| Name | n3_chennan_CS_ershoufang_liebiao_com |
|---|---|
| Data | 3.20G (+ 0B) |
| Tables | 8 (+ 0) |
| Columns | 42 (+ 0) |
| Table Rows | 12,476,776 (+ 0) |
| Media | 812.84M (+ 0B) |
| Files | 8,396 (+ 0) |
| Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
这是一个全国二手房信息数据库，共有2,646,914个二手房信息记录。这些二手房信息来源于全国363个城市。每个二手房信息中有发布时间，价格，房屋描述，单价，房型，小区名字，房屋情况，地址，联系人，联系电话等。除此之外，数据库中还包含有79,284个房屋详情描述和51,102张房屋图片。该二手房数据库共有8个表。
From this China second-hand houses data, there are 2,646,914 second-hand housing records with release time, price, description, unit price, house layout, name of residential area, state of the house, address, contact, telephone number, etc. in each. All these second-hand houses are from 363 cities in China. It also has other 2 most related tables, they are 79,284 detailed of description records and 51,102 photos of these houses. The whole China second-hand houses database totally has 8 tables.
| Tables | Rows | Columns | Non-empty |
|---|---|---|---|
| ershoufang | 2,646,914 | fangwu_miaoshu |
92.71%
|
| tese_biaoqian |
2.31%
|
||
| lianxi_dianhua |
92.78%
|
||
| lianxiren |
80.52%
|
||
| dizhi |
92.78%
|
||
| fangwu_qingkuang |
88.2%
|
||
| xiaoqu_mingzi |
4.18%
|
||
| fangxing |
92.65%
|
||
| danjia |
92.45%
|
||
| jiage |
100%
|
||
| fabu_shijian |
100%
|
||
| title |
100%
|
||
| ershoufang_x_xiangqing_miaoshu | 7,051,836 | xiangqing_miaoshu_id |
100%
|
| ershoufang_id |
100%
|
||
| chengshi | 363 | title |
100%
|
| xiangqing_miaoshu | 79,284 | value |
100%
|
| key |
100%
|
||
| image | 51,102 | ershoufang_id |
100%
|
| category_1_x_ershoufang | 2,646,914 | ershoufang_id |
100%
|
| category_1_id |
100%
|
||
| category_1 | 363 | chengshi_id |
100%
|
| chengshi |
100%
|
| Size (Bytes) | Files |
|---|---|
| 812.84M | 8,396 |
| Time | Data | Tables | Columns | Rows | Media | Files |
|---|---|---|---|---|---|---|
| 2023-06-19 (+ 169 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2023-01-01 (+ 95 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2022-09-27 (+ 271 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2021-12-30 (+ 115 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2021-09-05 (+ 150 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2021-04-08 (+ 68 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2021-01-29 (+ 120 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2020-10-01 (+ 38 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2020-08-23 (+ 141 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2020-04-04 (+ 196 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (+ 0B) | 8,396 (+ 0) |
| 2019-09-21 (+ 197 d) | 3.20G (+ 0B) | 8 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 812.84M (- 26.55M) | 8,396 (- 10) |
| 2019-03-07 (+ 43 d) | 3.20G (+ 2.69M) | 8 (+ 1) | 42 (+ 0) | 12,476,776 (+ 0) | 839.38M (+ 839.38M) | 8,406 (+ 8,406) |
| 2019-01-23 (+ 44 d) | 3.20G (+ 0B) | 7 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-12-09 (+ 29 d) | 3.20G (+ 0B) | 7 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-11-09 (+ 27 d) | 3.20G (+ 2.17G) | 7 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-10-13 (+ 29 d) | 1.03G (+ 0B) | 7 (+ 0) | 42 (+ 0) | 12,476,776 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-09-13 (+ 34 d) | 1.03G (+ 0B) | 7 (+ 0) | 42 (+ 0) | 12,476,776 (+ 1,876,587) | 0B (+ 0B) | 0 (+ 0) |
| 2018-08-09 (+ 27 d) | 1.03G (+ 0B) | 7 (+ 0) | 42 (+ 0) | 10,600,189 (+ 2,919,356) | 0B (+ 0B) | 0 (+ 0) |
| 2018-07-12 | 1.03G | 7 | 42 | 7,680,833 | 0B | 0 |
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