5 datasets found
  1. d

    Apartment Market Rent Prices by Census Tract

    • catalog.data.gov
    • data.seattle.gov
    • +1more
    Updated Mar 29, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). Apartment Market Rent Prices by Census Tract [Dataset]. https://catalog.data.gov/dataset/apartment-market-rent-prices-by-census-tract
    Explore at:
    Dataset updated
    Mar 29, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Displacement risk indicator classifying census tracts according to apartment rent prices in census tracts. We classify apartment rent along two dimensions:The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development

  2. g

    Apartment Market Rent Prices by Census Tract | gimi9.com

    • gimi9.com
    Updated Oct 23, 2024
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    (2024). Apartment Market Rent Prices by Census Tract | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_apartment-market-rent-prices-by-census-tract
    Explore at:
    Dataset updated
    Oct 23, 2024
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.

  3. Condominium Comparable Rental Income in NYC

    • kaggle.com
    Updated Oct 30, 2020
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    Jin Bonnie (2020). Condominium Comparable Rental Income in NYC [Dataset]. https://www.kaggle.com/jinbonnie/condominium-comparable-rental-income-in-nyc/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 30, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Jin Bonnie
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New York
    Description

    If you think the dataset is useful please vote for it, it's an assignment from my data science class, I'll be appreciate! :))

    Context

    The Department of Finance (DOF) is required by NY State law to value condominiums or cooperatives as if they were residential rental apartment buildings. DOF uses income information from rental properties similar in physical features and location to the condominiums or cooperatives. DOF applies this income data to the condominium or cooperative to determine its value in the same way DOF values rental apartment buildings. This report includes information at a condominium suffix level which represents a subdivision of the condominium since DOF values condominiums at a suffix level. A condominium may have more than one suffix.

    Content

    This data set contains the reports from 2012-2018. Boro-Block-Lot
    The Borough-Block-Lot location of the subject condominium. The lot identifies the condominium billing lot generally associated with the condominium management organization. Address The Street Address of the property Neighborhood
    Department of Finance determines the neighborhood name in the course of valuing properties. The common name of the neighborhood is generally the same as the name Finance designates. However, there may be slight differences in neighborhood boundary lines. Building Classification The Building Class code is used to describe a property’s use. This report includes the two character code as well as the description of the building class. Total Units Total number of units in the building Year Built
    The year the building was built Gross SqFt
    Gross square footage of the building Estimated Gross Income
    Estimated Income per SquareFoot * Gross SquareFoot Estimated Expense Estimated Expense per SquareFoot * Gross SquareFoot Net Operating Income Estimated Gross Income-Estimated Expense Full Market Value Current year’s total market value of the land and building Report Year

    Acknowledgements

    Agency: Department of Finance (DOF) Source: NYC open data

  4. Orlando Neighborhood

    • kaggle.com
    Updated Oct 7, 2022
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    Sebastian Giovannini (2022). Orlando Neighborhood [Dataset]. https://www.kaggle.com/datasets/sgiov95/orlando-neighborhood
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 7, 2022
    Dataset provided by
    Kaggle
    Authors
    Sebastian Giovannini
    Area covered
    Orlando
    Description

    This dataset is a snapshot from October 2022 of all 48 homes in a section of a neighborhood nearby a large university in Central Florida. All of the homes are single family homes featuring a garage, a driveway, and a fenced-in backyard. Data was gathered by hand (keyboard) via a collection of sites, including Zillow, Realtor, Redfin, Trulia, and Orange County Property Appraiser. All homes were built in the same year in the early 2000's and feature central air and all other utilities typical of contemporary suburban homes in the United States. The area is close to a university and a large portion of renters are college students and young professionals, as well as families and older adults.

    There are 30 columns:

    • HID: House ID, a unique identifier for each house (int from 1 to 48, not the actual address number) -Sqft: The Square Footage of the Interior of the house (int) -LandSqft: The Total Square Footage of the land (int) -Neighbors: The number of homes directly adjacent to each house (int) -Stories: The number of stories in each house (int) -Pool: Does the house have a pool (int, 0 for 'No', 1 for 'Yes') -Bedrooms: The number of bedrooms in each house (int) -Bathrooms: The number of bathrooms (full or half) in each house (int) -DateLastSold: The date on which the house was last sold (datetime) -PropertyTaxes2022: The annual property taxes for 2022 (float) -OwnedByBank: Is the house owned by a bank (int, 0 for 'No', 1 for 'Yes') -OuterPortion: Is the house on the Outer Portion of the Neighborhood (int, 0 for 'No', 1 for 'Yes') -NextToLoudRoad: Is the house directly adjacent to a loud road (int, 0 for 'No', 1 for 'Yes') -PriceLastSold: Price that the house was last sold for (float) -Zestimate: Zillow's Price Estimate for the house (float) -RentZestimate: Zillow's Estimate for the Monthly Price of rent for the house (float) -RealtorcomEstimate: Realtor dot com's Estimate for the house (float) -RedfinEstimate: Redfin's Estimate for the house (float) -TruliaEstimate: Trulia's Estimate for the house (float) -OCPALandValue2022: The Land Value on the county's 2022 records (float) -OCPABuildingValue2022: The Building Value on the county's 2022 records (float) -OCPAFeaturesValue2022: The Features Value on the county's 2022 records (float) -OCPAMarketValue2022: The Market Value on the county's 2022 records (float) -OCPAAssessedValue2022: The Assessed Value on the county's 2022 records (float), AKA what homeowners are taxed on -OCPALandValue2021: The Land Value on the county's 2021 records (float) -OCPABuildingValue2021: The Building Value on the county's 2021 records (float) -OCPAFeaturesValue2021: The Features Value on the county's 2021 records (float) -OCPAMarketValue2021: The Market Value on the county's 2021 records (float) -OCPAAssessedValue2021: The Assessed Value on the county's 2021 records (float), AKA what homeowners are taxed on -Notes: any notes on any of the homes (str)

    Note that while the dataset is exhaustive in that it has all of the houses, some homes are missing some columns, typically because a home did not feature a estimate on a site or the one home not found on the property appraiser's site. This also is therefore not a randomized dataset, so the only population of homes that it can be used to infer on are those within this specific portion of the neighborhood. Personally, I am going to use the dataset to practice a couple of aspects of real-world data: Cleaning, Imputing, and Exploratory Data Analysis. Mainly, I want to compare different approaches to filling in the missing values of the dataset, then do some Model Building with some additional Dimensionality Reduction.

  5. v

    Non-market housing

    • opendata.vancouver.ca
    • vancouver.opendatasoft.com
    csv, excel, geojson +1
    Updated Jul 28, 2025
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    (2025). Non-market housing [Dataset]. https://opendata.vancouver.ca/explore/dataset/non-market-housing/
    Explore at:
    excel, json, csv, geojsonAvailable download formats
    Dataset updated
    Jul 28, 2025
    License

    https://opendata.vancouver.ca/pages/licence/https://opendata.vancouver.ca/pages/licence/

    Description

    This dataset contains data of non-market housing projects - both the buildings owned by City of Vancouver, and the buildings provided by other agencies. Non-market housing is for low and moderate income singles and families, often subsidized through a variety of ways, including senior government support. This housing is managed through various operators, including the public, non-profit, co-op, and urban indigenous sectors. Non-market housing is located throughout Vancouver in the forms of social, supportive, and co-op housing. This dataset includes temporary modular housing, which are demountable structures, not permanently affixed to land and assembled within months. The inventory does not include the following types of housing:Special Needs Residential Facilities - includes community care facilities providing licensed care services, and group residences providing housing as required by law, rehabilitative programs, or temporary housingSingle Room Accommodation - privately-owned single room occupancy (SRO) hotels, rooming houses, and other housing with rooms less than 320 square feet, typically featuring units with a basic cooking setup and shared bathroomsShelters - provide temporary beds, meals, and services to the city's homeless population NoteUnit total (and breakdown) of projects could change over the course of development and are not captured real timeHousing projects with "proposed", "approved" and "under construction" status may not contain unit number breakdown by "Design"Housing projects with "proposed", "approved" and "under construction" status may not contain information on operator names or typeUnit total is the sum of clientele groups (families, seniors, and others) Data currencyThis dataset is updated weekly. Data accuracyData for this dataset is amalgamated from a number of sources. It is possible that some information may not be shown because of data synchronization issues. There may be some loss of quality from data entry errors.Non-housing market projects for which geographic coordinates are not available yet will not show up on the map or in the spatial formats. For a complete list, please consult the XLS or CSV formats. Websites for further informationSocial and market rental housingFind social and co-op housing in Vancouver

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City of Seattle ArcGIS Online (2025). Apartment Market Rent Prices by Census Tract [Dataset]. https://catalog.data.gov/dataset/apartment-market-rent-prices-by-census-tract

Apartment Market Rent Prices by Census Tract

Explore at:
Dataset updated
Mar 29, 2025
Dataset provided by
City of Seattle ArcGIS Online
Description

Displacement risk indicator classifying census tracts according to apartment rent prices in census tracts. We classify apartment rent along two dimensions:The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development

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