100+ datasets found
  1. T

    United States MBA 30-Yr Mortgage Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 9, 2025
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    TRADING ECONOMICS (2025). United States MBA 30-Yr Mortgage Rate [Dataset]. https://tradingeconomics.com/united-states/mortgage-rate
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Jul 9, 2025
    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 5, 1990 - Jul 18, 2025
    Area covered
    United States
    Description

    Fixed 30-year mortgage rates in the United States averaged 6.84 percent in the week ending July 18 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  2. T

    United States 30-Year Mortgage Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 17, 2025
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    TRADING ECONOMICS (2025). United States 30-Year Mortgage Rate [Dataset]. https://tradingeconomics.com/united-states/30-year-mortgage-rate
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jul 17, 2025
    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
    Apr 1, 1971 - Jul 17, 2025
    Area covered
    United States
    Description

    30 Year Mortgage Rate in the United States increased to 6.75 percent in July 17 from 6.72 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

  3. T

    United States Fed Funds Interest Rate

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 14, 2025
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    TRADING ECONOMICS (2025). United States Fed Funds Interest Rate [Dataset]. https://tradingeconomics.com/united-states/interest-rate
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Jul 14, 2025
    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
    Aug 4, 1971 - Jun 18, 2025
    Area covered
    United States
    Description

    The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  4. T

    Sweden Interest Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 8, 2025
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    TRADING ECONOMICS (2025). Sweden Interest Rate [Dataset]. https://tradingeconomics.com/sweden/interest-rate
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    May 8, 2025
    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
    May 26, 1994 - Jun 18, 2025
    Area covered
    Sweden
    Description

    The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  5. T

    United States MBA Mortgage Applications

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 23, 2025
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    TRADING ECONOMICS (2025). United States MBA Mortgage Applications [Dataset]. https://tradingeconomics.com/united-states/mortgage-applications
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Jul 23, 2025
    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 12, 1990 - Jul 18, 2025
    Area covered
    United States
    Description

    Mortgage Application in the United States increased by 0.80 percent in the week ending July 18 of 2025 over the previous week. This dataset provides - United States MBA Mortgage Applications - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  6. Methodology for Determining Credit Risk Scenarios for Stress-Testing...

    • catalog.data.gov
    • datasets.ai
    Updated Feb 10, 2025
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    Federal Housing Finance Agency (2025). Methodology for Determining Credit Risk Scenarios for Stress-Testing Mortgage Related Assets [Dataset]. https://catalog.data.gov/dataset/methodology-for-determining-credit-risk-scenarios-for-stress-testing-mortgage-related-asse
    Explore at:
    Dataset updated
    Feb 10, 2025
    Dataset provided by
    Federal Housing Finance Agencyhttps://www.fhfa.gov/
    Description

    The FHFA stress test is updated each quarter according to objective rules derived from fundamental economic relationships. These rules affect a dynamic adjustment to the severity of the stress test that accounts for current economic conditions, specifically the current level of house prices relative to the ongoing house price cycle. The stress test incorporates different house-price level (HPI) stress paths for each state, thus accounting for the fact that house price cycles can differ significantly from one state or region to another. The severity of the economic stress imposed by the test, as measured by the projected percentage drop in HPI, changes over time for each state corresponding to the deviation of current HPI from its long-run trend. As a result of this design, the FHFA stress test will produce countercyclical economic capital requirements, in that the estimates of potential losses on new mortgage loan originations increase during economic expansions, as current HPI rises above its long-term trend, and decrease during economic contractions, as current HPI falls to or below trend. The dynamic adjustment feature of the stress test allows that it will accommodate any size current house price cycle, even those of greater amplitude than any observed previously. Further, the severity of the stress test is calibrated to produce economic capital requirements that are sufficient, as of the day of origination, to fully capitalize the mortgage assets for the life of those assets.

  7. Canada Mortgage and Housing Corporation, conventional mortgage lending rate,...

    • www150.statcan.gc.ca
    • thelearningbarn.org
    • +4more
    Updated Jul 17, 2025
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    Government of Canada, Statistics Canada (2025). Canada Mortgage and Housing Corporation, conventional mortgage lending rate, 5-year term [Dataset]. http://doi.org/10.25318/3410014501-eng
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    Dataset updated
    Jul 17, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...).

  8. e

    Survey of Mortgage Lenders, 2001 - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Oct 22, 2023
    + more versions
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    (2023). Survey of Mortgage Lenders, 2001 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/a73d2ac0-0233-5716-b62d-b6be6a92ab31
    Explore at:
    Dataset updated
    Oct 22, 2023
    Description

    Abstract copyright UK Data Service and data collection copyright owner.The Survey of Mortgage Lenders (SML) was launched on 1st April 1992 to succeed the 5% Sample Survey of Building Society Mortgage Completions (BSM) (See GN:33191). The aims were to improve the survey in three principal ways: a) to broaden the range of institutions surveyed to incorporate other mortgage lenders in addition to building societies and Abbey National. With the entry of the high street banks and then the centralised lenders into the mortgage market, information provided by the building societies no longer represented the whole market in the way it did when the BSM was set up in the 1960s. b) to extend its coverage to include further advances, remortgages and top-up loans in addition to first mortgages. c) to increase the level of detail on the questionnaire especially with respect to the characteristics of the mortgage loan. An important consideration for users of the data is that the SML figures allow continuity with the BSM survey results to be maintained for a reasonable period. Main Topics: Financial institution code, date mortgage completed, whether dwelling is wholly or partly occupied by borrower. Mortgage amount, type of advance, whether solely for purchase of property, period of mortgage, gross rate of interest, whether the interest charged is fixed or variable rate, whether interest payments are discounted or deferred, repayment method, source of mortgage business, purchase price and whether discounted in any way, location of dwelling, whether new, age of dwelling, type of dwelling, number of habitable rooms, number, sex and age of borrowers, basic income of main borrower, other income and total income on which mortgage is based, whether applicant previously owner occupier, previous tenure. The institutions are divided into four strata according to the size of their assets. All the largest were asked to complete questionnaires on a sample of 5 per cent of their new mortgage advances. Mortgages are included if their reference numbers end in specified digits chosen so that every twentieth mortgage is selected. Institutions in the next stratum are arranged in order of size of assets and alternate institutions chosen each of which are asked to complete questionnaires on 10 per cent of their mortgages. In the next stratum 20 per cent of the mortgages of every fourth institution are obtained. The smallest institutions are completely excluded.

  9. T

    Mexico Interest Rate

    • tradingeconomics.com
    • fr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 26, 2025
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    TRADING ECONOMICS (2025). Mexico Interest Rate [Dataset]. https://tradingeconomics.com/mexico/interest-rate
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Jun 26, 2025
    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
    Oct 14, 2005 - Jun 26, 2025
    Area covered
    Mexico
    Description

    The benchmark interest rate in Mexico was last recorded at 8 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. e

    Map Viewing Service (WMS) of the dataset: Program of general interest in...

    • data.europa.eu
    wms
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    Map Viewing Service (WMS) of the dataset: Program of general interest in habitat improvement [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-9170d6c2-9816-4fac-a8b9-87b8696ab573
    Explore at:
    wmsAvailable download formats
    Description

    Established in 1977, the programmed habitat improvement operations (OPAH) have been the main tool for the rehabilitation of urban centres and rural towns for the past 30 years. Other tools have been created to respond to territorial, technical and social specificities: declination of OPAHs (rural, urban, degraded condominiums), General Interest Programmes (GIPs) and Thematic Social Programmes (PST).When the planned intervention in a given area, generally large — large agglomeration, extensive habitat basin, or even department, these territories do not have significant urban and social dysfunctions, justifying an overall project — is a particular problem to be dealt with, social or technical, OPAH is not an adequate tool, and should be preferred to it the procedure of the Programme of General Interest (PGI), regulated by Article R 327-1 of the Code de la construction et de l’habitation (CCH).The general interest programme (PIG) is an action programme initiated by local and regional authorities benefiting from an agreement for the delegation of stone aid. It aims to provide solutions to specific problems relating to the improvement of housing in housing units or buildings on different scales (agglomeration, housing basin, canton, country or even department). Thus, the scope of intervention can be the housing of students, young workers, the elderly or the disabled, the reduction of the number of vacant dwellings, the increase in the supply of social housing or the fight against diffuse unhealthiness. In addition, exceptional situations resulting from a disaster, whether natural or not, may be dealt with within the framework of a GIP. The duration of the GIP is free, at the discretion of the local authorities, taking into account the local context and issues: one year, 3 years or more if a contractual framework is defined in advance between the programme partners. The data does not contain the old IMPs that are otherwise archived.For the record: the public interest programme must be distinguished from the project of general interest, also known as the GIP, provided for by the Urban Planning Code. update on 12/09/2019

  11. f

    Japan Interest Rate

    • focus-economics.com
    excel, flat file, pdf
    Updated Feb 1, 2023
    + more versions
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    FocusEconomics S.L.U. (2023). Japan Interest Rate [Dataset]. https://www.focus-economics.com/country-indicator/japan/interest-rate
    Explore at:
    excel, flat file, pdfAvailable download formats
    Dataset updated
    Feb 1, 2023
    Authors
    FocusEconomics S.L.U.
    Time period covered
    1980 - 2028
    Area covered
    Japan
    Description

    FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Japan Interest Rate.

  12. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - South Africa

    • datarade.ai
    .csv
    Updated Jan 15, 2022
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    Geolytica (2022). Geolytica POIData.xyz Points of Interest (POI) Geo Data - South Africa [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-sou-geolytica-14c4
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Jan 15, 2022
    Dataset authored and provided by
    Geolytica
    Area covered
    South Africa
    Description

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The South Africa POI Dataset is one of our worldwide POI datasets with over 98% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The core attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 8 poi_tel 67 formatted_address 100 main_category 98 latitude 100 longitude 100 neighborhood 1 source_url 43 email 8 opening_hours 47

    The data may be visualized on a map at https://store.poidata.xyz/za and a data sample may be downloaded at https://store.poidata.xyz/datafiles/za_sample.csv

  13. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Taiwan

    • datarade.ai
    .csv
    Updated Sep 20, 2021
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    Geolytica (2021). Geolytica POIData.xyz Points of Interest (POI) Geo Data - Taiwan [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-taiwan-geolytica
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Sep 20, 2021
    Dataset authored and provided by
    Geolytica
    Area covered
    Taiwan
    Description

    https://store.poidata.xyz/tw

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Taiwan POI Dataset is one of our worldwide POI datasets with over 99% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The core attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 7 poi_tel 63 formatted_address 100 main_category 98 latitude 100 longitude 100 neighborhood 7 source_url 44 email 2 opening_hours 49

    The dataset may be viewed online at https://store.poidata.xyz/tw and a data sample may be downloaded at https://store.poidata.xyz/datafiles/tw_sample.csv

  14. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Italy

    • datarade.ai
    .csv
    Share
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    Geolytica, Geolytica POIData.xyz Points of Interest (POI) Geo Data - Italy [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-italy-geolytica
    Explore at:
    .csvAvailable download formats
    Dataset authored and provided by
    Geolytica
    Area covered
    Italy
    Description

    https://store.poidata.xyz/it

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Italian POI Dataset is one of our worldwide POI datasets with over 98% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The core attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 8 poi_tel 49 formatted_address 100 main_category 99 latitude 100 longitude 100 neighborhood 11 source_url 38 email 7 opening_hours 32

    The dataset may be viewed online at https://store.poidata.xyz/it and a data sample may be downloaded at https://store.poidata.xyz/datafiles/it_sample.csv

  15. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Spain

    • datarade.ai
    .csv
    Updated May 18, 2022
    Share
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    Geolytica (2022). Geolytica POIData.xyz Points of Interest (POI) Geo Data - Spain [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-spain-geolytica
    Explore at:
    .csvAvailable download formats
    Dataset updated
    May 18, 2022
    Dataset authored and provided by
    Geolytica
    Area covered
    Spain
    Description

    https://store.poidata.xyz/es

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Spain POI Dataset is one of our worldwide POI datasets with over 98% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The core attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 9 poi_tel 54 formatted_address 100 main_category 99 latitude 100 longitude 100 neighborhood 5 source_url 42 email 6 opening_hours 46

    The dataset may be viewed online at https://store.poidata.xyz/es and a data sample may be downloaded at https://store.poidata.xyz/datafiles/es_sample.csv

  16. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Colombia

    • datarade.ai
    .csv
    Share
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    Geolytica, Geolytica POIData.xyz Points of Interest (POI) Geo Data - Colombia [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-col-geolytica
    Explore at:
    .csvAvailable download formats
    Dataset authored and provided by
    Geolytica
    Area covered
    Colombia
    Description

    https://store.poidata.xyz/co

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Colombia POI Dataset is one of our worldwide POI datasets with over 90% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The main attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 5 poi_tel 43 formatted_address 100 main_category 99 latitude 100 longitude 100 neighborhood 3 source_url 29 email 4 opening_hours 41

    A data sample may be downloaded at https://store.poidata.xyz/datafiles/co_sample.csv and the data may be previewed on a map at https://store.poidata.xyz/co

  17. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Chile

    • datarade.ai
    .csv
    Updated Apr 3, 2022
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    Geolytica (2022). Geolytica POIData.xyz Points of Interest (POI) Geo Data - Chile [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-chile-geolytica
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    .csvAvailable download formats
    Dataset updated
    Apr 3, 2022
    Dataset authored and provided by
    Geolytica
    Area covered
    Chile
    Description

    https://store.poidata.xyz/cl

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Chile POI Dataset is one of our worldwide POI datasets with over 90% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The main attribute coverage is as follows:

    Poi Field Data Coverage (%) poi_name 100 brand 4 poi_tel 43 formatted_address 100 main_category 93 latitude 100 longitude 100 neighborhood 6 source_url 37 email 5 opening_hours 38

    A data sample may be downloaded at https://store.poidata.xyz/datafiles/cl_sample.csv and the data may be previewed on a map at https://store.poidata.xyz/cl

  18. d

    Geolytica POIData.xyz Points of Interest (POI) Geo Data - Iran

    • datarade.ai
    .csv
    Updated Mar 22, 2022
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    Geolytica (2022). Geolytica POIData.xyz Points of Interest (POI) Geo Data - Iran [Dataset]. https://datarade.ai/data-products/geolytica-poidata-xyz-points-of-interest-poi-geo-data-iran-geolytica
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Mar 22, 2022
    Dataset authored and provided by
    Geolytica
    Area covered
    Iran
    Description

    https://store.poidata.xyz/ir

    Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

    We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The Iran POI Dataset is one of our worldwide POI datasets with over 98% coverage.

    This is our process flow:

    Our machine learning systems continuously crawl for new POI data
    Our geoparsing and geocoding calculates their geo locations
    Our categorization systems cleanup and standardize the datasets
    Our data pipeline API publishes the datasets on our data store
    

    POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

    Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

    In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

    We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

    The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

    The core attribute coverage is as follows: Poi Field Data Coverage (%) poi_name 100 brand 3 poi_tel 48 formatted_address 100 main_category 100 latitude 100 longitude 100 neighborhood 3 source_url 10 email 1 opening_hours 44

    The dataset may be viewed online at https://store.poidata.xyz/ir and a data sample may be downloaded at https://store.poidata.xyz/datafiles/ir_sample.csv

  19. Database of forecasts for the UK economy

    • gov.uk
    • s3.amazonaws.com
    Updated Apr 17, 2024
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    HM Treasury (2024). Database of forecasts for the UK economy [Dataset]. https://www.gov.uk/government/statistics/database-of-forecasts-for-the-uk-economy
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    Dataset updated
    Apr 17, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    HM Treasury
    Area covered
    United Kingdom
    Description

    Each month we publish independent forecasts of key economic and fiscal indicators for the UK economy. Forecasts before 2010 are hosted by The National Archives.

    We began publishing comparisons of independent forecasts in 1986. The first database brings together selected variables from those publications, averaged across forecasters. It includes series for Gross Domestic Product, the Consumer Prices Index, the Retail Prices Index, the Retail Prices Index excluding mortgage interest payments, Public Sector Net Borrowing and the Claimant Count. Our second database contains time series of independent forecasts for GDP growth, private consumption, government consumption, fixed investment, domestic demand and net trade, for 26 forecasters with at least 10 years’ worth of submissions since 2010.

    We’d welcome feedback on how you find the database and any extra information that you’d like to see included. Email your comments to Carter.Adams@hmtreasury.gov.uk.

  20. e

    Simple download service (Atom) of the dataset: Public interest programmes in...

    • data.europa.eu
    unknown
    + more versions
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    Simple download service (Atom) of the dataset: Public interest programmes in Haute-Savoie [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-4628688e-0b4d-46af-8e5b-561565dd31b4
    Explore at:
    unknownAvailable download formats
    Description

    Established in 1977, the programmed habitat improvement operations (OPAH) have been the main tool for the rehabilitation of urban centres and rural towns for the past 30 years. Other tools have been created to respond to territorial, technical and social specificities: declination of OPAHs (rural, urban, degraded condominiums), General Interest Programmes (GIPs) and Thematic Social Programmes (PST).When the planned intervention in a given area, generally large — large agglomeration, extensive habitat basin, or even department, these territories do not have significant urban and social dysfunctions, justifying an overall project — is a particular problem to be dealt with, social or technical, OPAH is not an adequate tool, and should be preferred to it the procedure of the Programme of General Interest (PGI), regulated by Article R 327-1 of the Code de la construction et de l’habitation (CCH).The general interest programme (PIG) is an action programme initiated by local and regional authorities benefiting from an agreement for the delegation of stone aid. It aims to provide solutions to specific problems relating to the improvement of housing in housing units or buildings on different scales (agglomeration, housing basin, canton, country or even department). Thus, the scope of intervention can be the housing of students, young workers, the elderly or the disabled, the reduction of the number of vacant dwellings, the increase in the supply of social housing or the fight against diffuse unhealthiness. In addition, exceptional situations resulting from a disaster, whether natural or not, may be dealt with within the framework of a GIP. The duration of the GIP is free, at the discretion of the local authorities, taking into account the local context and issues: one year, 3 years or more if a contractual framework is defined in advance between the programme partners. The data does not contain the old IMPs that are otherwise archived.For the record: the public interest programme must be distinguished from the project of general interest, also known as the GIP, provided for by the Urban Planning Code.

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TRADING ECONOMICS (2025). United States MBA 30-Yr Mortgage Rate [Dataset]. https://tradingeconomics.com/united-states/mortgage-rate

United States MBA 30-Yr Mortgage Rate

United States MBA 30-Yr Mortgage Rate - Historical Dataset (1990-01-05/2025-07-18)

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4 scholarly articles cite this dataset (View in Google Scholar)
xml, excel, json, csvAvailable download formats
Dataset updated
Jul 9, 2025
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 5, 1990 - Jul 18, 2025
Area covered
United States
Description

Fixed 30-year mortgage rates in the United States averaged 6.84 percent in the week ending July 18 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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