daniilak/Russia_Real_Estate_2018_2021

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license: cc
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### Context

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.

### Content
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.

### Dataset
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

### Attention.
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.

原始信息汇总

数据集概述

数据集内容

• 类型：俄罗斯房地产数据集
• 规模：包含540,000个独特的房地产对象

数据集结构

• 字段数量：13个
• 详细字段：
  • date - 广告发布日期
  • time - 广告发布时间
  • geo_lat - 纬度
  • geo_lon - 经度
  • region - 俄罗斯地区（共85个主体）
  • building_type - 建筑立面类型（0-其他, 1-面板, 2-整体浇筑, 3-砖, 4-块状, 5-木）
  • object_type - 公寓类型（1-二手房市场, 2-新房）
  • level - 公寓楼层
  • levels - 楼层总数
  • rooms - 居住室数（-1表示工作室公寓）
  • area - 公寓总面积
  • kitchen_area - 厨房面积
  • price - 价格（卢布）

注意事项

• 数据集可能包含由于服务输入错误导致的错误数据，以及异常值等。