Amsterdam is set to maintain its position as Europe's most expensive city for apartment rentals in 2025, with median costs reaching 2,500 euros per month for a furnished unit. This figure is double the rent in Prague and significantly higher than other major European capitals like Paris, Berlin, and Madrid. The stark difference in rental costs across European cities reflects broader economic trends, housing policies, and the complex interplay between supply and demand in urban centers. Factors driving rental costs across Europe The disparity in rental prices across European cities can be attributed to various factors. In countries like Switzerland, Germany, and Austria, a higher proportion of the population lives in rental housing. This trend contributes to increased demand and potentially higher living costs in these nations. Conversely, many Eastern and Southern European countries have homeownership rates exceeding 90 percent, which may help keep rental prices lower in those regions. Housing affordability and market dynamics The relationship between housing prices and rental rates varies significantly across Europe. As of 2024, countries like Turkey, Iceland, Portugal, and Hungary had the highest house price to rent ratio indices. This indicates a widening gap between property values and rental costs since 2015. The affordability of homeownership versus renting differs greatly among European nations, with some countries experiencing rapid increases in property values that outpace rental growth. These market dynamics influence rental costs and contribute to the diverse rental landscape observed across European cities.

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.

Correction coefficients are used to ensure equality of purchasing power of salaries of EU officials in the different duty stations. They are calculated as the ratio between the “economic parity” and the exchange rate to the Euro (where applicable). They operate as a percentage adjustment to remuneration expressed in local currency.

The method used to establish economic parities is to compare the price of a basket of goods and services purchased by the average retired international official in Belgium with the price of an equivalent basket of goods and services purchased by the average retired international official in each of the other countries.

The rent paid for an apartment or house, due to its high weight in the total household expenditure structure, plays a significant role in determining the overall correction coefficient.

Consequently, specific rent surveys are carried out annually in cooperation with relevant real estate agencies. The information obtained, and that derived from similar surveys in previous years, is used to determine the difference in rental prices between Brussels and each of the other locations where the survey is carried out, in rental prices for the same type of dwelling.

The scope of these surveys is to compare the average market rent for some specific kinds of dwellings in some pre-specified representative areas of Brussels with similar dwellings in similar (representative and comparable) areas in other EU capitals and duty stations.

The estate agency rent surveys (EARS) are organised jointly by Eurostat, the International Service for Remunerations and Pensions (ISRP) of the Co-ordinated Organisations and national statistical institutes (NSI) in each duty station, including Brussels, with the collaboration of estate agents in the duty stations concerned.

The work is done in accordance with a methodology approved by the Expert Working Group on Articles 64 & 65 of the Staff Regulations.
Whilst this rent information is collected for a specific purpose, according to a specific methodology, it may also be relevant for other purposes.

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

In 2024, New York, NY, was the most expensive rental market for one-bedroom apartments in the United States. The median monthly rental rate of an apartment in New York was ***** U.S. dollars, while in San Francisco, CA which ranked second highest, renters paid on average ***** U.S. dollars.

VITAL SIGNS INDICATOR List Rents (EC9)

FULL MEASURE NAME List Rents

LAST UPDATED October 2016

DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

DATA SOURCE real Answers (1994 – 2015) no link

Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

Inflation-adjusted data are presented to illustrate how rents 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. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

In the first quarter of 2025, Amsterdam was the most expensive city to rent a furnished private room among the 27 European cities surveyed. It was also among the top ranking most expensive cities to rent a furnished one-bedroom flat and studio apartment. One of the main factors driving high rents across European cities is the same as any other consumer-driven business. If demand outweighs supply, prices will inflate. The drive for high paid professionals to be located centrally in prime locations, mixed with the low levels of available space, high land, and construction costs, all keep rental prices increasing.

Price to Rent Ratio in the United States increased to 134.04 in the fourth quarter of 2024 from 133.46 in the third quarter of 2024. This dataset includes a chart with historical data for the United States Price to Rent Ratio.

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

VITAL SIGNS INDICATOR
Rent Payments (EC8)

FULL MEASURE NAME
Median rent payment

LAST UPDATED
January 2023

DESCRIPTION
Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time.

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Count 2 (1970)
Form STF1 (1980-1990)
Form SF3a (2000)

U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B25058 (2005-2021; median contract rent)

Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Rent data reflects median rent payments rather than list rents (refer to measure definition above). American Community Survey 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

1970 Census data for median rent payments has been imputed from quintiles using methodology from California Department of Finance as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

Inflation-adjusted data are presented to illustrate how rent payments 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 CPI itself.

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 ...

Rent Inflation in the United States remained unchanged at 3.60 percent in September. This dataset includes a chart with historical data for the United States Rent Inflation.

This table contains data described by the following dimensions (Not all combinations are available): Geography (247 items: Carbonear; Newfoundland and Labrador; Corner Brook; Newfoundland and Labrador; Grand Falls-Windsor; Newfoundland and Labrador; Gander; Newfoundland and Labrador ...), Type of structure (4 items: Apartment structures of three units and over; Apartment structures of six units and over; Row and apartment structures of three units and over; Row structures of three units and over ...), Type of unit (4 items: Two bedroom units; Three bedroom units; One bedroom units; Bachelor units ...).

Context

The purpose of this dataset is to provide updated data on the Zillow Observed Rent Index (ZORI). Most of the Zillow datasets on Kaggle have not been updated in four years, and no other dataset except one contains information related to rent. Providing updated data on this will also allow the community to analyze the effects of COVID-19 on rent prices, which could not be done with previous available data sets.

Content

Zillow Observed Rent Index (ZORI): A smoothed measure of the typical observed market rate rent across a given region. ZORI is a repeat-rent index that is weighted to the rental housing stock to ensure representativeness across the entire market, not just those homes currently listed for-rent. The index is dollar-denominated by computing the mean of listed rents that fall into the 40th to 60th percentile range for all homes and apartments in a given region, which is once again weighted to reflect the rental housing stock. Details available in ZORI methodology. https://www.zillow.com/research/methodology-zori-repeat-rent-27092/

This dataset contains two files. The Metro dataset looks at the median rent prices for large US cities. The ZIP code dataset breaks the US cities down by their ZIP codes. Note that the region IDs in both datasets are only used for tracking purposes. Also, some of the ZIP codes under the Region Name are less than the standard five-digit zip code and unreliable. Even if you add zeros in accounting for possible formatting mistakes. It is recommended to remove these entries since there is no way to identify which ZIP code the entry actually represents. These entries are left in here in case some analyst can solve the issue.

Acknowledgements

Zillow provides many useful open source datasets that relate to housing, which can be found at Zillow Research Data. https://www.zillow.com/research/data/ This dataset was also prompted by an older dataset I came across that only lacked updated data. https://www.kaggle.com/zillow/rent-index Thumbnail and banner picture is from this pixabay artist https://pixabay.com/users/pexels-2286921/

Inspiration

1. Where are the cheapest and most expensive ZIP codes to live?
2. We all know rent increases overtime, but has it been increasing at a faster rate since 2014?
3. If rent has been increasing at a faster rate, what year did it increase the fastest?
4. What cities or ZIP codes are increasing rent the fastest and by how much?
5. Did rent continue to increase during the COVID-19 pandemic, and was it at a faster or slower rate than previous years?

Average asking rent price in select Census Metropolitan Areas by rental unit type. The breakdown by number of bedrooms is provided only for apartments. The results are based on an experimental approach, meaning they are derived from recent methodologies and may be subject to revisions. Quarterly data are available starting from the first quarter of 2019.

Renting an apartment in Cambridge cost on average ***** British pounds per month in July 2025. This made it one of the most expensive cities for renters in the UK after London. In London region, the average rent amounted to ***** British pounds. According to the source, this figure shows the asking rent, adjusted for achieved rents. A comparison of the rent prices of different London boroughs shows that costs may vary by several hundred and even over a thousand British pounds. Looking at the regional prices, Northern Ireland, Wales, and the Northeast emerged as the regions with the most affordable rents.

Rents in Germany continued to increase in all seven major cities in 2024. The average rent per square meter in Munich was approximately **** euros — the highest in the country. Conversely, Düsseldorf had the most affordable rent, at approximately **** euros per square meter. But how does renting compare to buying? According to the house price to rent ratio, house prices in Germany have risen faster than rents, making renting more affordable than buying. Affordability of housing in Germany In 2023, Germany was among the European countries with a relatively high house price to income ratio in Europe. The indicator compares the affordability of housing across OECD countries and is calculated as the nominal house prices divided by nominal disposable income per head, with 2015 chosen as a base year. Between 2012 and 2022, property prices in the country rose much faster than income, with the house price to income index peaking at *** index points at the beginning of 2022. Slower house price growth in the following years has led to the index declining, as incomes catch up. Nevertheless, homebuyers in 2024 faced significantly higher mortgage interest rates, contributing to a higher final cost. How much does buying a property in Germany cost? Just as with renting, Munich was the most expensive city for newly built apartments. In 2024, the cost per square meter in Munich was almost ***** euros pricier than in the runner-up city, Frankfurt. Detached and semi-detached houses are usually more expensive. The price gap between Munich and the second most expensive city, Stuttgart, was nearly ***** euros per square meter.

Rental prices for Canada. The data give prices for 1-bedroom, 2-bedroom, 3-bedroom and Bachelor (studio) units. The data runs from 1987 until 2020.

The rental prices are average for the year, and included both vacant as well as occupied units.

This is a good beginner dataset for practicing simple data analysis or visualization.

Source - StatCan

There are 4 CSV files, one for each unit type- One Bedroom, Two Bedroom, Three Bedroom and Bachelors

The dataset has the following columns: City- Name of the City Province- Name of the province where the city is 1987- Average rental price for the unit for that year 1987 1988- Average rental price for the unit for that year 1988 .. 2020- Average rental price for the unit for that year 2020

All rental prices are in Canadian Dollars.

Median monthly rental prices for the private rental market in England by bedroom category, region and administrative area, calculated using data from the Valuation Office Agency and Office for National Statistics.

United States US: Price to Rent Ratio: sa data was reported at 133.530 2015=100 in 2024. This records an increase from the previous number of 133.173 2015=100 for 2023. United States US: Price to Rent Ratio: sa data is updated yearly, averaging 89.750 2015=100 from Dec 1970 (Median) to 2024, with 55 observations. The data reached an all-time high of 137.339 2015=100 in 2022 and a record low of 89.750 2015=100 in 1997. United States US: Price to Rent Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by rent price indices