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Median price paid for residential property in England and Wales, by property type and administrative geographies. Annual data.
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TwitterThe median house price in *****, Atherton, California, was about *** million U.S. dollars. This made it the most expensive zip code in the United States in 2023. ***** Sagaponack, N.Y., was the runner-up with a median house price of about *** million U.S. dollars. Of the ** most expensive zip codes in the United States in 2026, six were in California.
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TwitterHouse prices in England have increased notably in the last 10 years, despite a slight decline in 2023. In December 2024, London retained its position as the most expensive regional market, with the average house price at ******* British pounds. According to the UK regional house price index, Northern Ireland saw the highest increase in house prices since 2023.
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TwitterThe UK House Price Index is a National Statistic.
Download the full UK House Price Index data below, or use our tool to https://landregistry.data.gov.uk/app/ukhpi?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=tool&utm_term=9.30_20_03_24" class="govuk-link">create your own bespoke reports.
Datasets are available as CSV files. Find out about republishing and making use of the data.
This file includes a derived back series for the new UK HPI. Under the UK HPI, data is available from 1995 for England and Wales, 2004 for Scotland and 2005 for Northern Ireland. A longer back series has been derived by using the historic path of the Office for National Statistics HPI to construct a series back to 1968.
Download the full UK HPI background file:
If you are interested in a specific attribute, we have separated them into these CSV files:
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price&utm_term=9.30_20_03_24" class="govuk-link">Average price (CSV, 9.4MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-prices-Property-Type-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average_price_property_price&utm_term=9.30_20_03_24" class="govuk-link">Average price by property type (CSV, 28MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Sales-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=sales&utm_term=9.30_20_03_24" class="govuk-link">Sales (CSV, 5MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Cash-mortgage-sales-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=cash_mortgage-sales&utm_term=9.30_20_03_24" class="govuk-link">Cash mortgage sales (CSV, 7MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/First-Time-Buyer-Former-Owner-Occupied-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=FTNFOO&utm_term=9.30_20_03_24" class="govuk-link">First time buyer and former owner occupier (CSV, 6.3MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/New-and-Old-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=new_build&utm_term=9.30_20_03_24" class="govuk-link">New build and existing resold property (CSV, 17MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index&utm_term=9.30_20_03_24" class="govuk-link">Index (CSV, 6.1MB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Indices-seasonally-adjusted-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=index_season_adjusted&utm_term=9.30_20_03_24" class="govuk-link">Index seasonally adjusted (CSV, 209KB)
https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Average-price-seasonally-adjusted-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=average-price_season_adjusted&utm_term=9.30_20_03_24" class="govuk-link">Average price seasonally adjusted (CSV, 218KB)
<a rel="external" href="https://publicdata.landregistry.gov.uk/market-trend-data/house-price-index-data/Repossession-2024-01.csv?utm_medium=GOV.UK&utm_source=datadownload&utm_campaign=repossession&utm_term=9.30_20_03_24" class
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A dataset comprising various variables around housing and demographics for the top 50 American cities by population.
Variables:
Zip Code: Zip code within which the listing is present.
Price: Listed price for the property.
Beds: Number of beds mentioned in the listing.
Baths: Number of baths mentioned in the listing.
Living Space: The total size of the living space, in square feet, mentioned in the listing.
Address: Street address of the listing.
City: City name where the listing is located.
State: State name where the listing is located.
Zip Code Population: The estimated number of individuals within the zip code. Data from Simplemaps.com.
Zip Code Density: The estimated number of individuals per square mile within the zip code. Data from Simplemaps.com.
County: County where the listing is located.
Median Household income: Estimated median household income. Data from the U.S. Census Bureau.
Latitude: Latitude of the zip code. ** Data from Simplemaps.com.**
Longitude: Longitude of the zip code. Data from Simplemaps.com.
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Quarterly house price data based on a sub-sample of the Regulated Mortgage Survey.
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Summary statistics for housing transactions by local authority in England and Wales, on an annual basis, updated quarterly using HM Land Registry Price Paid Data. Select values from the Year and Month dimensions for data for a 12-month period ending that month and year (e.g. selecting June and 2018 will return the twelve months to June 2018).
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Median price paid for residential property in England and Wales, for all property types by lower layer super output area. Annual data..
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Get up to date with the permitted use of our Price Paid Data:
check what to consider when using or publishing our Price Paid Data
If you use or publish our Price Paid Data, you must add the following attribution statement:
Contains HM Land Registry data © Crown copyright and database right 2021. This data is licensed under the Open Government Licence v3.0.
Price Paid Data is released under the http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government Licence (OGL). You need to make sure you understand the terms of the OGL before using the data.
Under the OGL, HM Land Registry permits you to use the Price Paid Data for commercial or non-commercial purposes. However, OGL does not cover the use of third party rights, which we are not authorised to license.
Price Paid Data contains address data processed against Ordnance Survey’s AddressBase Premium product, which incorporates Royal Mail’s PAF® database (Address Data). Royal Mail and Ordnance Survey permit your use of Address Data in the Price Paid Data:
If you want to use the Address Data in any other way, you must contact Royal Mail. Email address.management@royalmail.com.
The following fields comprise the address data included in Price Paid Data:
The October 2025 release includes:
As we will be adding to the October data in future releases, we would not recommend using it in isolation as an indication of market or HM Land Registry activity. When the full dataset is viewed alongside the data we’ve previously published, it adds to the overall picture of market activity.
Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.
Google Chrome (Chrome 88 onwards) is blocking downloads of our Price Paid Data. Please use another internet browser while we resolve this issue. We apologise for any inconvenience caused.
We update the data on the 20th working day of each month. You can download the:
These include standard and additional price paid data transactions received at HM Land Registry from 1 January 1995 to the most current monthly data.
Your use of Price Paid Data is governed by conditions and by downloading the data you are agreeing to those conditions.
The data is updated monthly and the average size of this file is 3.7 GB, you can download:
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Graph and download economic data for All-Transactions House Price Index for Massachusetts (MASTHPI) from Q1 1975 to Q3 2025 about MA, appraisers, HPI, housing, price index, indexes, price, and USA.
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TwitterThe median house prices in the most expensive zip codes in California reached as high as *** million U.S dollars. Atherton (94027), had the most expensive median house price, followed by Santa Barbara (93108), and Beverly Hills (90210). Six of the ranked zip codes were among the top ten most expensive zip codes in the United States in 2023.
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TwitterIn December 2024, the average house price in England was pricier than in any other country. This considerable disparity in average house prices is in no small part down to the country's capital city, where the average asking price was more than double that of the UK’s average. Even in London, for those who can afford a mortgage, the savings made through buying over renting can be beneficial. What drives house prices? Average house prices are affected by several factors, including economic growth, unemployment, and interest rates. Housing supply also plays a considerable role, with a shortage of supply leading to increased competition and an upward push in prices. Conversely, an excess of housing means prices fall to stimulate buyers. House prices still set to grow The housing market in the UK is expected to continue to grow in the next years. By 2029,.the annual number of housing transactions is set to reach *** million. With transactions on the rise, the average house price is also set to rise.
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TwitterThe FHFA House Price Index (FHFA HPI®) is the nation’s only collection of public, freely available house price indexes that measure changes in single-family home values based on data from all 50 states and over 400 American cities that extend back to the mid-1970s. The FHFA HPI incorporates tens of millions of home sales and offers insights about house price fluctuations at the national, census division, state, metro area, county, ZIP code, and census tract levels. FHFA uses a fully transparent methodology based upon a weighted, repeat-sales statistical technique to analyze house price transaction data. What does the FHFA HPI represent? The FHFA HPI is a broad measure of the movement of single-family house prices. The FHFA HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. The FHFA HPI serves as a timely, accurate indicator of house price trends at various geographic levels. Because of the breadth of the sample, it provides more information than is available in other house price indexes. It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas. U.S. Federal Housing Finance Agency, All-Transactions House Price Index for Connecticut [CTSTHPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CTSTHPI, August 2, 2023.
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This dataset contains information on 1000 properties in Australia, including location, size, price, and other details
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
If you're looking for a dataset on Australian housing data, this is a great option. This dataset contains information on over 1000 properties in Australia, including location, size, price, and other details. With this data, you can answer questions like What is the average price of a home in Australia?, What are the most popular type of homes in Australia?, and more
- This dataset can be used to predict hosing prices in Australia.
- This dataset can be used to find relationships between housing prices and location.
- This dataset can be used to find relationships between housing prices and features such as size, number of bedrooms, and number of bathrooms
If you use this dataset in your research, please credit the original authors. Data Source
License
See the dataset description for more information.
File: RealEstateAU_1000_Samples.csv | Column name | Description | |:--------------------|:---------------------------------------------------------------------------------------| | breadcrumb | A breadcrumb is a text trail that shows the user's location within a website. (String) | | category_name | The name of the category that the listing belongs to. (String) | | property_type | The type of property being listed. (String) | | building_size | The size of the property's building, in square meters. (Numeric) | | land_size | The size of the property's land, in square meters. (Numeric) | | preferred_size | The preferred size of the property, in square meters. (Numeric) | | open_date | The date that the property was first listed for sale. (Date) | | listing_agency | The agency that is listing the property. (String) | | price | The listing price of the property. (Numeric) | | location_number | The number that corresponds to the property's location. (Numeric) | | location_type | The type of location that the property is in. (String) | | location_name | The name of the location that the property is in. (String) | | address | The property's address. (String) | | address_1 | The first line of the property's address. (String) | | city | The city that the property is located in. (String) | | state | The state that the property is located in. (String) | | zip_code | The zip code that the property is located in. (String) | | phone | The listing agent's phone number. (String) | | latitude | The property's latitude. (Numeric) | | longitude | The property's longitude. (Numeric) | | product_depth | The depth of the product. (Numeric) | | bedroom_count | The number of bedrooms in the property. (Numeric) | | bathroom_count | The number of bathrooms in the property. (Numeric) | | parking_count | The number of parking spaces in the property. (Numeric) | | RunDate | The date that the listing was last updated. (Date) |
If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Jeff.
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TwitterVITAL SIGNS INDICATOR Home Prices (EC7)
FULL MEASURE NAME Home Prices
LAST UPDATED August 2019
DESCRIPTION Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.
DATA SOURCE Zillow Median Sale Price (1997-2018) http://www.zillow.com/research/data/
Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1997-2018; specific to each metro area) http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Median housing price estimates for the region, counties, cities, and zip code come from analysis of individual home sales by Zillow. The median sale price is the price separating the higher half of the sales from the lower half. In other words, 50 percent of home sales are below or above the median value. Zillow defines all homes as single-family residential, condominium, and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that you own in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums where the homeowners own shares in the corporation that owns the building, not the actual units themselves.
For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Home sales prices are not reliably available for Houston, because Texas is a non-disclosure state. For more information on non-disclosure states, see: http://www.zillow.com/blog/chronicles-of-data-collection-ii-non-disclosure-states-3783/
Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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TwitterIn 2023, Sagaponack, NY (zip code *****) was the zip code that witnessed the highest luxury house price increase in the United States. Year-on-year, prices in that zip code increased by ** percent. Ross, CA (zip code *****) stood at the other end of the scale, with a decline of ** percent.
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TwitterAnnual mean and median property prices calculated by the GLA from Price Paid Data published on Land Registry website. Number of property sales also included. Data has been aggregated to Borough, Ward, MSOA, LSOA, Postcode Districts and Postcode Sectors. Caution should be used when analysing figures based on a low number of sales. Price Paid Data provides information on every residential property sale in England and Wales that has been lodged with HM Land Registry for registration. Download full price paid data from the Land Registry. Click on the image below to access an interactive dashboard using some of the data available from this page.
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TwitterVITAL SIGNS INDICATOR
Home Prices (EC7)
FULL MEASURE NAME
Home Prices
LAST UPDATED
December 2022
DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.
DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021
California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021
US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021
Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021
US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.
For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.
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TwitterVITAL SIGNS INDICATOR
Home Prices (EC7)
FULL MEASURE NAME
Home Prices
LAST UPDATED
December 2022
DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.
DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021
California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021
US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021
Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021
US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.
For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.
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License information was derived automatically
These data were developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. .
For a deep dive into the data model including every specific metric, see the ACS 2018-2022 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e22Estimate from 2018-22 ACS_m22Margin of Error from 2018-22 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_22Change, 2010-22 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2018-2022). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2018-2022Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/3b86ee614e614199ba66a3ff1ebfe3b5/about
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Median price paid for residential property in England and Wales, by property type and administrative geographies. Annual data.