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.

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.

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 agreed rent for new tenancies in the UK ranged from *** British pounds to ***** British pounds, depending on the region. On average, renters outside of London paid ***** British pounds, whereas in London, this figure amounted to ***** British pounds. Rents have been on the rise for many years, but the period after the COVID-19 pandemic accelerated this trend. Since 2015, the average rent in the UK increased by about ** percent, with about half of that gain achieved in the period after the pandemic. Why have UK rents increased so much? One of the main reasons driving up rental prices is the declining affordability of homeownership. Historically, house prices grew faster than rents, making renting more financially feasible than buying. In 2022, when the house price to rent ratio index peaked, house prices had outgrown rents by nearly ** percent since 2015. As house prices peaked in 2022, home buying slowed, exacerbating demand for rental properties and leading to soaring rental prices. How expensive is too expensive? Although there is no official requirement about the proportion of income spent on rent for it to be considered affordable, a popular rule is that rent should not exceed more than ** percent of income. In 2024, most renters in the UK exceeded that threshold, with the southern regions significantly more likely to spend upward of ** percent of their income on rent. Rental affordability has sparked a move away from the capital to other regions in the UK, such as the South East (Brighton and Southampton), the West Midlands (Birmingham) and the North West (Liverpool, Manchester, Blackpool and Preston).

Residential real estate rents in France declined slightly in 2023. Bedrooms for rent and houses made an exception, with the average rent for a bedroom rising to 453 euros per month, and the average rent for a house rising to 1,044 euros per month. A two-room apartment in 2023 cost on average 555 euros, down from 725 euros in 2022.

As of July 2025, the average rent for rental apartments increased in ** of the 50 U.S. metropolitan areas with the largest populations. San Francisco-Oakland-Berkeley, CA was the metro with the highest rental growth, an annual increase of **** percent. Conversely, Austin-Round Rock-Georgetown, TX experienced the highest decline in rents, at ***** percent.

As of January 2025, the rent for a two-bedroom apartment in Hawaii was about 120 U.S. dollars higher than in California. The states of Hawaii and California ranked as the most expensive within the United States for apartment renters. Conversely, an apartment in Arkansas was almost three times more affordable than one in Hawaii.In 2025, the average monthly rent in the U.S. declined slightly. Nevertheless, in rents increased in most states, with West Virginia registering the highest growth.

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.

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.

Rent Inflation in Japan increased to 0.40 percent in October from 0.30 percent in September of 2025. This dataset includes a chart with historical data for Japan Rent Inflation.

Rental Affordability Analysis Based on Median Income

Trends in Tier-Based Affordability Across the U.S

By Zillow Data [source]

About this dataset

This dataset contains rental affordability data for different regions in the US, giving valuable insights into regional rental markets. Renters can use this information to identify where their budget will go the farthest. The cities are organized by rent tier in order to analyze affordability trends within and between different housing stock types. Within each region, the data includes median household income, Zillow Rent Index (ZRI), and percent of income spent on rent.

The Zillow Home Value Forecast (ZHVF) is used to calculate future combined mortgage pay/rent payments in each region using current median home prices, actual outstanding debt amounts and 30-year fixed mortgage interest rates reported through partnership with TransUnion credit bureau. Zillow also provides a breakdown of cash vs financing purchases for buyers looking for an investment or cash option solution.

This dataset provides an effective tool for consumers who want to better understand how their budget fits into diverse rental markets across the US; from condominiums and co-ops, multifamily residences with five or more units, duplexes and triplexes - every renter can determine how their housing budget should be adjusted as they consider multiple living possibilities throughout the country based on real-time price data!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

Introduction

Getting Started

• First, you'll need to download the TieredAffordability_Rental.csv dataset from this Kaggle page onto your computer or device.

• After downloading the data set onto your device, open it with any CSV viewing software of your choice (ex: Excel). It will include columns for RegionName**RegionName** , homes type/housing stock (All Homes or Condo/Co-op) SizeRank , Rent tier tier , Date date , median household income income , Zillow Rent Index zri and PercentIncomeSpentOnRent percentage (what portion of monthly median house-hold goes toward monthly mortgage payment) .

• To begin analyzing rental prices across different regions using this dataset, look first at column four: SizeRank; which ranks each region based on size - smallest regions listed first and largest at last - so that you can compare a similar range of Regions when looking at affordability by home sizes larger than one unit multiplex dwellings.*Duples/Triplex*. Once there is an understanding of how all homes compare overall now it is time to consider home types Multifamily 5+ units according to rent tiers tier .

• Next, choose one or more region(s) for comparison based on their rank in SizeRank column –so that all information gathered about them reflects what portionof households fall into certain categories ; eg; All Homes / Small Home /Large Home / MultiPlex Dwelling and what tier does each size rank falls into eg.: Affordable/Slightly Expensive/ Moderately Expensive etc.. This will enable further abstraction from other elements like date vs inflation rate per month or periodical intervals set herein by Rate segmentation i e dates givenin ‘Date’Columns – making the task easier and more direct while analyzing renatalAffordibility Analysis Based On Median Income zri 00 zwi & PCISOR 00 PCIRO

Research Ideas

• Use the PercentIncomeSpentOnRent column to compare rental affordability between regions within a particular tier and determine optimal rent tiers for relocating families.
• Analyze how market conditions are affecting rental affordability over time by using the income, zri, and PercentageIncomeSpentOnRent columns.
• Identify trends in housing prices for different tiers over the years by comparing SizeRank data with Zillow Home Value Forecast (ZHVF) numbers across different regions in order to identify locations that may be headed up or down in terms of home values (and therefore rent levels)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: TieredAffordability_Rental.csv | Column name | Description | |:-----------------------------|:-------------------------------------------------------------| | RegionName | The name of the region. (String) ...

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.

This table includes figures on the average increase of rent broken down by income class. A distinction is made here between rental of regulated dwellings by social and other landlords, mid-tier rental and liberalised rental.

Data available from: 2015.

Status of the figures: The figures in this table are definitive.

Changes as of 10 October 2025: The figure for the income class ‘Income unknown’ in the category ‘Total; regulated’ has been corrected for the reporting year 2025. In the earlier calculation, not all homes were correctly classified. This has no impact on the other figures in this table.

Changes as of 5 September 2025: The 'Mid-tier rental' category has been added to the dimension 'Type of rental'. The figures of 2025 have been published.

Changes as of 20 May 2025: The figures broken down by income class have been removed from this table for the categories of 'Liberalised rental' and 'Total'. These figures are not applicable and were previously published in error. Landlords can only request income data for regulated rents, which form the basis for this table.

Changes as of 8 September 2023: The category 'Middle income' has been added to the dimension 'Income classes'.

When will new figures be published? New figures of 2026 will become available in September 2026.

This table includes figures on the average rent increase (including and excluding rent harmonisation) of regulated and liberalised dwellings. The data is broken down by part of the country, province and the four major municipalities (Amsterdam, Rotterdam, The Hague and Utrecht).

Data available from: 2015.

Status of the figures: The figures in this table are definitive.

Changes as of 6 September 2021: The figures of 2021 have been published.

When will new figures be published? New figures will become available in September 2022.

Amount charged by Registered Social Landlord (Private Registered Provider (PRP)) Average Weekly Rents for social housing. Data is collected by the Housing Corporation via the annual Regulatory and Statistical Return (RSR) based on general needs stock only. Figures are based on only the larger Registered Social Landlords (RSLs) completing the long form. Upto 2006 the threshold for completing the long form was that the RSL owned/ managed at least 250 units/bedspaces. From 2007 this increased to 1,000 units/bedspaces. The districts, unitary authorities and counties listed above are based on 1 April 1998 boundaries. Figures for any 'new' re-organised areas have been estimated retrospectively applying the new boundaries back to 1997 and making appropriate assumptions. Note that the average RSL rents within a local authority area can move down from one year to the next. This is especially true if, during the latest year, most of the LA stock has been transferred through a large-scale voluntary transfer to the RSL sector. Larger housing associations report the rent they charge in the HCA’s Statistical Data Return. Data in spreadsheet includes average weekly rents for housing association general needs properties by number of bedrooms, in London by borough (stock owned by larger associations only).

This is the average weekly Private Registered Provider (PRP) rent in GBP for the financial year.Until 2011, data was collected by the Tenant Services Authority via the annual Regulatory and Statistical Return (RSR). From 2012, it was collected by the Homes and Communities Agency via the Statistical Data Return (SDR). In 2018, the responsibility for the SDR was moved to the Regulator of Social Housing (RSH).

Figures are based on general needs stock available for social rent only and are only taken from the larger Private Registered Providers (PRPs) completing the long form. Up to 2006, the threshold for completing the long form was that the PRP owned/managed at least 250 units/bed spaces. From 2007, this increased to 1,000 units/bed spaces. From 2012, the threshold for completing the long form of the SDR was that the PRP owned at least 1,000 units/bed spaces.

The average PRP rents within a local authority area can move down from one year to the next. This is especially true if, during the latest year, most of the LA stock has been transferred through a large-scale voluntary transfer to the PRP sector. Averages are calculated for self-contained units only.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

This table includes figures on the average increase of rent paid for dwellings (including and excluding rent harmonisation) of regulated dwellings (broken down by type of landlord), mid-tier dwellings and liberalised dwellings.

Data available from: 2015

Status of the figures:
The provisional figures are published in August and relate to the rent increase as implemented in July. The figures become definitive upon publication in September. Disparities between provisional and definitive figures are caused by new source material.

Changes as of 5 September 2025: Definitive figures of 2025 have been published.

Changes as of 12 August 2025: The Mid-tier rental category has been added to the dimension Type of rental.

When will new figures be published? Provisional figures of 2026 will be published in August 2026.

This table contains the Consumer Price Index (CPI). This index shows the price evolution of a package of goods and services that an average household in the Netherlands buys. The table also shows the derived consumer price index. This is the CPI exclusive influence of government measures such as VAT.

In addition to these indices, the table contains inflation. Inflation as an economic concept is the average price increase of the goods and services consumers buy. Inflation in the Netherlands is measured as the increase in the consumer price index (CPI) compared to the corresponding period in the previous year. The consumer price index shows the price evolution of a package of goods and services as purchased on average by Dutch households. The monthly-on-month development is also shown in the table. You can view these figures about 269 combinations of product groups. For each product group you can also find how much the Dutch consumer spends on it in relation to his total expenditure. This is called the weighting coefficient.

Data available from 1996 to 2015

Status of the figures: The figures in this table are final.

Changes as of 18 May 2016 None, this table has been discontinued.

Changes as of 10 December 2015 As of 1 October, the national government has adjusted the points system for housing rentals. As a result, the rents of a limited number of homes have fallen, so the average rents also decreased. The effect of this rent decrease on the price indices of rent and imputed rent could not be determined earlier, as the housing corporations only announced the extent of the rent adjustments in November. The figures of the groups 04100 ‘Employable rent’ and 04200 ‘Accounted rental own home’ of October 2015 have therefore been adjusted.

The figures for the groups 061100 ‘Self-care medicines, 061200 ‘Other medical products’, 072200 ‘Autofuels’ and 083000 ‘Phone, fax and internet services’ have been updated from June to September 2015. This does not affect the published indices at main level.

The derived CPI has been revised down 0.01 index point over the month of August 2015.

When are new figures coming? This table is followed by consumer prices; price index 2015=100. See paragraph 3.

Real Estate Breakeven Analysis for U.S. Home Types

Buy vs Rent Comparison Across Markets

By Zillow Data [source]

About this dataset

This dataset provides a comprehensive analysis of the current real estate situation in the United States. It includes breakeven analysis charts that compare buying vs renting across major U.S. markets. This dataset contains various metrics such as home types, housing stock, price-to-income ratio, cash buyers, mortgage affordability and rental affordability to name a few. This data has been compiled using Zillow's own data along with TransUnion financing survey data and the Freddie Mac Primary Mortgage Market Survey to provide an accurate understanding of each metro area’s market health and purchasing power for buyers and renters alike. By downloading this information you can compare different regions based on size rank and other factors to get full insights regarding their potential fit for your needs or investments strategies as well as any potential risks associated with each region's housing market health

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset is for real estate professionals, owner-occupants, potential buyers and renters who are interested in understanding which U.S. markets offer the most favorable home buying or rental opportunities from a financial perspective over the long term.

The “Real Estate Breakeven Analysis for U.S Home Types” dataset contains data pulled from Zillow's current and forecasted housing market metrics across many different real estate regions in the United States including cities, counties, states, metro areas and combined statistical areas (CSAs). The data includes several measures of affordability such as median price-to-rent ratio (MedPR), median breakeven horizon (MedBE) - which refers to how long it takes to make up purchase costs when compared with renting; cash purchaser share; mortgage rate; mortgage affordability indices; rental affordability rates etc.

In order to analyze and compare buying vs renting decisions across various regions in the US this dataset provides breakeven analysis at various levels of geographies i.e., state names, region types (city/metro area/county) and show how long it will take homeowners to break even on their purchase costs when compared with renting in that region over a longer period of time using discounted cash flow methodology. This information helps people understand what type of transaction is a better fit for them by weighing short term vs long term goals accordingly by evaluating these different factors related to housing metrics carefully before making financial decisions about purchasing or renting properties in desired location(s).

To use this dataset one can use either basic filters like RegionType or RegionName or more detailed filter criteria like CountyName, City name , Metro area name , State Name etc . For example if someone wanted to look at properties available for rent only then they can apply filters based on Province Type =‘Rental’ Also one can further refine searches based on filtering them with defined SampleRate , Median Price – To – Rent Ratio …..etc . This could be useful if seekers would want only specific type of property like Condominium/Coop /Multifamily 5+ Units /Duplex Triplex listing etc …and then apply other parameters like Cash Buyers percent , Mortgage Affordability Rate….etc ..in order narrow down search results while looking at Breakeven scores /horizons in their target locations . One should take advantages of all relevant parameters while searching through data before making any decision related with owning rental properties so that they can make sure best possible investment decision given

Research Ideas

• Visualizing changes in real estate trends across regions by comparing price to rent ratios, mortgage affordability indices and cash buyers over time.
• Market segmentation analysis based on region-level market characteristics such as negative equity data, rental affordability, median house values and population size.
• Predicting housing demand within a particular region based on its breakeven horizon or price to rent ratio

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: BreakEven_2017-03.csv | Column name | Description | |:----------------|:----------------------------------------------------...

Graph and download economic data for Rental Vacancy Rate for the United States (USRVAC) from 1986 to 2024 about vacancy, rent, rate, and USA.