The median monthly rent for all apartment types in the U.S. has stabilized since 2022, despite some seasonal fluctuations. In January 2026, the monthly rent for a two-bedroom apartment amounted to ***** U.S. dollars. That was an increase from ***** U.S. dollars in January 2021, but a decline from the peak value of ***** U.S. dollars in August 2022. Where are the most expensive apartments in the U.S.? Apartment rents vary widely from state to state. To afford a two-bedroom apartment in California, for example, a renter needed to earn an average hourly wage of nearly ** U.S. dollars. This was approximately double the average wage in Michigan and 2.6 times as much as the average wage in Arkansas, South Dakota, and West Virginia. In fact, rental costs were considerably higher than the hourly minimum wage in all U.S. states. How did rents change in different states in the U.S.? In late 2025, some of the most expensive states to rent an apartment only saw a moderate increase in rental prices. Nevertheless, rents increased in about half of U.S. states as of January 2026. In North Dakota, the annual rental growth was the highest, at almost **** percent.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in Size Class B/C (CUURX000SEHA) from Dec 1997 to Feb 2026 about primary, rent, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

This statistic shows the average monthly cost of owning and renting in the United States in 2018, by state. In Hawaii, the average monthly cost of a home mortgage was ***** U.S. dollars and the average monthly rent was ***** U.S. dollars.

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.

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?

The average monthly rent of apartments in California increased substantially in 2021, followed by a period of stabilization. In January 2026, the average rent of a two-bedroom apartment cost over ***** U.S. dollars, up from ***** U.S. dollars in December 2020 before rents started to rise. Nevertheless, not all cities saw rents rise at the same pace.

The average monthly rent of apartments in Florida increased substantially in 2021, followed by two years of slight decrease. As of ********, the average rent of a two-bedroom apartment in Florida cost ***** U.S. dollars, which was an increase of *** U.S. dollars from ******** when prices started to rise.

Performance measures dataset

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.

For the past decade, buying a home in the UK has been more affordable than renting one, when only considering the monthly costs. The renting versus buying gap fluctuated during the period and in 2016, it reached its highest value of 131 British pounds. In 2023, the monthly costs for a first-time buyer were 1,231 British pounds, compared to 1,258 British pounds for renters. Rental growth vs house price growth Housing costs in the UK have been on an uprise, with both renting and buying a home increasingly unreachable. Though the monthly costs of buying have consistently been lower in the past decade, house price growth has been much stronger than rental growth since the beginning of the pandemic. Additionally, buyers have been affected by the aggressive mortgage rate hikes, making acquiring their first home even less affordable. Barriers to homeownership Buying a home is not straightforward. For younger (18-40) potential first-time buyers, there are a number of barriers. Approximately one in three first-time buyers point out that raising a deposit was the main obstacle. Other reasons stopping buyers were not being able to take out a mortgage on their current income and poor credit ratings. Unsurprisingly, the highest share of people who buy a home with a mortgage was in the age group of 45 to 55-year-olds.

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

Monthly dataset of 1-bedroom multifamily apartment rent prices across major U.S. metropolitan areas, including San Francisco, Los Angeles, Boston, Washington, DC, Miami, Chicago, Dallas, Phoenix, Atlanta, and Houston. The dataset reflects median asking rents observed in October 2025 and is used to analyze pricing trends, affordability shifts, seasonal patterns, and year-over-year changes in the U.S. rental housing market. This dataset includes both national-level pricing benchmarks and metro-level indicators for high-cost, mid-tier, and affordable markets.

New Delhi Rental Property Dataset – Makaan.com

This dataset consists of detailed rental listings of 14,000 residential properties located in New Delhi, India, collected from the real estate portal makaan.com. The data was gathered using web scraping techniques involving BeautifulSoup4 and Regular Expressions (Regex). A total of 700 pages were scraped to compile this dataset.

This dataset is especially useful for beginners in data science looking to explore and practice concepts such as data cleaning, preprocessing, feature engineering, exploratory data analysis, and even machine learning. It contains a variety of real-world attributes related to rental properties, providing a solid foundation for understanding housing market trends in urban India.

📄 Dataset Features

Below are the features included in the dataset:

• Size : The size configuration of the property, usually indicating the number of rooms. For example: 1, 2, 3 BHK or RK (Room-Kitchen unit).

• Size_unit : The unit associated with the property size — either BHK (Bedroom-Hall-Kitchen) or RK (Room-Kitchen). Helps distinguish full apartments from studio-type accommodations.

• Property_type : The type or category of the property. Examples include Apartment, Independent House, Independent Floor, and other residential types listed on makaan.com.

• Location : The neighborhood or locality within New Delhi where the property is situated. Useful for geographic and locality-specific analysis.

• Seller_name : The name of the individual or organization who listed the property on the platform. This can help identify frequent sellers or real estate agencies.

• Seller_type : Classification of the seller into categories such as Owner, Agent, or Builder. Offers insights into listing authenticity and marketing patterns.

• Rent_price : The monthly rental cost of the property in Indian Rupees (INR). A core variable for price analysis and budget comparisons.

• Area_sqft : The built-up or carpet area of the property in square feet. Important for calculating price per square foot and comparing property sizes.

• Status : Indicates the current condition of the property. Can be one of:

  • Refurbished
  • Semi-refurbished
  • Unfurbished

• Security_deposit : The amount required as a refundable security deposit, often a multiple of the monthly rent.

• Bathroom : The total number of bathrooms in the property. Useful for assessing the comfort level, especially for families or shared accommodations.

• Facing_direction : The directional orientation of the property (e.g., East, West, North-East). This is a significant factor in Indian housing due to preferences based on sunlight, ventilation, and Vastu Shastra principles.

Feel free to use this dataset for hands-on practice in data exploration, visualization, modeling, or even creating a rental recommendation system. Let me know if you’d like help getting started! :

This chart shows the monthly housing cost expenses for renters. Gross rent is the agreed upon rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter.

The average monthly home rental payment in the United Kingdom (UK) increased steadily since 2008, reaching 1, 258 British pounds in December 2023. In comparison, the average home buying costs amounted to 1,231 British Pounds that year, meaning that homeowners saved 27 British pounds monthly from the difference.

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?

bar chart showing Illustrative Monthly Rent-to-Price Ratios by Zone

Matanuska-Susitna Borough, AK has an average rent of $1073 per month. Overall, the average rent in Matanuska-Susitna Borough, AK is growing at an average of 2.6% per year. There was neither an increase or a decrease in its average rent in the last two census.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Rent of Primary Residence in Detroit-Warren-Dearborn, MI (CBSA) (CUURA208SEHA) from Dec 1914 to Jan 2026 about Detroit, primary, rent, MI, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

City : City where is house located Town : Town where is house located Neighborhood : Neighborhood where is house located Apartment Type : Type of building House type : Type of house House Age : Date the house was built and time elapsed until today House Size : Area of the house Room Count : Bedroom count + hall count Floor: Floor of the House Furniture : Can rent with a furniture Bathroom Count : Number of bathroom Hand : How many owners of the house. Sıfır means first owner. Heater Type : Type of heater that using heat for house. Heater Fuel : Fuel used for the heater Price : Monthly rent amount