appropriate period. There are multiple, multistep excel worksheets that are used to balance between the specialty Housing Software, City Financial System and the HUD mandated reporting system. Additionally, it is important to note that Funding is allocated by Congress on the Federal Fiscal Year (October - September), the City operates on a Fiscal Year (July - June) and HUD provides funding on the Housing Authority in Calendar Year (January - December) funding increments. Therefore, the City must cross balance between three funding years.Publish Frequency: AnnuallyPublish Method: ManualData Dictionary

Graph and download economic data for Existing Home Sales (EXHOSLUSM495S) from Jul 2024 to Jul 2025 about headline figure, sales, housing, and USA.

This dataset contains the ratio of lower quartile/median house price to lower quartile/median earnings in England This dataset uses the median/lower quartile house price data sourced from ONS House Price Statistics for Small Areas (HPSSA) statistical release for years 2013-2015 and house price data sourced directly from Land Registry prior to 2013. This leads to slight differences in the distribution of affordability ratios before and after 2013 which should be noted if the dataset is used as a time series. It is planned to update the ratios with the HPSSA dataset for all years in the future. The house price data is then compared to the median/lower quartile income data of full time workers from the Annual Survey of Hours and Earnings (ASHE) produced by the ONS. This data was derived from Table 576 and 577, available for download as an Excel spreadsheet from the Live tables page (https://www.gov.uk/government/statistical-data-sets/live-tables-on-housing-market-and-house-prices). More details about the data sources are also available in the link provided.

The Uniform Appraisal Dataset (UAD) Aggregate Statistics Data File and Dashboards are the nation’s first publicly available datasets of aggregate statistics on appraisal records, giving the public new access to a broad set of data points and trends found in appraisal reports. The UAD Aggregate Statistics for Enterprise Single-Family, Enterprise Condominium, and Federal Housing Administration (FHA) Single-Family appraisals may be grouped by neighborhood characteristics, property characteristics and different geographic levels.DocumentationOverview (10/28/2024)Data Dictionary (10/28/2024)Data File Version History and Suppression Rates (12/18/2024)Dashboard Guide (2/3/2025)UAD Aggregate Statistics DashboardsThe UAD Aggregate Statistics Dashboards are the visual front end of the UAD Aggregate Statistics Data File. The Dashboards are designed to provide easy access to customized maps and charts for all levels of users. Access the UAD Aggregate Statistics Dashboards here.UAD Aggregate Statistics DatasetsNotes:Some of the data files are relatively large in size and will not open correctly in certain software packages, such as Microsoft Excel. All the files can be opened and used in data analytics software such as SAS, Python, or R.All CSV files are zipped.

This dataset includes Statistics Canada table 46-10-0026-01, titled “Immigrant status and selected admission categories for residential property owners in the census metropolitan areas of Toronto and Vancouver”. The table has been edited to include only geographies from British Columbia. The table is available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet. This data set was collected as part of the Canadian Housing Statistics Program by Statistics Canada. Geographies: Vancouver Census Metropolitan Area

Source: Manually maintained data, Housing Pro and QuickbooksContact: Irma Hollamby CainContact Phone: 480-858-2264Data Source Type: ExcelPreparation Method: Monthly values are calculated by determining the month each of the expenditures was for and retroactively accruing the funding use to the appropriate period. There are multiple, multistep excel worksheets that are used to balance between the specialty Housing Software, City Financial System and the HUD mandated reporting system. Additionally, it is important to note that Funding is allocated by Congress on the Federal Fiscal Year (October - September), the City operates on a Fiscal Year (July - June) and HUD provides funding on the Housing Authority in Calendar Year (January - December) funding increments. Therefore, the City must cross balance between three funding years.Publish Frequency: Annually

The dataset titled "Measures supporting affordable housing development" is a comprehensive collection of data pertaining to the affordability and development of housing. It is categorized under the domain of Housing and is tagged with keywords such as Affordability, Affordable Housing, Construction, Development, Finance, Housing Potential, Indicator, and property boundary. The dataset is available in PDF and Excel formats and was published on May 29, 2021. The data spans from January 1, 2019, to December 31, 2021, and covers OECD member countries. The dataset is open for access with certain usage limitations set by the OECD. The dataset is owned and published by the OECD and can be contacted via phone or fax for access-related queries. The dataset is in English and was last accessed on November 26, 2023. It does not contain data about individuals or identifiable individuals. The dataset is updated annually and covers OECD member countries in terms of geospatial resolution. It consists of 67 rows, 15 columns, and 516 data cells. The dataset is owned by The Organisation for Economic Co-operation and Development (OECD) and provides an overview of measures to property developers to finance the construction of new affordable housing. The dataset does not specify a license and was created on November 26, 2023, and last modified on March 28, 2025.

This dataset contains an amenity index for all Utah Census Places. Using Census data and other available datasets, an index for 'amenityness' was created. Following Ganning and Flint's previous research note, the index is calculated using physical amenities as well as socio-economic indicators (See: Ganning, Joanna Paulson, and Courtney G. Flint. “Constructing a Community-Level Amenity Index.” Society & Natural Resources 23, no. 12 (November 2, 2010): 1253–58. doi:10.1080/08941920903030132).

This index adds context to any study where an understanding of local, natural amenities is valued. It contains the following physical amenity variables: 1. Open Land 2. Open Water 3. Kapos Classification 4. Number of Recreation sites

It also includes key indicators which come from Census Data. 1. Employment Diversity 2. Median Household Income 3. Seasonal Housing 4. Population Growth 5. In-migration from out of state 6. In-migration from out of county 7. College education 8. New Housing Built 9. Housing Valued over $175,000 10. Median Rent 11. Median Housing Value 12. Employment in arts, entertainment, recreation, accommodation, and food services.

For more information on the calculations and variables, please read Ganning & Flint's research note and the ReadMe file linked to this dataset or the data dictionary within the excel spreadsheet as Tab 2.

Graph and download economic data for All-Transactions House Price Index for Utah (UTSTHPI) from Q1 1975 to Q1 2025 about UT, appraisers, HPI, housing, price index, indexes, price, and USA.

All data was collected in microsoft excel. All data was processed in IBM SPSS statistics. All graphs were constructed in Graphpad Prism.

Raw data outputs 1-18 Raw data output 1. Differentially expressed genes in AML CSCs compared with GTCs as well as in TCGA AML cancer samples compared with normal ones. This data was generated based on the results of AML microarray and TCGA data analysis. Raw data output 2. Commonly and uniquely differentially expressed genes in AML CSC/GTC microarray and TCGA bulk RNA-seq datasets. This data was generated based on the results of AML microarray and TCGA data analysis. Raw data output 3. Common differentially expressed genes between training and test set samples the microarray dataset. This data was generated based on the results of AML microarray data analysis. Raw data output 4. Detailed information on the samples of the breast cancer microarray dataset (GSE52327) used in this study. Raw data output 5. Differentially expressed genes in breast CSCs compared with GTCs as well as in TCGA BRCA cancer samples compared with normal ones. Raw data output 6. Commonly and uniquely differentially expressed genes in breast cancer CSC/GTC microarray and TCGA BRCA bulk RNA-seq datasets. This data was generated based on the results of breast cancer microarray and TCGA BRCA data analysis. CSC, and GTC are abbreviations of cancer stem cell, and general tumor cell, respectively. Raw data output 7. Differential and common co-expression and protein-protein interaction of genes between CSC and GTC samples. This data was generated based on the results of AML microarray and STRING database-based protein-protein interaction data analysis. CSC, and GTC are abbreviations of cancer stem cell, and general tumor cell, respectively. Raw data output 8. Differentially expressed genes between AML dormant and active CSCs. This data was generated based on the results of AML scRNA-seq data analysis. Raw data output 9. Uniquely expressed genes in dormant or active AML CSCs. This data was generated based on the results of AML scRNA-seq data analysis. Raw data output 10. Intersections between the targeting transcription factors of AML key CSC genes and differentially expressed genes between AML CSCs vs GTCs and between dormant and active AML CSCs or the uniquely expressed genes in either class of CSCs. Raw data output 11. Targeting desirableness score of AML key CSC genes and their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 12. CSC-specific targeting desirableness score of AML key CSC genes and their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 13. The protein-protein interactions between AML key CSC genes with themselves and their targeting transcription factors. This data was generated based on the results of AML microarray and STRING database-based protein-protein interaction data analysis. Raw data output 14. The previously confirmed associations of genes having the highest targeting desirableness and CSC-specific targeting desirableness scores with AML or other cancers’ (stem) cells as well as hematopoietic stem cells. These data were generated based on a PubMed database-based literature mining. Raw data output 15. Drug score of available drugs and bioactive small molecules targeting AML key CSC genes and/or their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 16. CSC-specific drug score of available drugs and bioactive small molecules targeting AML key CSC genes and/or their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 17. Candidate drugs for experimental validation. These drugs were selected based on their respective (CSC-specific) drug scores. CSC is the abbreviation of cancer stem cell. Raw data output 18. Detailed information on the samples of the AML microarray dataset GSE30375 used in this study.

This dataset includes Statistics Canada table 46-10-0029-01, titled “Property use of residential properties, by property type and residency ownership”. The table has been edited to include only geographies from British Columbia and to have the unique ID numbers added to the Census Subdivisions and Census Metropolitan Areas. The table is available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet. This data set was collected as part of the Canadian Housing Statistics Program by Statistics Canada. Geographies: British Columbia, Abbotsford-Mission, census metropolitan area, Abbotsford, Mission, Kelowna, census metropolitan area, Central Okanagan, Central Okanagan J, Kelowna, Lake Country, Peachland, West Kelowna, Vancouver, census metropolitan area, Anmore, Belcarra, Bowen Island, Burnaby, Coquitlam, Delta, Langley, city, Langley, municipal district, Lions Bay, Maple Ridge, Metro Vancouver A, New Westminster, North Vancouver, city, North Vancouver, municipal district, Pitt Meadows, Port Coquitlam, Port Moody, Richmond, Surrey, Vancouver, West Vancouver, White Rock, Victoria, census metropolitan area, Central Saanich, Colwood, Esquimalt, Highlands, Juan de Fuca (Part 1), Langford, Metchosin, North Saanich, Oak Bay, Saanich, Sidney, Sooke, Victoria, View Royal, British Columbia, outside of census metropolitan areas, Alberni-Clayoquot A, Alberni-Clayoquot B, Alberni-Clayoquot C, Alberni-Clayoquot D, Alberni-Clayoquot E, Alberni-Clayoquot F, Alert Bay, Armstrong, Ashcroft, Barriere, Bulkley-Nechako A, Bulkley-Nechako B, Bulkley-Nechako C, Bulkley-Nechako D, Bulkley-Nechako E, Bulkley-Nechako F, Bulkley-Nechako G, Burns Lake, Cache Creek, Campbell River, Canal Flats, Cariboo A, Cariboo B, Cariboo C, Cariboo D, Cariboo E, Cariboo F, Cariboo G, Cariboo H, Cariboo I, Cariboo J, Cariboo K, Cariboo L, Castlegar, Central Coast A, Central Coast C, Central Coast D, Central Coast E, Central Kootenay A, Central Kootenay B, Central Kootenay C, Central Kootenay D, Central Kootenay E, Central Kootenay F, Central Kootenay G, Central Kootenay H, Central Kootenay I, Central Kootenay J, Central Kootenay K, Chase, Chetwynd, Chilliwack, Clearwater, Clinton, Coldstream, Columbia-Shuswap A, Columbia-Shuswap B, Columbia-Shuswap C, Columbia-Shuswap D, Columbia-Shuswap E, Columbia-Shuswap F, Comox, Comox Valley A, Comox Valley B (Lazo North), Comox Valley C (Puntledge - Black Creek), Courtenay, Cowichan Valley A, Cowichan Valley B, Cowichan Valley C, Cowichan Valley D, Cowichan Valley E, Cowichan Valley F, Cowichan Valley G, Cowichan Valley H, Cowichan Valley I, Cranbrook, Creston, Cumberland, Dawson Creek, Duncan, East Kootenay A, East Kootenay B, East Kootenay C, East Kootenay E, East Kootenay F, East Kootenay G, Elkford, Enderby, Fernie, Fort St. James, Fort St. John, Fraser Lake, Fraser Valley A, Fraser Valley B, Fraser Valley C, Fraser Valley D, Fraser Valley E, Fraser Valley F, Fraser Valley G, Fraser Valley H, Fraser-Fort George A, Fraser-Fort George C, Fraser-Fort George D, Fraser-Fort George E, Fraser-Fort George F, Fraser-Fort George G, Fraser-Fort George H, Fruitvale, Gibsons, Gold River, Golden, Grand Forks, Granisle, Greenwood, Harrison Hot Springs, Hazelton, Hope, Houston, Hudson's Hope, Invermere, Juan de Fuca (Part 2), Kamloops, Kaslo, Kent, Keremeos, Kimberley, Kitimat, Kitimat-Stikine A, Kitimat-Stikine B, Kitimat-Stikine C (Part 1), Kitimat-Stikine C (Part 2), Kitimat-Stikine D, Kitimat-Stikine E, Kitimat-Stikine F, Kootenay Boundary A, Kootenay Boundary B / Lower Columbia-Old-Glory, Kootenay Boundary C / Christina Lake, Kootenay Boundary D / Rural Grand Forks, Kootenay Boundary E / West Boundary, Ladysmith, Lake Cowichan, Lantzville, Lillooet, Logan Lake, Lumby, Lytton, Mackenzie, Masset, McBride, Merritt, Midway, Montrose, Mount Waddington A, Mount Waddington B, Mount Waddington C, Mount Waddington D, Nakusp, Nanaimo, Nanaimo A, Nanaimo B, Nanaimo C, Nanaimo E, Nanaimo F, Nanaimo G, Nanaimo H, Nelson, New Denver, New Hazelton, North Coast A, North Coast C, North Coast D, North Coast E, North Cowichan, North Okanagan B, North Okanagan C, North Okanagan D, North Okanagan E, North Okanagan F, Northern Rockies, Okanagan-Similkameen A, Okanagan-Similkameen B, Okanagan-Similkameen C, Okanagan-Similkameen D, Okanagan-Similkameen E, Okanagan-Similkameen F, Okanagan-Similkameen G, Okanagan-Similkameen H, Oliver, One Hundred Mile House, Osoyoos, Parksville, Peace River B, Peace River C, Peace River D, Peace River E, Pemberton, Penticton, Port Alberni, Port Alice, Port Clements, Port Edward, Port Hardy, Port McNeill, Pouce Coupe, Powell River, Powell River A, Powell River B, Powell River C, Powell River D, Powell River E, Prince George, Prince Rupert, Princeton, Qualicum Beach, Queen Charlotte, Quesnel, Radium Hot Springs, Revelstoke, Rossland, Salmo, Salmon Arm, Saltspring Island, Sayward, Sechelt, Sicamous, Silverton, Slocan, Smithers, Southern Gulf Islands, Spallumcheen,...

Venezuela Consumer Price Index (CPI): Weights: Maracaibo: Housing Services excel Telephone data was reported at 3.900 % in 2013. This stayed constant from the previous number of 3.900 % for 2012. Venezuela Consumer Price Index (CPI): Weights: Maracaibo: Housing Services excel Telephone data is updated yearly, averaging 3.900 % from Dec 2007 (Median) to 2013, with 7 observations. The data reached an all-time high of 3.900 % in 2013 and a record low of 3.900 % in 2013. Venezuela Consumer Price Index (CPI): Weights: Maracaibo: Housing Services excel Telephone data remains active status in CEIC and is reported by Central Bank of Venezuela. The data is categorized under Global Database’s Venezuela – Table VE.I009: Consumer Price Index: Weights: Maracaibo: Dec2007=100.

Additional affordable dwellings by local authority district, England 1991-92 to 2016-17 This dataset describes the additions to the stock of affordable housing from the period 1991-92 to 2016-17, broken down by local authority district. Note that over that period, there have been numerous changes to the structure of local government, therefore some districts do not have values for the full series of years, only for those years when the corresponding local authority was in operation. Affordable housing is the sum of affordable rent, social rent, intermediate rent and affordable home ownership. Affordable homes are defined in line with the National Planning Policy Framework, published 27 March 2012, as housing units (or traveller pitches and bed spaces when describing a shared dwelling such as a hostel) provided to specified eligible households whose needs are not met by the market. Eligibility may be determined with regard to local authority allocations policies, local incomes and local house prices depending on the type of affordable housing. Affordable housing should include provisions to remain at an affordable price for future eligible households or for the subsidy to be recycled for alternative affordable housing provision. Affordable rented housing is a new form of social housing, introduced in 2011 as the main type of affordable housing supply. It may only be delivered with grant through the Affordable Homes Programme 2011-17 and other associated and subsequent programmes or without grant by local authority and other providers, where a contract or confirmation of the ability to charge an affordable rent is in place. Affordable rented homes are let by local authorities or private registered providers of social housing to households who are eligible for social rented housing. Affordable rent is subject to rent controls that require a rent of up to 80 per cent of the local market rent (including service charges, where applicable). Social rented housing is rented housing owned and managed by local authorities and private registered providers, for which target rents are determined through the national rent regime. It may also include rented housing managed by other persons and provided under equivalent rental arrangements to the above. Intermediate affordable housing is housing at prices and rents above those of social rent but below market price or rents, and which meet the criteria as set out in the definition for affordable housing. These can include equity loan products, shared ownership and intermediate rent. The data in this dataset were derived from Tables 1006C, 1006aC, 1007C and 1008C of the DCLG 'Live statistical tables', available in the form of Excel spreadsheets here. For further guidance see the Affordable Housing Supply: April 2016 to March 2017 England Statistical Release.

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.