Housing Starts in the United States decreased to 1307 Thousand units in August from 1429 Thousand units in July of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Maryland Total New Housing Units Authorized for Construction from 2010 to 2024. Source from the U.S. Department of Commerce, Bureau of the Census.

Starts and completions of new build dwellings in the UK, on a quarterly and annual basis, time series data

This dataset provides values for HOUSING STARTS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

New Home Sales in the United States increased to 800 Thousand units in August from 664 Thousand units in July of 2025. This dataset provides the latest reported value for - United States New Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The latest Construction Status Report shows that 10,614 social homes are currently onsite with an additional 13,996 homes at design and tender stage. In Quarter 4 2024, 80 new construction schemes (1,489 homes) were added to the pipeline. In total, the Construction Status Report provides details on 50,152 new-build social homes across 2,986 schemes. .hidden { display: none }

Housing Starts Single Family in the United States decreased to 890 Thousand units in August from 957 Thousand units in July of 2025. This dataset includes a chart with historical data for the United States Housing Starts Single Family.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Prince Edward Island; Nova Scotia; Newfoundland and Labrador ...), Housing estimates (3 items: Housing starts; Housing under construction; Housing completions ...), Type of unit (6 items: Total units; Semi-detached; Single-detached; Multiples ...).

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

Key Table Information.Table Title.Selected Housing Characteristics.Table ID.ACSDP1Y2024.DP04.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Data Profiles.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of ...

Housing Starts Multi Family in the United States decreased to 403 Thousand units in August from 453 Thousand units in July of 2025. This dataset includes a chart with historical data for the United States Housing Starts Multi Family.

Dataset Overview

This dataset contains real estate listings from Utah, comprising 4,440 entries and 14 columns. The data includes various attributes of properties such as type, description, year built, number of bedrooms and bathrooms, garage spaces, lot size, square footage, stories, listing price, and the date the property was last sold. The data was ethically mined and is to be used for educational and non-commercial purposes only.

Data Science Applications

Given the size of the dataset (4,440 entries) and the available columns, this dataset is well-suited for various data science applications, including but not limited to:

• Regression Analysis: Predict property listing prices based on features like square footage, number of bedrooms and bathrooms, year built, and lot size.
• Classification: Classify properties into different types or price ranges.
• Time Series Analysis: Analyze trends in property sales over time using the lastSoldOn column.
• Feature Engineering: Create new features such as price per square foot or age of the property at the time of sale to enhance predictive models.

Column Descriptors

• type: Type of property (e.g., single_family, land)
• text: Description of the property
• year_built: Year the property was built
• beds: Number of bedrooms
• baths: Total number of bathrooms
• baths_full: Number of full bathrooms
• baths_half: Number of half bathrooms
• garage: Number of garage spaces
• lot_sqft: Lot size in square feet
• sqft: Property size in square feet
• stories: Number of stories
• lastSoldOn: Date the property was last sold
• listPrice: Listing price of the property
• status: Current status of the property (e.g., for_sale)

Ethically Mined Data

This dataset was ethically mined from Realtor.com using an API provided by Apify. The data collection process ensured compliance with ethical standards and respect for the source of the information. The dataset is intended for educational and analytical purposes, promoting transparency and responsible data use.

Acknowledgements

• Apify: For providing the API used to mine the data.
• Realtor.com: For being the source of the data.
• DALL-E 3: For generating the thumbnail image for this dataset.

Housing Starts in Sweden decreased to 6.55 Thousand units in the third quarter of 2025 from 7.48 Thousand units in the second quarter of 2025. This dataset provides the latest reported value for - Sweden Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset contains multifamily housing sites in the City of Detroit meeting the following criteria:

The series Output price index of new homes, 2015=100, shows the development of the construction costs of new homes. This series is based on all categories of new homes. The construction costs referred to include the general costs and 'profit and risk' of the contractor, but exclude the land costs and costs of the project developer or broker. The basic material for this statistic is derived from data reported by municipalities to Statistics Netherlands (CBS) from building permits for new dwellings that they have issued.

Data available from: 1st quarter 2012

Status of figures: The figures remain for four quarters for the time being. They will then be definitively determined.

Changes as of 29 March 2024: Figures for Q4 2022 have been definitively established. In addition, the figures for the 4th quarter and the year 2023 have been added.

The index series in this table have 2015 as reference year (2015=100). In order to make the results of the index series more in line with current events, a so-called basic shift is implemented once every five years. Due to the implementation of FRIBS (Framework Regulation Integrating Business Statistics) in 2021, this time the basic shift will be postponed by one year to 2021=100. The subsequent base shift will take place again in a usual year, namely 2025=100. At the time of publication of the reporting period Q1 2024, such a base shift will take place and will be moved to the reference year 2021 (2021=100). The index series with reference 2021=100 will be published in new StatLine tables. This table will be discontinued and will no longer be updated. This table will remain available in the archive. The new tables 2021=100 will start with reporting period Q1 2018.

When will there be new figures? New figures for Q1 2024 will be released at the end of June 2024.

The Q1 2024 Construction Status Report shows that 9,179 social homes are currently onsite with an additional 15,848 homes at design and tender stage. In Quarter 1 2024, 121 new construction schemes (2,595 homes) were added to the pipeline. In total the Construction Status Report provides details on 43,795 new-build social homes across 2,570 schemes.

The Q2 2024 Construction Status Report shows that 10,465 social homes are currently onsite with an additional 16,614 homes at design and tender stage. In Quarter 2 2024, 212 new construction schemes (2,947 homes) were added to the pipeline.

Dataset Overview

This dataset comprises detailed real estate listings scraped from Realtor.com, providing a snapshot of various property types across Chicago. It includes 2,000 entries with information on property characteristics such as type, size, age, price, and features. This dataset was ethically collected using an API provided by Apify, ensuring all data scraping adhered to ethical standards.

Data Science Applications

This dataset is ideal for a variety of data science applications, including but not limited to: - Predictive Modeling: Forecast property prices based on various features like location, size, and age. - Market Analysis: Understand trends in real estate, including the types of properties being sold, pricing trends, and the influence of property features on market value. - Natural Language Processing: Analyze the textual descriptions provided for each listing to extract additional features or perform sentiment analysis. - Anomaly Detection: Identify unusual listings or potential outliers in the data, which could indicate errors in data collection or unique investment opportunities.

Column Descriptors

1. type: The type of property (e.g., single-family home, condo).
2. text: A textual description of the property.
3. year_built: The year in which the property was constructed.
4. beds: The number of bedrooms.
5. baths: Total number of bathrooms (including full and half).
6. baths_full: Number of full bathrooms.
7. baths_half: Number of half bathrooms.
8. garage: Garage capacity (number of cars).
9. lot_sqft: Size of the lot in square feet.
10. sqft: Living area size in square feet.
11. stories: Number of stories/floors in the property.
12. lastSoldPrice: The price at which the property was last sold.
13. soldOn: The date on which the property was last sold.
14. listPrice: The listing price of the property at the time of data collection.
15. status: The current status of the listing (e.g., for sale, sold).

Ethically Mined Data

This dataset was responsibly and ethically mined, adhering to all legal standards of data collection. The use of Apify's API ensures that the data collection process respects privacy and the platform's terms of service.

Acknowledgements

We thank Realtor.com for maintaining a comprehensive and accessible database, and Apify for providing the tools necessary for ethical data scraping. Their contributions have been invaluable in the creation of this dataset. Credits to Dall E3 for thumbnail image.

Usage Policy

This dataset is provided for non-commercial and educational purposes only. Users are encouraged to use this data to enhance learning, contribute to academic or personal projects, and develop skills in data science and real estate market analysis.