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.

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.

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.

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 ...).

What is Rental Data?

Rental data encompasses detailed information about residential rental properties, including single-family homes, multifamily units, and large apartment complexes. This data often includes key metrics such as rental prices, occupancy rates, property amenities, and detailed property descriptions. Advanced rental datasets integrate listings directly sourced from property management software systems, ensuring real-time accuracy and eliminating reliance on outdated or scraped information.

Additional Rental Data Details

The rental data is sourced from over 20,000 property managers via direct feeds and property management platforms, covering over 30 percent of the national rental housing market for diverse and broad representation. Real-time updates ensure data remains current, while verified listings enhance accuracy, avoiding errors typical of survey-based or scraped datasets. The dataset includes 14+ million rental units with detailed descriptions, rich photography, and amenities, offering address-level granularity for precise market analysis. Its extensive coverage of small multifamily and single-family rentals sets it apart from competitors focused on premium multifamily properties.

Rental Data Includes:

• Property Types
• Single-Family Rentals
• Small Multi-family Units
• Premium Apartments
• 16,000+ ZIP Codes
• 800+ MSAs
• Pricing Trends
• Lease Terms Amenities

Rental price statistics historical data time series (indices and annual percentage change). These are official statistics in development.

Renting data center space in the United States has been becoming increasingly pricier since 2021. Fueled by soaring demand due to the rise of artificial intelligence (AI), the average monthly rent per kilowatt increased from ****** U.S. dollars in 2021 to ****** U.S. dollars in 2024.

I just started to analyze the housing market in the Netherlands. I started with cabernet.nl. I made a data set of 975 available rental properties on this website. I will continue to scrape other websites and then make a bigger data set and go for an analysis.

Private rent price statistics, including indices, annual percentage change and price levels.

The DIY and hardware category was estimated to be the consumer goods category which generated the highest revenue from rentals in 2022 by a considerable margin. According to Statista estimates, the revenue from DIY and hardware rentals was forecast to more than ****** from 2022 to 2026.

Prominent rent growth indices often give strikingly different measurements of rent inflation. We create new indices from Bureau of Labor Statistics (BLS) rent microdata using a repeat-rent index methodology and show that this discrepancy is almost entirely explained by differences in rent growth for new tenants relative to the average rent growth for all tenants. Rent inflation for new tenants leads the official BLS rent inflation by four quarters. As rent is the largest component of the consumer price index, this has implications for our understanding of aggregate inflation dynamics and guiding monetary policy. Download NTRR and ATRR indices through 2022q3 here.

Graph and download economic data for Rental Vacancy Rate in the United States (RRVRUSQ156N) from Q1 1956 to Q2 2025 about vacancy, rent, rate, and USA.

This table contains 15 series, with data for years 1997 - 2012 (not all combinations necessarily have data for all years), and was last released on 2015-06-22. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), North American Industry Classification System (NAICS) (3 items: Consumer goods and general rental; Consumer goods rental; General rental centres ...), Summary statistics (5 items: Operating revenue; Operating expenses; Salaries; wages and benefits; Operating profit margin ...).

In 2024, the most expensive residential rental market in Europe was Luxembourg with rental costs of approximately *****euros per square meter.Paris and Dublin followed with rental costs of ***and *****euros per square meter. Rents increased across most markets - a trend that could also be observed in the housing market. How much does an apartment cost in different European cities? Renting a furnished studio apartment in some of the leading cities in Europe can cost anywhere between *** euros monthly (Budapest) and ***** euros (Amsterdam) per month. For a furnished one-bedroom apartment in Paris, France, one may be expected to pay on average ***** euros monthly. Which countries have the most affordable housing? The house price to rent ratio is an indicator of the affordability of owning housing over renting across European countries and is calculated as the nominal house prices divided by a rent price index. The higher the ratio, the more the gap between house prices and rental rates has widened since 2015 when the index base was 100. As of the first quarter of 2025, Finland, Italy, and Romania had the lowest house price to rent ratio, meaning that buying a house was most affordable there compared to renting.

Commercial rents services price index (CRSPI) by North American Industry Classification System (NAICS). Monthly data are available from January 2006 for the total index and from January 2019 for all other indexes. The table presents data for the most recent reference period and the last five periods. The base period for the index is (2019=100).

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 ...

The data set contains the number of motor vehicle rental companies registered in the specified period and the number of rental cars.

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?