As a Data scientist, who yearns to experiment, learn and explore different techniques applied in this field, one cannot overlook the importance of application of Exploratory Data Analysis on various datasets out there.

This housing dataset provides a thorough analysis of the current state of the housing market. It includes information on housing prices, availability, and key trends, allowing you to gain a better understanding of the market and make informed decisions. Whether you're a homebuyer, investor, or simply interested in the state of the housing market, this dataset has valuable insights to offer.

The average price of Australian residential property has risen over the past ten years, and in June 2025, it reached over one million Australian dollars. Nonetheless, property experts in Australia have indicated that the country has been in a property bubble over the past decade, with some believing the market will collapse sometime in the near future. Property prices started declining in 2022; however, a gradual upward trend was witnessed throughout 2023, with minor fluctuations in 2024. Australian capital city price differences While the national average residential property price has exhibited growth, individual capital cities display diverse trends, highlighting the complexity of Australia’s property market. Sydney maintains its position as the most expensive residential property market across Australia's capital cities, with a median property value of approximately 1.19 million Australian dollars as of April 2025. Brisbane has emerged as an increasingly pricey capital city for residential property, surpassing both Canberra and Melbourne in median housing values. Notably, Perth experienced the most significant annual increase in its average residential property value, with a 10 percent increase from April 2024, despite being a comparably more affordable market. Hobart and Darwin remain the most affordable capital cities for residential properties in the country. Is the homeownership dream out of reach? The rise in property values coincides with the expansion of Australia's housing stock. In the June quarter of 2025, the number of residential dwellings reached around 11.37 million, representing an increase of about 53,600 dwellings from the previous quarter. However, this growth in housing supply does not necessarily translate to increased affordability or accessibility for many Australians. The country’s house prices remain largely disproportional to income, leaving the majority of low- and middle-income earners priced out of the market. Alongside this, elevated mortgage interest rates in recent years have made taking out a loan increasingly unappealing for many potential property owners, and the share of mortgage holders at risk of mortgage repayment stress has continued to climb.

Graph and download economic data for Real Residential Property Prices for Australia (QAUR628BIS) from Q1 1970 to Q2 2025 about Australia, residential, HPI, housing, real, price index, indexes, and price.

Sydney had the highest median house value compared to other capital cities in Australia as of April 2025, with a value of over **** million Australian dollars. Brisbane similarly had relatively high average residential housing values, passing Canberra and Melbourne to top the pricing markets for real estate across the country alongside Sydney. Housing affordability in Australia Throughout 2024, the average price of residential dwellings remained high across Australia, with several capital cities breaking price records. Rising house prices continue to be an issue for potential homeowners, with many low- and middle-income earners priced out of the market. In the fourth quarter of 2024, Australia’s house price-to-income ratio declined slightly to ***** index points. With the share of household income spent on mortgage repayments increasing alongside the disparity in supply and demand, inflating construction costs, and low borrowing capacity, the homeownership dream has become an unattainable prospect for the average person in Australia. Does the rental market offer better prospects? Renting for prolonged periods has become inevitable for many Australians due to the country’s largely inaccessible property ladder. However, record low vacancy rates and elevated median weekly house and unit rent prices within Australia’s rental market are making renting a less appealing prospect. In financial year 2024, households in the Greater Sydney metropolitan area reported spending around ** percent of their household income on rent.

Housing Index in Australia increased to 183.90 points in the fourth quarter of 2021 from 175.60 points in the third quarter of 2021. This dataset provides the latest reported value for - Australia House Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Median prices for dwellings/townhouses, and apartments by their year of settlement for the City of Melbourne.

Graph and download economic data for All-Transactions House Price Index for Palm Bay-Melbourne-Titusville, FL (MSA) (ATNHPIUS37340Q) from Q4 1979 to Q2 2025 about Palm Bay, appraisers, FL, HPI, housing, price index, indexes, price, and USA.

Key information about Australia Gold Production

• Australia Real Residential Property Price Index was reported at 134.815 2010=100 in Jun 2025.
• This records an increase from the previous number of 133.974 2010=100 for Mar 2025.
• Australia Real Residential Property Price Index data is updated quarterly, averaging 48.406 2010=100 from Mar 1970 to Jun 2025, with 222 observations.
• The data reached an all-time high of 141.875 2010=100 in Mar 2022 and a record low of 31.307 2010=100 in Mar 1970.
• Australia Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Real estate markets are of great importance for both local and international investors. Sydney and Melbourne are two dynamic markets where economic and social factors have significant impacts on property prices. Below is a detailed description of each feature:

1. Date: The date when the property was sold. This feature helps in understanding the temporal trends in property prices.
2. Price:The sale price of the property in USD. This is the target variable we aim to predict.
3. Bedrooms:The number of bedrooms in the property. Generally, properties with more bedrooms tend to have higher prices.
4. Bathrooms: The number of bathrooms in the property. Similar to bedrooms, more bathrooms can increase a property’s value.
5. Sqft Living: The size of the living area in square feet. Larger living areas are typically associated with higher property values.
6. Sqft Lot:The size of the lot in square feet. Larger lots may increase a property’s desirability and value.
7. Floors: The number of floors in the property. Properties with multiple floors may offer more living space and appeal.
8. Waterfront: A binary indicator (1 if the property has a waterfront view, 0 other- wise). Properties with waterfront views are often valued higher.
9. View: An index from 0 to 4 indicating the quality of the property’s view. Better views are likely to enhance a property’s value.
10. Condition: An index from 1 to 5 rating the condition of the property. Properties in better condition are typically worth more.
11. Sqft Above: The square footage of the property above the basement. This can help isolate the value contribution of above-ground space.
12. Sqft Basement: The square footage of the basement. Basements may add value depending on their usability.
13. Yr Built: The year the property was built. Older properties may have historical value, while newer ones may offer modern amenities.
14. Yr Renovated: The year the property was last renovated. Recent renovations can increase a property’s appeal and value.
15. Street: The street address of the property. This feature can be used to analyze location-specific price trends.
16. City: The city where the property is located. Different cities have distinct market dynamics.
17. Statezip: The state and zip code of the property. This feature provides regional context for the property.
18. Country: The country where the property is located. While this dataset focuses on properties in Australia, this feature is included for completeness.

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The average price of Australian residential property has risen over the past ten years, and in December 2024, it reached 976,800 Australian dollars. Nonetheless, property experts in Australia have indicated that the country has been in a property bubble over the past decade, with some believing the market will collapse sometime in the near future. Property prices started declining in 2022; however, a gradual upward trend was witnessed throughout 2023, with minor fluctuations in 2024. Australian capital city price differences While the national average residential property price has exhibited growth, individual capital cities display diverse trends, highlighting the complexity of Australia’s property market. Sydney maintains its position as the most expensive residential property market across Australia's capital cities, with a median property value of approximately 1.19 million Australian dollars as of April 2025. Brisbane has emerged as an increasingly pricey capital city for residential property, surpassing both Canberra and Melbourne in median housing values. Notably, Perth experienced the most significant annual increase in its average residential property value, with a 10 percent increase from April 2024, despite being a comparably more affordable market. Hobart and Darwin remain the most affordable capital cities for residential properties in the country. Is the homeownership dream out of reach? The rise in property values coincides with the expansion of Australia's housing stock. In the December quarter of 2024, the number of residential dwellings reached around 11.29 million, representing an increase of about 53,200 dwellings from the previous quarter. However, this growth in housing supply does not necessarily translate to increased affordability or accessibility for many Australians. The country’s house prices remain largely disproportional to income, leaving the majority of low- and middle-income earners priced out of the market. Alongside this, elevated mortgage interest rates in recent years have made taking out a loan increasingly unappealing for many potential property owners, and the share of mortgage holders at risk of mortgage repayment stress has continued to climb.

Explore Melbourne, FL rental market 2025. The average long-term prices $1,911 and short-term $2,205, with trends shaping housing in a city of 85,718 residents.

Urban housing location and locational amenities play an important role in median house price distribution and growth among the suburbs of many metropolitan cities in developed countries, such as Australia. In particular, distance from the central business district (CBD) and access to the transport network plays a vital role in house price distribution and growth over various suburbs in a city. However, Australian metropolitan cities have experienced increases in housing prices by up to 120% over the last 20 years, and the growth pattern was different across all suburbs in a city, such as in Melbourne. Therefore, this study examines the impacts of locational amenities on house price changes across various suburbs in Melbourne over the three census periods of 2006, 2011, and 2016, and suggests some strategic guidelines to improve the availability and accessibility of locational amenities in the suburbs with less concentrated amenities.

This study chose three Local Government Areas (LGAs) of Maribyrnong, Brimbank and Wyndham in Melbourne. Each LGA has been selected as a case study because many low-income people live in these LGAs’ areas. Further, some suburbs of these LGAs have maintained similar housing prices for an extended time, while some have not.

The study applied a quantitative spatial methodology to examine the housing price distribution and growth patterns by evaluating the concentration and accessibility of locational urban amenities using GIS-based techniques and a spatial data set. The spatial data analyses were performed by spatial statistics methods to measure central tendency, Local Moran’s I of LISA clustering, Kernel Density Estimation (KDE), Kernel Density Smoothing (KDS). These tests were used to find the patterns of house price distribution and growth. The study also identified the accessibility of amenities in relation to median house price distribution and growth. Spatial Autoregressive Regression (SAR), Spatial Lag, and Spatial Errors models were used to identify the spatial dependencies to test the statistical significance between the median house price and the concentration and access of local urban amenities over the three census years.

This study found three median house price distribution and growth patterns among the suburbs in the three selected LGAs. There are growth differences in the median house price for different census years between 2006 and 2011, 2011 and 2016, and 2006 and 2016. The Low-High (LH) median house price distribution clusters between 2006 and 2011 became High-High (HH) clusters between the census years 2011 and 2016, and 2006 and 2016. The median house price growth rate increased significantly in the census years between 2006 and 2011. Most of the HH median house price distribution and growth clusters’ tendencies were closer to the Melbourne CBD. On the other hand, the Low-Low (LL) distribution and growth clusters were closer to Melbourne’s periphery. The suburbs located further away had low access to amenities. The HH median house price clusters are located closer to stations and educational institutes. Better access to locational amenities led to more significant HH median house price clusters, as the median house price increased at an increasing rate between 2011 and 2016. The HH median house price clusters recorded more growth between 2006 and 2016. The suburbs with train stations had better access to most other locational amenities. Almost all HH median house price clusters had train stations with higher access to amenities.

There was a consistent relationship between median house price distribution, growth patterns, and locational urban amenities. The spatial lag and spatial error model tests showed that between 2006 and 2011, and 2006 and 2016, there were differences in the amenities. Still, these did not affect the outcomes in observations, and were related only to immeasurable factors for some reason. Therefore, the higher house price in the neighbouring suburb could increase the price in that suburb. The research also found from the regression analysis that highly significant amenities confirming travel time to the CBD by bus, and distance to the CBD, were negatively related in all three previous census years. This negative relationship estimates that the house price growth is lower when the distance is longer. Due to this travel to the CBD by bus is not a popular option for households. The train stations are essential for high house price growth. The house price growth is low when homes are further away from train stations and workplaces.

This thesis has three contributions. Firstly, it uses the Rational Choice Theory (RCT), providing a theoretical basis for analysing households’ mutually interdependent preferences of urban amenities that are found to regulate house price growth clusters. Secondly, the methodological contribution uses the GIS-defined cluster mapping and spatial statistics in queries and reasoning, measurements, transformations, descriptive summaries, optimisation, and hypothesis testing models between house price distribution and growth, and access to urban locational amenities. Thirdly, this research contributes to designing practical guidelines to identify local urban amenities for planning local area development.

Overall, this thesis demonstrates that the median house price distribution and growth patterns are highly correlated with the concentration and accessibility of locational urban amenities among the suburbs in three selected LGAs in Melbourne over the three census years (i.e., 2006, 2011, and 2016). The findings bring to the fore the need for research at the local and state levels to identify specific amenities relevant to the middle-class house distribution strategy, which can be helpful for investors, estate agents, town planners, and builders as partners for effective local development. The future study might use social, psychological, and macroeconomic variables not considered or used in this research.

• Objective: To predict the prices of houses in the City of Melbourne
• Approach: Using Decision Tree and Random Forest https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2Ffc6fb7d0bd8e854daf7a6f033937a397%2FPicture1.png?generation=1693489996707941&alt=media" alt="">
• Data Cleaning:
• Date column is shown as a character vector which is converted into a date vector using the library ‘lubridate’
• We create a new column called age to understand the age of the house as it can be a factor in the pricing of the house. We extract the year from column ‘Date’ and subtract it from the column ‘Year Built’
• We remove 11566 records which have missing values
• We drop columns which are not significant such as ‘X’, ‘suburb’, ‘address’, (we have kept zipcode as it serves the purpose in place of suburb and address), ‘type’, ‘method’, ‘SellerG’, ‘date’, ‘Car’, ‘year built’, ‘Council Area’, ‘Region Name’
• We split the data into ‘train’ and ‘test’ in 80/20 ratio using the sample function
• Run libraries ‘rpart’, ‘rpart.plot’, ‘rattle’, ‘RcolorBrewer’
• Run decision tree using the rpart function. ‘Price’ is the dependent variable https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2F6065322d19b1376c4a341a4f22933a51%2FPicture2.png?generation=1693490067579017&alt=media" alt="">
• Average price for 5464 houses is $1084349
• Where building area is less than 200.5, the average price for 4582 houses is $931445. Where building area is less than 200.5 & age of the building is less than 67.5 years, the avg price for 3385 houses is $799299.6.
• $4801538 is the Highest average prices of 13 houses where distance is lower than 5.35 & building are is >280.5
  https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2F136542b7afb6f03c1890bae9b07dc464%2FDecision%20Tree%20Plot.jpeg?generation=1693490124083168&alt=media" alt="">
• We use the caret package for tuning the parameter and the optimal complexity parameter found is 0.01 with RMSE 445197.9 https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2Feb1633df9dd61ba3a51574873b055fd0%2FPicture3.png?generation=1693490163033658&alt=media" alt="">
• We use library (Metrics) to find out the RMSE ($392107), MAPE (0.297) which means an accuracy of 99.70% and MAE ($272015.4)
• Variables ‘postcode’, longitude and building are the most important variables
• Test$Price indicates the actual price and test$predicted indicates the predicted price for particular 6 houses. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2F620b1aad968c9aee169d0e7371bf3818%2FPicture4.png?generation=1693490211728176&alt=media" alt="">
• We use the default parameters of random forest on the train data https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2Fe9a3c3f8776ee055e4a1bb92d782e19c%2FPicture5.png?generation=1693490244695668&alt=media" alt="">
• The below image indicates that ‘Building Area’, ‘Age of the house’ and ‘Distance’ are the most important variables that affect the price of the house. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2Fc14d6266184db8f30290c528d72b9f6b%2FRandom%20Forest%20Variables%20Importance.jpeg?generation=1693490284920037&alt=media" alt="">
• Based on the default parameters, RMSE is $250426.2, MAPE is 0.147 (accuracy is 99.853%) and MAE is $151657.7
• Error starts to remain constant between 100 to 200 trees and thereafter there is almost minimal reduction. We can choose N tree=200. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10868729%2F365f9e8587d3a65805330889d22f9e60%2FNtree%20Plot.jpeg?generation=1693490308734539&alt=media" alt="">
• We tune the model and find mtry = 3 has the lowest out of bag error
• We use the caret package and use 5 fold cross validation technique
• RMSE is $252216.10 , MAPE is 0.146 (accuracy is 99.854%) , MAE is $151669.4
• We can conclude that Random Forest give us more accurate results as compared to Decision Tree
• In Random Forest , the default parameters (N tree = 500) give us lower RMSE and MAPE as compared to N tree = 200. So we can proceed with those parameters.

Median prices for dwellings/townhouses, and apartments by their year of sale for the City of Melbourne.

The Residential Property Price Index in Australia rose by 4.7 percent qoq in Q4 2021, above market consensus of 3.9 percent and after a 5.0 percent growth in Q3. This was the sixth straight quarter of growth in property prices, supported by record-low interest rates and strong demand. The strongest quarterly price increases were recorded in Brisbane (9.6 percent), followed by Adelaide (6.8 percent), Hobart (6.5 percent), and Canberra (6.4 percent). Through the year to Q4, the index jumped to a record high of 23.7 percent, with Hobart, Canberra, Brisbane, Sydney, and Adelaide having the largest annual rise since the commencement of the series; while Melbourne had the largest annual rise since Q2 2010. This dataset includes a chart with historical data for Australia House Price Index QoQ.

About this Dataset

Context

Melbourne real estate is BOOMING. Can you find the insight or predict the next big trend to become a real estate mogul… or even harder, to snap up a reasonably priced 2-bedroom unit?

It was scraped from publicly available results posted every week from Domain.com.au. He cleaned it well, and now it's up to you to make data analysis magic. The dataset includes Address, Type of Real estate, Suburb, Method of Selling, Rooms, Price, Real Estate Agent, Date of Sale and distance from C.B.D.

Notes on Specific Variables Rooms: Number of rooms

Price: Price in dollars

Method: S - property sold; SP - property sold prior; PI - property passed in; PN - sold prior not disclosed; SN - sold not disclosed; NB - no bid; VB - vendor bid; W - withdrawn prior to auction; SA - sold after auction; SS - sold after auction price not disclosed. N/A - price or highest bid not available.

Type: br - bedroom(s); h - house,cottage,villa, semi,terrace; u - unit, duplex; t - townhouse; dev site - development site; o res - other residential.

SellerG: Real Estate Agent

Date: Date sold

Distance: Distance from CBD

Regionname: General Region (West, North West, North, North east …etc)

Propertycount: Number of properties that exist in the suburb.

Bedroom2 : Scraped # of Bedrooms (from different source)

Bathroom: Number of Bathrooms

Car: Number of carspots

Landsize: Land Size

BuildingArea: Building Size

CouncilArea: Governing council for the area

Acknowledgements This is intended as a static (unchanging) snapshot of https://www.kaggle.com/anthonypino/melbourne-housing-market. It was created in September 2017. Additionally, homes with no Price have been removed.

All-Transactions House Price Index for Palm Bay-Melbourne-Titusville, FL (MSA) was 450.46000 Index 1995 Q1=100 in April of 2025, according to the United States Federal Reserve. Historically, All-Transactions House Price Index for Palm Bay-Melbourne-Titusville, FL (MSA) reached a record high of 458.58000 in October of 2024 and a record low of 62.11000 in April of 1980. Trading Economics provides the current actual value, an historical data chart and related indicators for All-Transactions House Price Index for Palm Bay-Melbourne-Titusville, FL (MSA) - last updated from the United States Federal Reserve on November of 2025.

Discover the booming Australian commercial real estate market! Projected to reach $67.56 billion by 2033 with an 8.46% CAGR, this in-depth analysis reveals key drivers, trends, and top players in Sydney, Melbourne, Brisbane and beyond. Invest wisely with our data-driven insights. Recent developments include: • October 2023: Costco is planning a major expansion in Australia, with several new warehouses under construction and several prime locations being considered for future locations. Costco currently operates 15 warehouses in Australia, with plans to expand to 20 within the next five years, based on current stores and potential locations., • July 2023: A 45-storey BTR tower will be developed by Lendlease and Japanese developer Daiwa House, completing the final phase of Lendlease's Melbourne Quarter project and its second Build-to-Rent (BTR) project in Australia. The USD 650 million deal, similar to Lend lease's first 443-unit BTR project under construction in the 5.5 hectares of mixed-use space at Brisbane Showground, is a stand-alone investment and is separate from the company's ongoing efforts to build a wider BTR partnership, which will include several assets.. Key drivers for this market are: Rapid Urbanization, Government Initiatives Actively promoting the Construction Activities. Potential restraints include: Rapid Urbanization, Government Initiatives Actively promoting the Construction Activities. Notable trends are: Retail real estate is expected to drive the market.

The Australian luxury residential property market, valued at $23.88 billion in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 5.75% from 2025 to 2033. This expansion is fueled by several key drivers. Strong economic performance in key cities like Sydney, Melbourne, and Brisbane, coupled with a burgeoning high-net-worth individual (HNWI) population, continues to underpin demand for premium properties. Furthermore, a limited supply of luxury housing stock in prime locations, combined with increasing preference for spacious, high-amenity homes, particularly villas and landed houses, contributes to sustained price appreciation. While rising interest rates present a potential restraint, the resilience of the luxury market segment, driven by wealthier buyers less susceptible to interest rate fluctuations, is expected to mitigate this effect. The market is segmented by property type (apartments/condominiums versus villas/landed houses) and location, with Sydney, Melbourne, and Brisbane dominating market share, reflecting their established luxury real estate markets and strong economic activity. Prominent developers like Metricon Homes, James Michael Homes, and others cater to this discerning clientele, offering bespoke designs and high-end finishes. The sustained growth trajectory indicates a promising outlook for investors and developers alike, although careful consideration of macroeconomic factors and regulatory changes will remain crucial. The forecast period (2025-2033) anticipates consistent market expansion, driven by ongoing demand from both domestic and international high-net-worth individuals. While the "Other Cities" segment demonstrates potential for growth, Sydney, Melbourne, and Brisbane are likely to maintain their dominant positions due to existing infrastructure, established luxury markets, and lifestyle appeal. The preference for villas and landed houses is expected to remain strong, reflecting a shift towards larger properties with increased privacy and outdoor space. However, the market will likely see some adjustments in response to economic conditions, including potential shifts in buyer preferences and developer strategies to meet evolving market demands. Maintaining a keen understanding of these dynamics will be critical for navigating the complexities of this dynamic market. Recent developments include: August 2023: Sydney-based boutique developer Made Property laid plans for a new apartment project along Sydney Harbour amid sustained demand for luxury waterfront properties. The Corsa Mortlake development, positioned on Majors Bay in the harbor city’s inner west, will deliver 20 three-bedroom apartments offering house-sized living spaces and ready access to a 23-berth marina accommodating yachts up to 20 meters. With development approval secured for the project, the company is moving quickly to construction. Made Property expects construction to be completed in late 2025., September 2023: A luxurious collection of private apartment residences planned for a prime double beachfront site in North Burleigh was released to the market for the first time with the official launch of ultra-premium apartment development Burly Residences, being delivered by leading Australian developer David Devine and his team at DD Living. The first stage of Burly Residences released to the market includes prestigious two and three-bedroom apartments – with or without multipurpose rooms – and four-bedroom plus multipurpose room apartments that deliver luxury and space with expansive ocean and beach views.. Key drivers for this market are: 4., Increasing Number of High Net-Worth Individuals (HNWIs). Potential restraints include: 4., Increasing Number of High Net-Worth Individuals (HNWIs). Notable trends are: Ultra High Net Worth Population Driving the Demand for Prime Properties.

The Australia Luxury Residential Real Estate Market Report is Segmented by Business Model (Sales and Rental), by Property Type (Apartments & Condominiums and Villas & Landed Houses), by Mode of Sale (Primary New-Build and Secondary Existing-Home Resale), and by Key Cities (Sydney, Melbourne, Brisbane, Perth and the Rest of Australia). The Market Forecasts are Provided in Terms of Value (USD).