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TwitterReal estate ads in Russia are published on the websites avito.ru, realty.yandex.ru, cian.ru, sob.ru, youla.ru, n1.ru, moyareklama.ru. The ads-api.ru service allows you to upload real estate ads for a fee. The parser of the service works strangely and duplicates real estate ads in the database if the authors extended them after some time. Also in the Russian market there are a lot of outbids (bad realtors) who steal ads and publish them on their own behalf. Before publishing this dataset, my task was to select the original ad from a bunch of ads. Russian real estate services allow ad authors to manually write data about an apartment or house. Therefore, it often happens that a user can publish an ad with errors or typos. Also, the user may not know, for example, the type of walls near his house. The user also specifies the address of the object being sold. He may make a mistake and simply indicate the address, for example, "Moscow". Which street? Which house? We will never know.
The real estate market in Russia is of two types, in the dataset it is used as object type 0 - Secondary real estate market; 2 - New building. I found it necessary to determine the geolocation for each ad address and add the coordinates to this dataset. Also there is a number of the region of Russia. For example, the number of the Chuvash region is 21. Additionally, there is a house number that is synchronized through the federal public database of the Federal Tax Service "FIAS". Since the data is obtained through a paid third party service, I cannot publish the results, however, I can anonymize them and publish parameters such as Street ID and House ID. Basically, all houses are built from blocks such as brick, wood, panel and others. I marked them with numbers: building type - 0 - Don't know. 1 - Other. 2 - panel. 3 - Monolithic. 4 - Brick. 5 - blocky. 6- Wooden
The number of rooms can also be as 1, 2 or more. However, there is a type of apartment that is called a studio apartment. I've labeled them "-1".
I hope that the publication of this dataset will improve developments in the field of global real estate. You can create apartment price forecasts. You can analyze real estate markets. You can understand that there is a need to publish free real estate datasets. And much more
The license for this dataset is public, you can use it in your scientific research, design work and other works. The only condition is the publication of a link to this dataset. You can send suggestions (or complaints) on the dataset by mail daniilakk@gmail.com
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TwitterResidential real estate prices have been steadily growing in Russia both in the primary and the secondary market over the observed period. After a brief decline at the beginning of 2012, price growth resumed over the following years. In the second quarter of 2024, the average square meter price of residential estate in the country was measured at around ******* Russian rubles for new construction and at ******* Russian rubles for the second-hand properties.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Housing Index in Russia decreased to 104.69 points in the third quarter of 2025 from 105.12 points in the second quarter of 2025. This dataset provides - Russia House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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In 2023, the Russia Real Estate Market reached a value of USD 216.4 million, and it is projected to surge to USD 356.7 million by 2030.
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Twitterhttp://www.gnu.org/licenses/agpl-3.0.htmlhttp://www.gnu.org/licenses/agpl-3.0.html
The dataset consists of lists of unique objects of popular portals for the sale of real estate in Russia. More than 540 thousand objects. The dataset contains 540000 real estate objects in Russia.
The Russian real estate market has a relatively short history. In the Soviet era, all properties were state-owned; people only had the right to use them with apartments allocated based on one's place of work. As a result, options for moving were fairly limited. However, after the fall of the Soviet Union, the Russian real estate market emerged and Muscovites could privatize and subsequently sell and buy properties for the first time. Today, Russian real estate is booming. It offers many exciting opportunities and high returns for lifestyle and investment. The real estate market has been in a growth phase for several years, which means that you can still find properties at very attractive prices, but with good chances of increasing their value in the future.
The dataset has 13 fields. - date - date of publication of the announcement; - time - the time when the ad was published; - geo_lat - Latitude - geo_lon - Longitude - region - Region of Russia. There are 85 subjects in the country in total. - building_type - Facade type. 0 - Other. 1 - Panel. 2 - Monolithic. 3 - Brick. 4 - Blocky. 5 - Wooden - object_type - Apartment type. 1 - Secondary real estate market; 2 - New building; - level - Apartment floor - levels - Number of storeys - rooms - the number of living rooms. If the value is "-1", then it means "studio apartment" - area - the total area of ​​the apartment - kitchen_area - Kitchen area - price - Price. in rubles
The dataset may contain erroneous data due to input errors on services, as well as outliers, and so on.
Using this dataset, we offer Kagglers algorithms that use a wide range of functions to predict real estate prices. Competitors will rely on a vast dataset that includes housing data and macroeconomic models. An accurate forecasting model provides more confidence to its clients in a volatile economy.
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Twitterhttps://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for Residential Property Prices for Russian Federation (QRUN628BIS) from Q1 2001 to Q2 2025 about Russia, residential, HPI, housing, price index, indexes, and price.
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Russia Luxury Residential Real Estate Market Report is Segmented by Property Type (Apartments & Condominiums, Villas & Landed Houses), by Business Model (Sales and Rental), by Mode of Sale (Primary (New-Build) and Secondary (Existing-Home Resale)), and by City (Moscow, St. Petersburg, Kazan and Other Cities). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.
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TwitterThe real estate transaction value in the 'Residential Real Estate Transactions' segment of the real estate market in Russia was modeled to amount to ************* U.S. dollars in 2024. Following a continuous upward trend, the real estate transaction value has risen by ************* U.S. dollars since 2017. Between 2024 and 2029, the real estate transaction value will rise by ************ U.S. dollars, continuing its consistent upward trajectory.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Residential Real Estate Transactions.
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TwitterUSD 346.07 Billion in 2024; projected USD 535.06 Billion by 2033; CAGR 4.95%.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Key information about House Prices Growth
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TwitterMoscow was the leading city in the secondary housing market in Russia by price per square meter in June 2024. The price of an apartment on the secondary market in the capital stood at 333,000 Russian rubles per square meter, which was around 64 percent higher than the price level in Saint Petersburg.
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TwitterComprehensive real estate market data and investment metrics for Country RUSSIA
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TwitterIn the first nine months of 2021, most of the investment volume for real estate was attributed to the capital of the country. Investment volume share attributable to St. Petersburg was measured at ** percent of the total over the period under consideration.
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TwitterIn the first six months of 2024, almost half of commercial property in Russia was funded by developers, while the second-largest share was financed by investment companies and private investors. Furthermore, ** percent of investment was funded by end users.
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TwitterUSD 11.38 Billion in 2024; projected USD 19.5 Billion by 2033; CAGR 6.21%.
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Twitterhttps://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy
Discover the latest insights into Russia's luxury residential real estate market. Explore growth trends, key drivers, and market segmentation in Moscow, St. Petersburg, and other major cities. Learn about leading developers and the impact of geopolitical factors. Forecast to 2033. Key drivers for this market are: Increasing construction spending by governments, Growing popularity of interior design and architecture is likely to increase the demand for polymer sheets. Potential restraints include: Shortage of Raw Materials. Notable trends are: Growth in the Apartment Buildings Driving the Market.
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Russia Luxury Residential Real Estate comes with extensive industry analysis of development components, patterns, flows, and sizes. The report calculates present and past market values to forecast potential market management during the forecast period between 2025 - 2033.
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This dataset was created by Muhammad Hanzla Tahir
Released under MIT
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TwitterIn the first three months of 2023, total investment in Russian commercial real estate amounted to roughly *** billion Russian rubles. The 2022 investment was the highest over the observed period, having exceeded *** billion Russian rules. In 2014, investment levels in commercial property nearly halved compared to 2011.
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TwitterSignificant reductions in investments in retail real estate were forecasted in Russia for 2019 and 2020 years. The investment share in office real estate was expected to stabilize at ** percent of the total, while nearly one fourth of funds were projected to go for warehouse real estate in 2020.
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TwitterReal estate ads in Russia are published on the websites avito.ru, realty.yandex.ru, cian.ru, sob.ru, youla.ru, n1.ru, moyareklama.ru. The ads-api.ru service allows you to upload real estate ads for a fee. The parser of the service works strangely and duplicates real estate ads in the database if the authors extended them after some time. Also in the Russian market there are a lot of outbids (bad realtors) who steal ads and publish them on their own behalf. Before publishing this dataset, my task was to select the original ad from a bunch of ads. Russian real estate services allow ad authors to manually write data about an apartment or house. Therefore, it often happens that a user can publish an ad with errors or typos. Also, the user may not know, for example, the type of walls near his house. The user also specifies the address of the object being sold. He may make a mistake and simply indicate the address, for example, "Moscow". Which street? Which house? We will never know.
The real estate market in Russia is of two types, in the dataset it is used as object type 0 - Secondary real estate market; 2 - New building. I found it necessary to determine the geolocation for each ad address and add the coordinates to this dataset. Also there is a number of the region of Russia. For example, the number of the Chuvash region is 21. Additionally, there is a house number that is synchronized through the federal public database of the Federal Tax Service "FIAS". Since the data is obtained through a paid third party service, I cannot publish the results, however, I can anonymize them and publish parameters such as Street ID and House ID. Basically, all houses are built from blocks such as brick, wood, panel and others. I marked them with numbers: building type - 0 - Don't know. 1 - Other. 2 - panel. 3 - Monolithic. 4 - Brick. 5 - blocky. 6- Wooden
The number of rooms can also be as 1, 2 or more. However, there is a type of apartment that is called a studio apartment. I've labeled them "-1".
I hope that the publication of this dataset will improve developments in the field of global real estate. You can create apartment price forecasts. You can analyze real estate markets. You can understand that there is a need to publish free real estate datasets. And much more
The license for this dataset is public, you can use it in your scientific research, design work and other works. The only condition is the publication of a link to this dataset. You can send suggestions (or complaints) on the dataset by mail daniilakk@gmail.com