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Description:

A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to mainroad, etc. The dataset is small yet, it's complexity arises due to the fact that it has strong multicollinearity. Can you overcome these obstacles & build a decent predictive model?

Acknowledgement:

Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. J. Environ. Economics and Management 5, 81–102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t a single & multiple feature.
• Also evaluate the models & compare thier respective scores like R2, RMSE, etc.

Housing Index in the United Kingdom increased to 517.10 points in October from 514.20 points in September of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in Hong Kong increased to 143.46 points in November 23 from 142.49 points in the previous week. This dataset provides - Hong Kong House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average House Prices in the United States increased to 534100 USD in August from 478200 USD in July of 2025. This dataset includes a chart with historical data for the United States New Home Average Sales Price.

This dataset provides, on a systematic basis, gridded population densities, rents, real estate prices, and transport times (both in public transport and private car) in 192 cities across the world.

House Price Index YoY in the United States decreased to 1.70 percent in September from 2.40 percent in August of 2025. This dataset includes a chart with historical data for the United States FHFA House Price Index YoY.

Housing Index in China remained unchanged at -2.20 percent in October. This dataset provides the latest reported value for - China Newly Built House Prices YoY Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Housing Index in the United States decreased to 435.40 points in September from 435.60 points in August of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Housing Index in Germany increased to 220.43 points in October from 219.91 points in September of 2025. This dataset provides the latest reported value for - Germany House Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Housing Index in Portugal increased to 258.78 points in the second quarter of 2025 from 247.05 points in the first quarter of 2025. This dataset provides - Portugal House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in Spain increased to 2094 EUR/SQ. METRE in the second quarter of 2025 from 2033 EUR/SQ. METRE in the first quarter of 2025. This dataset provides the latest reported value for - Spain House Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

HUD Multifamily Housing Assisted Properties

Detailed Overview of Subsidized Aid Programs and Population Characteristics

By Matthew Schnars [source]

About this dataset

HUD’s Multifamily Housing property portfolio is integral in providing secure, affordable rental units for low-income households - including seniors, those with special needs, and disabled individuals. Our coverage includes apartments and townhouses but can also include nursing homes, hospitals, elderly housing centers, mobile home parks and retirement service centers. Through subsidies and grants to property owners and developers we further our mission of promoting the construction and preservation of low cost housing opportunities.

This dataset comprises such properties from across the United States; located via our enterprise geocoding service which uses latitude/longitude coordinates as well as associated attributes for those addresses that can be geocoded to an interpolated point along a street segment or a ZIP+4 centroid location. Ultimately this dataset provides key insights into multifamily housing availability throughout the U.S., providing valuable information regarding individual buildings associated with each property while also giving us direct insight into population serviced by such programs in terms of their developmental needs or disabilities which may exist. With these metrics in hand we are better equipped to identify areas where reduced prices on rental units may benefit local communities the most - aiding populations that require our assistance the most directly! Data Dictionary: DD_Multifamily Properties; Date of Coverage: 12/2017; Data Updated: Quarterly

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How to use the dataset

First, let's talk about what kind of information you can get from this dataset. The HUD Multifamily Housing property portfolio consists primarily of rental housing properties with five or more dwelling units such as apartments or town houses. It includes subsidies and grants provided by HUD in order to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled.

The data contains geographic location information (latitude/longitude coordinates), city/state/ZIP code information as well as other internal identifiers for each property in the HUD portfolio. Additionally, there are columns related to different assistance programs which were previously noted above - Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly and Section 811 Supportive Housing for Persons with Disabilities).

In terms of how to use the data itself: due its size it is best explored by importing into an existing database solution like PostgreSQL or MongoDB where you can create custom views based on query keywords that bring back more meaningful results upon execution. Once you define what properties fit your criteria of interest then further analysis can commence - statistical trending on occupancy rates among much else given that next level drilling tends to open up many interesting possibilities like revenue forecasts creating new business models etc.. And speaking of statistics one area worth noting here specifically is that location data provided by HUD may not always be 100% accurate so caution should be exercised when running analytics queries because incorrect locations will lead astray any conclusions reached after running said queries - so feel free to double check your results before leveraging them in any form whatsoever!

Finally keep in mind that since there has only been one version of this dataset released thus far it would probably beneficial if you checked back every quarter or so just incase any changes were made particularity related to program eligibility requirements / reporting requirements etc..

Hope this helps and good luck on your journey considering using 'Hud Multifamily Properties Data' for whatever project at hand 😊

Research Ideas

• To identify potential opportunities for developers looking to add affordable housing in underserved areas. Depending on different factors such as the income of the local population, geography, and the type of funding method used to support these projects, developers could be more likely to invest in those areas that have previously been assisted by HUD programs.
• To evaluate performance measures of existing affordable housing across different locations within a given region or state. This could help identify any discrepancies between properties or address any issues within a...

Average House Prices in Canada increased to 688800 CAD in October from 687600 CAD in September of 2025. This dataset includes a chart with historical data for Canada Average House Prices.

Overview This technical report estimates the responsiveness of demand for structural pine to changes in timber and steel prices. Measures of demand responsiveness can provide valuable insights into the potential implications of changes in policy or market settings on volumes and prices received by producers. The analysis focuses on estimating short-term price elasticities of demand--a formal measure of the sensitivity of demand--to changes in prices in the same quarter or recent past. Key Issues The estimates in this report suggest that the importance of timber and steel prices on the quantity of structural timber demanded in the short-run is limited. However, the volume of residential construction activity was found to have a substantial effect for demand of domestically produced structural pine products. In particular, new house commencements explain a great deal of the quarter-on-quarter changes in the quantity of domestic structural pine sales. This confirms the common assertion by industry that house commencements are the primary driver for structural timber demand within Australia. Looking forward, changes in consumer preferences, socio-demographic trends and building regulations will likely play a much greater role in the choice of building materials used in housing construction compared with timber and steel prices. Trends suggest consumers are placing more weight on the environmental benefits of structural materials. Changing architectural styles will change the material requirements for a standard home. A global trend towards higher-density living will likely promote a shift toward multi-unit buildings, with recent changes to the National Construction Code opening the way for increased timber use in the midrise construction market, leading to greater timber use in multi-level buildings.

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

Housing Index in Sweden increased to 959 points in the third quarter of 2025 from 945 points in the second quarter of 2025. This dataset provides - Sweden House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in South Korea increased to 94 points in October from 93 points in September of 2025. This dataset provides - South Korea House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in Italy increased to 116.40 points in the second quarter of 2025 from 113.30 points in the first quarter of 2025. This dataset provides - Italy House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in Israel decreased to 595.40 points in September from 597.20 points in August of 2025. This dataset provides - Israel House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing Index in Greece increased to 109.50 points in the third quarter of 2025 from 107.80 points in the second quarter of 2025. This dataset provides the latest reported value for - Greece House Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.