Russia Real Estate 2018-2021
The dataset contains 540000 real estate objects in Russia.
@kaggle.mrdaniilak_russia_real_estate_20182021
All V2
@kaggle.mrdaniilak_russia_real_estate_20182021.all_v2
- 113.3 MB
- 5477006 rows
- 13 columns
pricePrice | dateDate | timeTime | geo_latGeo Lat | geo_lonGeo Lon | regionRegion | building_typeBuilding Type | levelLevel | levelsLevels | roomsRooms | areaArea | kitchen_areaKitchen Area | object_typeObject Type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6050000 | Mon Feb 19 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 20:00:21 | 59.8058084 | 30.376141 | 2661 | 1 | 8 | 10 | 3 | 82.6 | 10.8 | 1 |
| 8650000 | Tue Feb 27 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 12:04:54 | 55.683807 | 37.297405 | 81 | 3 | 5 | 24 | 2 | 69.1 | 12 | 1 |
| 4000000 | Wed Feb 28 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 15:44:00 | 56.29525 | 44.061637 | 2871 | 1 | 5 | 9 | 3 | 66 | 10 | 1 |
| 1850000 | Thu Mar 01 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 11:24:52 | 44.996132 | 39.074783 | 2843 | 4 | 12 | 16 | 2 | 38 | 5 | 11 |
| 5450000 | Thu Mar 01 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 17:42:43 | 55.918767 | 37.984642 | 81 | 3 | 13 | 14 | 2 | 60 | 10 | 1 |
| 3300000 | Fri Mar 02 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 21:18:42 | 55.908253 | 37.726448 | 81 | 1 | 4 | 5 | 1 | 32 | 6 | 1 |
| 4704280 | Sun Mar 04 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 12:35:25 | 55.6210965 | 37.4310016 | 3 | 2 | 1 | 25 | 1 | 31.7 | 6 | 11 |
| 3600000 | Sun Mar 04 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 20:52:38 | 59.8755262 | 30.3954571 | 2661 | 1 | 2 | 5 | 1 | 31.1 | 6 | 1 |
| 3390000 | Mon Mar 05 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 07:07:05 | 53.1950306 | 50.1069518 | 3106 | 2 | 4 | 24 | 2 | 64 | 13 | 11 |
| 2800000 | Tue Mar 06 2018 00:00:00 GMT+0000 (Coordinated Universal Time) | 09:57:10 | 55.7369718 | 38.8464565 | 81 | 1 | 9 | 10 | 2 | 55 | 8 | 1 |
CREATE TABLE all_v2 (
"price" BIGINT,
"date" TIMESTAMP,
"time" VARCHAR,
"geo_lat" DOUBLE,
"geo_lon" DOUBLE,
"region" BIGINT,
"building_type" BIGINT,
"level" BIGINT,
"levels" BIGINT,
"rooms" BIGINT,
"area" DOUBLE,
"kitchen_area" DOUBLE,
"object_type" BIGINT
);