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README.md

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+Real 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.
+
+# Dataset
+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
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+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".
+
+# Ideas
+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
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+# Others
+
+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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+You can find more information about the data on the website https://dom.realtycloud.ru/