In District of Columbia, the average rent per square foot was **** U.S. dollars in 2018, whereas renters in Oregon were expected to pay half as much in rent per square foot. DC was the most expensive state for renters, followed by New York, Hawaii, Massachusetts and California. Why is DC so expensive? District of Columbia is the center of the U.S. political system with all three branches of federal government sitting there: Congress (legislative), President (executive) and the Supreme Court (judicial). The above average household incomes of its residents mean that high rents are still sustainable for the rental market. Limited space in DC DC has the largest share of apartment dwellers in the country. This is most likely due to limited space, as the federal district has a much higher population density than the states. The political importance of DC and the high population density suggest that the federal district is likely to retain its spot as the most expensive rental market in the future.

Displacement risk indicator classifying census tracts according to apartment rent prices in census tracts. We classify apartment rent along two dimensions: The average rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in average rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Average rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing. Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development.

Rents for industrial real estate in the U.S. have increased since 2017, with flexible/service space reaching the highest price per square foot in 2024. In just a year, the cost of, flex/service space rose by nearly *****U.S. dollars per square foot. Manufacturing facilities, warehouses, and distribution centers had lower rents and experienced milder growth. Los Angeles, Orange County, and Inland Empire, California, are some of the most expensive markets in the country. Office real estate is pricier Industrial real estate is far from being the most expensive commercial property type. For instance, average rental rates in major U.S. metros for office space are much higher than those for industrial space. This is most likely because office units are generally located in urban areas where there is limited space and thus higher demand, whereas industrial units are more suited to the outskirts of such urban areas. Industrial units, such as warehouses or factories, require much more space because they need to house large, heavy equipment or serve as a storage unit for future shipments. Big-box distribution space is gaining in importance Warehouses and distribution may currently command the lowest average rent per square foot among industrial space types, but the growing popularity of the asset class has earned it considerable gains over the past years. In 2021 and 2022, high occupier demand and insufficient supply led to soaring taking rent of big-box buildings. During that time, the vacancy rate of distribution centers fell below ****percent. The development of industrial and logistics facilities has accelerated since then, with the new supply coming to market, causing the vacancy rate to increase and the pressures on rent to ease.

This dataset provides comprehensive information about rental house prices across various locations in India. It includes details such as house type, size, location, city, latitude, longitude, price, currency, number of bathrooms, number of balconies, negotiability of price, price per square foot, verification date, description of the property, security deposit, and status of furnishing (furnished, unfurnished, semi-furnished).

Note: This is Recently scraped data of April 2024.

Dataset Glossary (Column-Wise)

• House Type: Type of house (e.g., apartment, villa, duplex).
• House Size: Size of the house in square feet or square meters.
• Location: Specific area or neighborhood where the property is located.
• City: City in India where the property is situated.
• Latitude: Geographic latitude coordinates of the property location.
• Longitude: Geographic longitude coordinates of the property location.
• Price: Rental price of the house.
• Currency: Currency in which the price is denoted (e.g., INR - Indian Rupees).
• Number of Bathrooms: Total number of bathrooms in the house.
• Number of Balconies: Total number of balconies in the house.
• Negotiability: Indicates whether the price is negotiable (Yes/No).
• Price per Square Foot: Price of the house per square foot.
• Verification Date: Date when the rental information was verified.
• Description: Additional description or details about the property.
• Security Deposit: Amount of security deposit required for renting the property.
• Status: Indicates the furnishing status of the property (furnished, unfurnished, semi-furnished).

Usage

This dataset aims to provide valuable insights into the rental housing market in India, enabling analysis of rental trends, comparison of prices across different locations and property types, and understanding the impact of various factors on rental prices. Researchers, analysts, and policymakers can utilize this dataset for a wide range of applications, including real estate market analysis, urban planning, and economic research.

Acknowledgement

This Dataset is created from https://www.makaan.com/. If you want to learn more, you can visit the Website.

Cover Photo by: Playground.ai

The median rents within the census tract for the specified year, balancing between nominal rental price and rental price per square foot.The change in median rent price (again balanced between nominal rent price and price per square foot) from the previous year.Note: Median rent calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.

Manhattan, NY, was the market where renting an office was most expensive in the United States in 2025. The average annual quoted square footage rent of office space was close to ***** U.S. dollars in the second quarter of the year. In Dallas, the market with the second-largest inventory, the annual rent amounted to ***** U.S. dollars per square foot. Since the onset of the coronavirus pandemic, the office real estate sector has been suffering an increase in office vacancies, affecting both downtown and suburban properties. Data on the sales prices of office property also indicates a notable decrease in office real estate valuations.

The data was scraped from the Magicbricks website. The following are the details of the dataset:

• Title: The title of the property listing.
• Price: The monthly rent of the property.
• Area: The total area of the property in square feet.
• BHK: The number of bedrooms in the property.
• Bathrooms: The number of bathrooms on the property.
• Furnished: Whether the property is furnished or not.
• Balconies: The number of balconies in the property.
• Floor: The floor number of the property.
• Ownership: The type of ownership of the property (i.e., freehold, leasehold, etc.).
• Facing: The direction the property faces.
• Amenities: The amenities that are available in the property or the surrounding area.
• Transaction Type: Whether the property is for sale or rent.
• Property Type: The type of property (i.e., apartment, house, villa, etc.).
• Location: The location of the property.
• Year of Construction: The year the property was built.
• Is Luxury: Whether the property is considered to be a luxury property.
• Description: A brief description of the property.
• Property Image: A link to the property image.

Key points in the dataset are :

1) This dataset can be used to gain insights into the rental market in Mumbai. For example, you could use the data to analyze the average rent for different types of properties, the most popular neighborhoods for renters, or the factors that affect the price of rent. You could also use the data to identify trends in the rental market, such as the increasing popularity of furnished apartments or the rising prices of luxury properties.

2) The dataset could also be used by real estate agents to help their clients find rental properties that meet their needs and budget. Additionally, the data could be used by developers to make informed decisions about the types of properties to build in Mumbai.

3) Overall, this dataset is a valuable resource for anyone who is interested in the rental market in Mumbai. It can be used to gain insights into the market, identify trends, and make informed decisions.

(Disclaimer: The data in this dataset has been gathered from publicly available sources. While the data is believed to be reliable and all privacy policies have been observed, No personal information such as email addresses, mobile numbers, or physical addresses hasn't been collected. I scrape data from the website Magicbricks to study the real estate market of Mumbai. ) Thank you !!!

Malls had the most expensive rental space among the different types of retail real estate in the United States in 2023. As of the fourth quarter of the year, the average rent in malls was ***** U.S. dollars per square foot, compared to ***** U.S. dollars for all retail. General retail space, defined as single-tenant freestanding commercial buildings with parking, such as drugstores, grocery stores, and street front urban retail stores, had some of the lowest vacancy rates.

Context

Zillow operates an industry-leading economics and analytics bureau led by Zillow’s Chief Economist, Dr. Stan Humphries. At Zillow, Dr. Humphries and his team of economists and data analysts produce extensive housing data and analysis covering more than 500 markets nationwide. Zillow Research produces various real estate, rental and mortgage-related metrics and publishes unique analyses on current topics and trends affecting the housing market.

At Zillow’s core is our living database of more than 100 million U.S. homes, featuring both public and user-generated information including number of bedrooms and bathrooms, tax assessments, home sales and listing data of homes for sale and for rent. This data allows us to calculate, among other indicators, the Zestimate, a highly accurate, automated, estimated value of almost every home in the country as well as the Zillow Home Value Index and Zillow Rent Index, leading measures of median home values and rents.

Content

The Zillow Rent Index is the median estimated monthly rental price for a given area, and covers multifamily, single family, condominium, and cooperative homes in Zillow’s database, regardless of whether they are currently listed for rent. It is expressed in dollars and is seasonally adjusted. The Zillow Rent Index is published at the national, state, metro, county, city, neighborhood, and zip code levels.

Zillow produces rent estimates (Rent Zestimates) based on proprietary statistical and machine learning models. Within each county or state, the models observe recent rental listings and learn the relative contribution of various home attributes in predicting prevailing rents. These home attributes include physical facts about the home, prior sale transactions, tax assessment information and geographic location as well as the estimated market value of the home (Zestimate). Based on the patterns learned, these models estimate rental prices on all homes, including those not presently for rent. Because of the availability of Zillow rental listing data used to train the models, Rent Zestimates are only available back to November 2010; therefore, each ZRI time series starts on the same date.

Acknowledgements

The rent index data was calculated from Zillow's proprietary Rent Zestimates and published on its website.

Inspiration

What city has the highest and lowest rental prices in the country? Which metropolitan area is the most expensive to live in? Where have rental prices increased in the past five years and where have they remained the same? What city or state has the lowest cost per square foot?

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in U.S. City Average (CUUR0000SEHA) from Dec 1914 to Sep 2025 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

SF Rents

The data comes from Kate Pennington, data.sfgov.org, Vital Signs.

If using Dr. Pennington's data, please cite:

Pennington, Kate (2018). Bay Area Craigslist Rental Housing Posts, 2000-2018. Retrieved from https://github.com/katepennington/historic_bay_area_craigslist_housing_posts/blob/master/clean_2000_2018.csv.zip.

Her methodology can be found at her website.

What impact does new housing have on rents, displacement, and gentrification in the surrounding neighborhood? Read our interview with economist Kate Pennington about her article, "Does Building New Housing Cause Displacement?:The Supply and Demand Effects of Construction in San Francisco." - Kate Pennington on Gentrification and Displacement in San Francisco

All building permits can be found at the Socrata API endpoint.

Data Dictionary

rent.csv

variable	class	description
post_id	character	Unique ID
date	double	date
year	double	year
nhood	character	neighborhood
city	character	city
county	character	county
price	double	price in USD
beds	double	n of beds
baths	double	n of baths
sqft	double	square feet of rental
room_in_apt	double	room in apartment
address	character	address
lat	double	latitude
lon	double	longitude
title	character	title of listing
descr	character	description
details	character	additional details

sf_permits.csv

variable	class	description
permit_number	character	permit_number
permit_type	double	permit_type
permit_type_definition	character	permit_type_definition
permit_creation_date	double	permit_creation_date
block	character	block
lot	character	lot
street_number	double	street_number
street_number_suffix	character	street_number_suffix
street_name	character	street_name
street_suffix	character	street_suffix
unit	double	unit
unit_suffix	character	unit_suffix
description	character	description
status	character	status
status_date	double	status_date
filed_date	double	filed_date
issued_date	double	issued_date
completed_date	double	completed_date
first_construction_document_date	double	first_construction_document_date
structural_notification	character	structural_notification
number_of_existing_stories	double	number_of_existing_stories
number_of_proposed_stories	double	number_of_proposed_stories
voluntary_soft_story_retrofit	character	voluntary_soft_story_retrofit
fire_only_permit	character	fire_only_permit
permit_expiration_date	double	permit_expiration_date
estimated_cost	double	estimated_cost
revised_cost	double	revised_cost
existing_use	character	existing_use
existing_units ...

This data was pulled from Rentler.com by Elizabeth on 7/12/2021, 8/12/2021, and 9/6/2021. Her addition to Kaggle from Rentler.com was further sorted by removing the no longer existing dead links column along with other columns such as the description, size of the property in acres, full address, population, and population density as they were not relevant to the work being done with this specific project.

This specific project is based on a hypothetical client who is looking to shop around for her next home and is very budget conscious. She has an idea that she may want a pet in the future and enjoys certain amenities as well, but wants to know how much of a difference in price those amenities will affect her bottom line. She also wants to know which areas of the US will be best for her to consider in terms of price an unit size (sqft).

Questions: Do 2 bed apartments with 1 bathroom have a disproportionate price compared to 2 bed apartments with 2 bathrooms? Do 1 bed apartments with 1 bathroom have a disproportionate price compared to Studio apartments with 1 bathroom? Does Air Conditioning play a role in overall price of a rental unit (regardless of size)? Does having a Dishwasher play a role in overall price of a rental unit (regardless of size)? Does having a Washer/Dryer play a role in overall price of a rental unit (regardless of size)? Does allowing pets play a role in overall price of a rental unit (regardless of size)? What are the top 10 cities to live in in regard to price per square foot? Price with the most amenities? What are the bottom 10 cities to live in in regard to price per square foot? Price with the most/least amenities?

It was also cleaned to minimize as many outliers and null values as possible to better support any hypotheses moving forward. The dataset here includes only listings for 1,2 and 3 bedroom rentals with between 1 and 3.5 baths. All duplicates comparing the fields of Street Address, Beds, Baths, SqFt and Price were removed as well as any fields that contained blanks in the category of SqFt. In order to avoid any unnecessary outliers in exploration, SqFt was limited to 2700, Price to under $3000 and the deposit could only be <= two times the price. The original dataset contained over 270k records and this was cleaned and sorted to just under 100k

This dataset contains detailed information about rental properties across various locations in the UK. The data was collected by scraping Rightmove, a popular real estate platform. Each entry in the dataset includes the property's address, subdistrict code, rental price, deposit amount, letting type, furnish type, council tax details, property type, number of bedrooms and bathrooms, size in square feet, average distance to the nearest train station, and the count of nearest stations.

Researchers and analysts interested in the UK rental market can utilize this dataset to explore rental trends, pricing variations based on location and property type, amenities preferences, and more. The dataset provides a valuable resource for machine learning models, statistical analysis, and market research in the real estate sector.

Metadata: Source: The data was collected by scraping the Rightmove real estate platform, a leading source for property listings in the UK. Date Range: The dataset covers rental property listings available during the scraping period. Geographical Coverage: Primarily focused on various locations across the UK, providing insights into regional rental markets. Data Fields: Address: The location of the rental property. Subdistrict Code: A code representing the subdistrict or area of the property. Rent: The monthly rental price in GBP (£) for the property. Deposit: The deposit amount required for renting the property. Let Type: Indicates whether the property is available for short-term or long-term rental. Furnish Type: Describes the furnishing status of the property (e.g., furnished, unfurnished, or flexible options). Council Tax: Information about the council tax associated with the property. Property Type: Specifies the type of property, such as apartment, flat, maisonette, etc. Bedrooms: The number of bedrooms in the property. Bathrooms: The number of bathrooms in the property. Size: The size of the property in square feet (sq ft). Average Distance to Nearest Station: The average distance (in miles) to the nearest train station from the property. Nearest Station Count: The count of nearest train stations within a certain distance from the property. Data Quality: The data may contain missing values or "Ask agent" placeholders, which require direct inquiry with agents or landlords for specific information. Potential Uses: The dataset can be used for market analysis, rental price prediction models, understanding property preferences, and exploring the impact of location and amenities on rental properties in the UK.

Context

This dataset contains information on rent pricing surrounding Kuala Lumpur and Selangor region, Malaysia. The information was scraped from mudah.my

Content

There are 13 features with one unique ids (ads_id) and one target feature (monthly_rent)

• ads_id: the listing ids (unique)
• prop_name: name of the building/ property
• completion_year: completion/ established year of the property
• monthly_rent: monthly rent in ringgit malaysia (RM)
• location: property location in Kuala Lumpur region
• property_type:property type such as apartment, condominium, flat, duplex, studio, etc
• rooms: number of rooms in the unit
• parking: number of parking space for the unit
• bathroom: number of bathrooms in the unit
• size: total area of the unit in square feet
• furnished: furnishing status of the unit (fully, partial, non-furnished)
• facilities: main facilities available
• additional_facilities: additional facilities (proximity to attraction area, mall, school, shopping, railways, etc)

Acknowledgements The data was scraped from mudah.my

Inspiration I have been living in Kuala Lumpur, Malaysia since 2017, and in the past there was no easy way to understand whether certain unit pricing is making sense or not. With this dataset, I wanted to be able to answer the following questions:

• What are the biggest factor affecting the unit/rent pricing?
• Which location in Kuala Lumpur/ Selangor region that has the highest rent price? etc?

🏠 House Cost by Space

This dataset and accompanying Python script simulate housing rental costs as a function of square footage.The generated Excel file contains 100,000 rows with three columns:

No. → Row index (1 to 100,000)
House Sq. Feet → Randomly generated value between 100 and 100,000 sq ft
House Rent ($) → Estimated rental cost in USD

  📊 Data Generation Logic

Minimum size: 100 sq ft → rent ≈ $1,000
Maximum size: 100,000 sq ft → rent ≈ $1,000,000… See the full description on the dataset page: https://huggingface.co/datasets/bdstar/House_Cost_Space.

The average asking rent for Class A office space in Midtown Manhattan was ***** U.S. dollars per square foot in the second quarter of 2025. It was above the Manhattan average of ***** U.S. dollars but below that of Midtown South, which was the most expensive district at ***** U.S. dollars per square foot. What is Class A real estate?Class A real estate refers to the best properties in terms of appearance, age, quality of infrastructure and location. These properties usually command the highest rental rates, due to their high quality. In the U.S., Manhattan has the most expensive rents for Class A offices.Midtown vs Midtown SouthMidtown Manhattan contains the Empire State Building, MoMA, Grand Central Station, and the United Nations Headquarters. The most expensive submarket there was Plaza District in 2025. Meanwhile, Midtown South is home to Madison Square Garden, Pennsylvania Station, Hudson Yards, and Koreatown. In 2025, the most expensive submarket there was Hudson Yards, followed by Chelsea and Hudson Square.

San Francisco's office rental market showcases significant variation across its submarkets, with Mission Bay commanding the highest rates at *** U.S. dollars per square foot in the third quarter of 2024. This premium location demanded nearly double the city's average rate, highlighting the stark differences in desirability and demand within the city's commercial real estate landscape. Economic powerhouse The San Francisco Bay Area's economic prowess is evident in its impressive economic growth over the past 20 years. The city's strength is fueled by the presence of major technology companies and a thriving startup ecosystem. The region's economic significance extends beyond local boundaries, contributing substantially to California's position as the state with the highest GDP in the country. This economic vitality helps explain the sustained demand for office space across various San Francisco submarkets. Offices: global context and market trends In a global context, San Francisco's office rental rates are relatively high but not the most expensive worldwide. In 2024, London, Hong Kong, and New York emerged as the top three most expensive office rental markets globally. Over the past five years, San Francisco has experienced a decline in office rents. This trend aligns with broader shifts in the office real estate sector, influenced by the COVID-19 pandemic and the rise of hybrid work. Despite these challenges, certain San Francisco submarkets like Mission Bay and The Presidio continue to command premium rates, reflecting their enduring appeal to commercial tenants.

This dataset provides a comprehensive collection of features related to houses in California, with the primary aim of facilitating the prediction of house rent prices. It includes 80 columns and 1460 rows, offering a rich set of information for model training and evaluation. Target Variable: The dataset aims to predict the house rent prices, making it suitable for regression models. The 'SalePrice' column can be used as the target variable for training and evaluating predictive models.

Columns:

1. Id: Unique identifier for each record.
2. MSSubClass: The building class
3. MSZoning: The general zoning classification of the property.
4. LotFrontage: Linear feet of street connected to property.
5. LotArea: Lot size in square feet.
6. Street: Type of road access to property.
7. Alley: Type of alley access to property.
8. LotShape: General shape of the property.
9. LandContour: Flatness of the property. ... (and many more)

Use Case: Ideal for exploring and implementing regression models, particularly Linear Regression, to predict house rent prices based on various features associated with the properties.

Dataset Size: 80 columns 1460 rows

Source: This dataset is based on houses in California, making it relevant for studying the factors influencing house rent prices in this region.

Note: Please refer to the dataset documentation for details on each column and additional information regarding the data. Feel free to use this dataset for your machine learning projects, research, or educational purposes. Happy coding!

Gain a complete view of the real estate market with our Zillow datasets. Track price trends, rental/sale status, and price per square foot with the Zillow Price History dataset and explore detailed listings with prices, locations, and features using the Zillow Properties Listing dataset. Over 134M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Zpid
City
State
Home Status
Street Address
Zipcode
Home Type
Living Area Value
Bedrooms
Bathrooms
Price
Property Type
Date Sold
Annual Homeowners Insurance
Price Per Square Foot
Rent Zestimate
Tax Assessed Value
Zestimate
Home Values
Lot Area
Lot Area Unit
Living Area
Living Area Units
Property Tax Rate
Page View Count
Favorite Count
Time On Zillow
Time Zone
Abbreviated Address
Brokerage Name
And much more

Renting an office space in the UK was the most expensive in London West End in 2025. In the first quarter of the year, the square foot cost of a prime office space cost 170 British pounds. Conversely, Belfast was the most affordable of the 18 markets ranked, at 26 British pounds per square foot.