Contains the location information (latitude and Longitude, Northing and Easting) of every property address within the City of Melbourne

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. It show business establishments with their business address, industry (ANZSIC4) classification, location and CLUE block and small area allocation.

A business establishment is defined as a • Commercial occupant in a building • Separate land use • Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC).

Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'.

For more information about CLUE see http://www.melbourne.vic.gov.au/clue

For more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

This dataset is about universities in Melbourne. It has 6 rows. It features 3 columns: total students, and address.

This bar chart displays universities by address using the aggregation count in Melbourne. The data is about universities.

This dataset shows all of the streets and laneways within the City of Melbourne. This dataset is used in order for people to create their own map of the city and can be used to label the streets with their names down the centre of the road as is the standard for labelling streets on maps.

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2023. The dwelling data is based on the Council's property rates database, using a simplified classification schema of Residential Apartment, House/Townhouse and Student Apartment. The count of dwellings per residential building is shown.

For more information about CLUE see http://www.melbourne.vic.gov.au/clue

This bar chart displays total students (people) by address using the aggregation sum in Melbourne. The data is about universities.

This horizontal bar chart displays universities by address using the aggregation count in Melbourne. The data is about universities.

Data collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2020. It show business establishments with their business address, …Show full descriptionData collected as part of the City of Melbourne's Census of Land Use and Employment (CLUE). The data covers the period 2002-2020. It show business establishments with their business address, industry (ANZSIC4) classification, location and CLUE block and small area allocation. A business establishment is defined as a • Commercial occupant in a building • Separate land use • Any permanent presence of economic activity in accordance with standard Industry classification (ANZSIC). Hence, if one organisation has its presence in several buildings in the CLUE area, each time it will be counted as a separate establishment. Consequently, the count of establishments presented in CLUE represents the number of locations, rather than 'enterprises'. For more information about CLUE see http://www.melbourne.vic.gov.au/clue For more information about the ANZSIC industry classification system see http://www.abs.gov.au/ausstats/abs@.nsf/mf/1292.0

This dataset provides information about the number of properties, residents, and average property values for Trimble Road cross streets in Melbourne, FL.

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.

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.

This horizontal bar chart displays graduate students (people) by address using the aggregation sum in Melbourne. The data is about universities.

The City of Melbourne's Public Open Space Contribution Register provides information on money collected from subdivision applications under the Subdivision Act 1988.​The register has the property address, prior and proposed use, date paid, percentage and amount of money collected.

This dataset provides information about the number of properties, residents, and average property values for Arbor Drive cross streets in Melbourne, FL.

This dataset provides information about the number of properties, residents, and average property values for Aurora Road cross streets in Melbourne, FL.

This is a List of off property leases that are administered by the City of Melbourne.

This dataset provides information about the number of properties, residents, and average property values for Rose Court cross streets in Melbourne, FL.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Melbourne. Based on the latest 2022 1-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Melbourne. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Melbourne, householders within the 45 to 64 years age group have the highest median household income at $87,193, followed by those in the 25 to 44 years age group with an income of $73,833. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $52,563. Notably, householders within the under 25 years age group, had the lowest median household income at $30,765.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Melbourne median household income by age. You can refer the same here

This dataset provides information about the number of properties, residents, and average property values for Business Center Boulevard cross streets in Melbourne, FL.