This dataset contains Real Estate Rents listings in the Canada broken by Province and City. Data was collected via web scraping using python libraries.

You may use the dataset for Canada rents houses trend analysis (with respect to the location - province/city/longitude/latitude), regression analysis (price prediction), correlation analysis, etc.,

Content

The dataset has 1 CSV file with 18 columns -

rentfaster.csv (25k+ entries)

-**'rentfaster_id'** - id of property on https://www.rentfaster.com . Can be explore with www.rentfaster.ca/rentfaster_id -**'city'** - city of property like 'Toronto', 'Calgary', 'Vancuver' and etc. -**'province'** - province of property like 'Alberta', 'Ontario' and etc. -**'address'** - address of property like '333 Seymour St' and etc -**'latitude'** - latitude coordinate of rental property -**'longitude'** - longitude coordinate of rental property -**'lease_term'** - category of rental period like 'Long Term', 'Negotiable' and etc -**'type'** - category of type a rental property like 'House', 'Apartment', 'Basement' and etc -**'price'** - price in CAD -**'beds'** - count of bedrooms -**'baths'** - count of bathrooms -**'sq_feet'** - area of rental property in square feets -**'link'** - right side of url for getting full details of the property rentfaster.com+'link' -**'furnishing'** - Furnished or not -**'availability_date'** - Date of availability -**'smoking'** - is allow smoke -**'cats'** - is allow cats -**'dogs'** - is allow dogs

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.

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

Discover the booming rental housing market! Explore key trends, drivers, and challenges impacting this multi-trillion dollar industry. Learn about top players like Airbnb and Zillow, regional market share, and future growth projections to 2033. Get insights to inform your investment or business strategy.

Revenue for apartment lessors has expanded through the end of 2025. Apartment lessors collect rental income from rental properties, where market forces largely determine their rates. The supply of apartment rentals has grown more slowly than demand, which has elevated rental rates for lessors' benefit. As the Federal Reserve hiked interest rates 11 times between March 2022 and January 2024, homeownership was pushed beyond the reach of many, resulting in a tighter supply and increased demand for rental properties. Despite three interest rate cuts in 2024, mortgage rates have remained stubbornly high in 2025, encouraging consumers to rent. Revenue has climbed at a CAGR of 2.6% over the past five years and is expected to reach $295.3 billion by the end of 2025. This includes an anticipated 1.4% gain in 2025 alone. The increasing unaffordability of housing is caused by the steady climb of mortgage rates and high prices maintained by a low supply. Supply has been held down as buyers who locked in low rates stay put, and investment groups hold a strategic number of their properties empty as investments. Industry profit has remained elevated because of solid demand for apartment rentals. Through the end of 2030, the apartment rental industry's future performance will be shaped by varying factors. The apartment supply in the US, which hit a record in 2024, is expected to taper off, which will push rental prices and occupancy rates up to the lessors' benefit. Other factors, such as interest rate cuts, decreasing financial barriers to homeownership and a high rate of urbanization, will also significantly impact the industry. With an estimated 80.7% of the US population living in urban areas, demand for apartment rentals will strengthen, although rising rental prices could force potential renters to cheaper suburbs. Demand will continue to outpace supply growth, prompting a climb in revenue. Revenue is expected to swell at a CAGR of 1.7% over the next five years, reaching an estimated $321.9 billion in 2030.

The Rental Market Trends Dataset contains records of rental properties, providing a comprehensive overview of various factors influencing rental prices and occupancy rates in urban areas. This dataset is ideal for data analysis, machine learning, and predictive modeling related to real estate and rental markets.

This dataset provides monthly rental price statistics for apartments across urban neighborhoods, including average, median, minimum, and maximum rents by apartment type and location. It enables detailed market trend analysis, investment strategy development, and urban planning by offering granular insights into rental dynamics over time. The dataset is ideal for real estate professionals, investors, and researchers seeking to understand rental market fluctuations.

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.

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

The apartment rental market in the United States has been stagnating since 2019, after increasing year-on-year for several years. In 2022, the estimated market size of apartment rental was ***** billion U.S. dollars, down from ***** billion U.S. dollars in 2021. In 2023, the market is forecast to further contract by one percent, reaching ***** billion U.S. dollars.

Explore the dynamic Real Estate Rental market forecast (2025-2033) with key insights, drivers, and trends. Discover market size, CAGR, and regional growth opportunities for residential and non-residential rentals.

The median monthly rent for all apartment types in the U.S. has stabilized since 2022, despite some seasonal fluctuations. In August 2025, 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 North Carolina and three times as much as the average wage in Arkansas. 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 2025, some of the most expensive states to rent an apartment only saw a moderate increase in rental prices. Nevertheless, rents increased in most states as of August 2025. In West Virginia, the annual rental growth was the highest, at ***** percent.

Discover the booming global housing rental service market! This in-depth analysis reveals a $1.5 trillion market in 2025, growing at a 7% CAGR through 2033. Explore key trends, drivers, restraints, and leading companies shaping this dynamic sector.

Global Real Estate Rental Market is segmented by Application (Residential Rentals_ Commercial Rentals_ Vacation Rentals_ Short-term Rentals_ Long-term Rentals), Type (Apartments_ Houses_ Villas_ Condos_ Commercial Properties), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

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 United States rental rate for residential real estate market was volumed at USD 1.32 per unit per month in 2024. The industry is expected to grow at a CAGR of 5.00% during the forecast period of 2025-2034 to attain a volume of USD 2.15 per unit per month by 2034.

The global House Rental Platforms market is poised for significant expansion, projected to reach an estimated value of $34,500 million by 2025, with a robust Compound Annual Growth Rate (CAGR) of 12.5% expected to propel it to $87,000 million by 2033. This impressive growth is primarily fueled by the increasing demand for flexible and convenient housing solutions, particularly among younger generations like millennials and Gen Z. The platform's ability to streamline the rental process, from property discovery and virtual tours to lease agreements and payment management, addresses key pain points for both renters and landlords. The burgeoning short-term rental market, driven by tourism and the rise of the gig economy, alongside the steady demand for long-term apartment and house rentals, are significant contributors to this upward trajectory. Technology advancements, including AI-powered search filters, virtual reality property viewings, and secure online payment systems, are further enhancing user experience and driving platform adoption. Key drivers for this market's ascent include urbanization, a growing preference for renting over homeownership, and the increasing adoption of digital tools for real estate transactions. While the market presents immense opportunities, certain restraints such as stringent regulatory frameworks in some regions, potential cybersecurity risks, and the intense competition among established and emerging players could pose challenges. However, the continuous innovation in platform features, the expansion into emerging markets, and strategic partnerships are expected to mitigate these concerns. The market encompasses a diverse range of property types, with apartments and houses dominating the landscape, catering to both long-term lease and short-term rental applications. Leading companies like HousingAnywhere, Rentberry, Spotahome, and Airbnb are at the forefront of shaping this dynamic industry, continuously introducing features to meet evolving consumer needs and solidify their market positions. This report provides a comprehensive analysis of the global house rental platform market, offering insights into its structure, dynamics, and future trajectory. We delve into the competitive landscape, product offerings, regional trends, and the key drivers and challenges shaping this rapidly evolving industry. The report leverages estimated user and transaction data in the millions to paint a clear picture of market scale and player influence.

The online home rental market is set to experience significant growth from 2025 to 2035, driven by increasing urbanization, rising digital adoption, and the growing demand for flexible living solutions. The market is expected to expand from USD 20.4 billion in 2025 to USD 82.5 billion by 2035, reflecting a CAGR of 14.2% during the forecast period.

Metric	Value
Industry Size (2025E)	USD 20.4 billion
Industry Value (2035F)	USD 82.5 billion
CAGR (2025 to 2035)	14.2%

Global Online Home Rental Market - Country-Wise Per Capita Spending

Country	United States
Population (millions)	345.4
Estimated Per Capita Spending (USD)	145.20

Country	United Kingdom
Population (millions)	68.3
Estimated Per Capita Spending (USD)	132.50

Country	Germany
Population (millions)	83.2
Estimated Per Capita Spending (USD)	120.80

Country	France
Population (millions)	65.6
Estimated Per Capita Spending (USD)	110.30

Country	Canada
Population (millions)	39.2
Estimated Per Capita Spending (USD)	138.60

Country-Wise Outlook

Country	CAGR (2025 to 2035)
United States	6.8%

Country	CAGR (2025 to 2035)
United Kingdom	6.5%

Country	CAGR (2025 to 2035)
Germany	6.7%

Country	CAGR (2025 to 2035)
India	7.5%

Country	CAGR (2025 to 2035)
China	8.1%

Competition Outlook

Estimated Market Share (%), 2024
Airbnb	20-25%
Zillow Rentals	15 to 20%
Realtor.com	12-16%
Apartments.com ( CoStar Group)	10-14%
Other Companies (combined)	35-45%

The net operating income comprised ** percent of the revenues of the conventional apartment rental market in the United States as of August 2022. During the same period, almost ** percent of leases were renewed, with renewal leases achieving on average ** percent increase in rental rates.

The global Housing Rental Service market is poised for significant expansion, projected to reach approximately USD 1,500 million by 2025, with an anticipated Compound Annual Growth Rate (CAGR) of 12% through 2033. This robust growth is fueled by a confluence of evolving lifestyle preferences and economic realities. Increasing urbanization continues to drive demand for rental accommodations, particularly in major metropolitan areas. Furthermore, the growing popularity of short-term rentals, facilitated by digital platforms, caters to the burgeoning tourism and business travel sectors. Concurrently, long-term leases remain a cornerstone of the market, offering stability for both renters and property owners. Key drivers include the increasing cost of homeownership, particularly for younger demographics, and a greater emphasis on flexibility and mobility in career choices. The market is also benefiting from technological advancements that streamline the rental process, from property discovery and application to lease management and payment. The competitive landscape of the Housing Rental Service market is characterized by a dynamic mix of established property management firms and innovative digital platforms. Companies like Invitation Homes, Vacasa, and HousingAnywhere are at the forefront, leveraging technology to enhance user experience and operational efficiency. The market is segmented by application into Personal and Commercial, with Personal rentals constituting the larger share due to widespread individual housing needs. Within types, both Short-term Rental and Long-term Lease segments are experiencing healthy growth. Geographically, North America is expected to maintain a dominant market share, driven by strong economies and established rental markets in the United States and Canada. However, Asia Pacific presents a substantial growth opportunity, with rapidly expanding economies and increasing urbanization in countries like China and India. Emerging trends such as co-living spaces and the integration of smart home technologies into rental properties are further shaping the market's trajectory. This report delves into the dynamic and rapidly evolving global housing rental service market. Analyzing data from the historical period of 2019-2024, with a base year of 2025 and a forecast period extending to 2033, this study provides invaluable insights for stakeholders seeking to navigate this complex landscape. The report estimates the market size in millions of units, offering a clear quantitative perspective on growth and demand.