| Name | n3_chennan_CS_yanglaoyuan_nbcyl_com |
|---|---|
| Data | 33.08M (+ 0B) |
| Tables | 5 (+ 0) |
| Columns | 36 (+ 0) |
| Table Rows | 74,382 (+ 0) |
| Media | 0B (+ 0B) |
| Files | 0 (+ 0) |
| Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
这是一个全国养老院信息数据库，共计包含有24,107个养老院且每个养老院记录中有占地面积，区域，地址，价格，机构概况，周边，机构设施，机构服务，评分等。这些养老院被分为以下6大分类，分别是养老产业园，老年公寓，护理院，托老所，养老院和敬老院。除此之外，该数据库中还包含有1,204个户型的价格，类型和详情。该养老院信息数据库共有5个表。
In the old people's homes database, there are 24,107 records with area covered, region, address, price, institutional profile, periphery, institutional facilities, institutional service, score, etc. in each. These old people's homes are categorized into 6 types, they are old-age industrial park, apartments for the aged, nursing Homes, homes for the aged, etc. Besides, it has 1,204 layout records with price, type and detail in each. The whole China old people's homes database has 5 tables in total.
| Tables | Rows | Columns | Non-empty |
|---|---|---|---|
| category_1 | 6 | title |
100%
|
| category_1_x_yanglaoyuan | 24,107 | category_1_id |
100%
|
| yanglaoyuan_id |
100%
|
||
| huxing | 1,204 | leixing |
99.92%
|
| jiage |
99.92%
|
||
| xiangqing |
99.92%
|
||
| alt |
100%
|
||
| yanglaoyuan | 24,107 | title |
100%
|
| zhandi_mianji |
4.75%
|
||
| quyu |
100%
|
||
| dizhi |
98.39%
|
||
| chaungwei |
96.9%
|
||
| jiage |
1.9%
|
||
| jigou_gaikuang |
99.94%
|
||
| zhoubian |
46.83%
|
||
| jigou_sheshi |
47.4%
|
||
| jigou_fuwu |
99.99%
|
||
| pingfen |
99.99%
|
||
| yanglaoyuan_x_huxing | 24,958 | yanglaoyuan_id |
100%
|
| huxing_id |
100%
|
No media sets.
| Time | Data | Tables | Columns | Rows | Media | Files |
|---|---|---|---|---|---|---|
| 2023-06-19 (+ 169 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2023-01-01 (+ 95 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2022-09-27 (+ 271 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-12-30 (+ 115 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-09-05 (+ 150 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-04-08 (+ 68 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-01-29 (+ 120 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-10-01 (+ 38 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-08-23 (+ 141 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-04-04 (+ 196 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-09-21 (+ 197 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-03-07 (+ 43 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-01-23 (+ 44 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-12-09 (+ 29 d) | 33.08M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-11-09 (+ 27 d) | 33.08M (+ 20.73M) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-10-13 (+ 29 d) | 12.34M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-09-13 (+ 34 d) | 12.34M (+ 0B) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-08-09 (+ 27 d) | 12.34M (+ 480K) | 5 (+ 0) | 36 (+ 0) | 74,382 (+ 18,591) | 0B (+ 0B) | 0 (+ 0) |
| 2018-07-12 | 11.88M | 5 | 36 | 55,791 | 0B | 0 |
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