| Name | n3_chennan_CS_yanglaoyuan_yanglao_com_cn |
|---|---|
| Data | 45.66M (+ 0B) |
| Tables | 4 (+ 0) |
| Columns | 38 (+ 0) |
| Table Rows | 82,626 (+ 0) |
| Media | 0B (+ 0B) |
| Files | 0 (+ 0) |
| Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
这是来自全国34个地区的24,996家养老院信息数据库。每家养老院包含有地址，床位数，收费区间，机构介绍，收费标准，服务内容，入住须知，设施，电话，所在地区，机构类型，负责人，成立时间，占地面积等。该养老院数据中还包含有32,600张养老院照片。整个养老院信息数据库中有4个表。
This old people's homes database has 24,996 records from 34 regions in China. Each old people's home is comprised of address, beds, institution profile, charging standard, service content, instructions for admission, facilities, telephone number, location, institution type, person in charge, founded time, area covered, etc. The old people's homes data also comes with 32,600 images of old people's homes in this data. The whole old people's homes data set totally has 4 tables.
| Tables | Rows | Columns | Non-empty |
|---|---|---|---|
| yanglaoyuan | 24,996 | chengli_shijian |
22.36%
|
| zhandi_mianji |
19.54%
|
||
| shouzhu_duixiang |
100%
|
||
| tese_fuwu |
12.35%
|
||
| wangzhi |
100%
|
||
| renqi |
100%
|
||
| title |
100%
|
||
| dizhi |
99.82%
|
||
| chuangweishu |
100%
|
||
| shoufei_qujian |
100%
|
||
| jigou_jieshao |
10.44%
|
||
| shoufei_biaozhun |
99.79%
|
||
| fuwu_neirong |
99.8%
|
||
| ruzhu_xuzhi |
99.82%
|
||
| sheshi |
99.6%
|
||
| dianhua |
0.47%
|
||
| suozai_diqu |
100%
|
||
| jigou_leixing |
100%
|
||
| jigou_xingzhi |
100%
|
||
| fuzeren |
27.54%
|
||
| diqu | 34 | title |
100%
|
| diqu_x_yanglaoyuan | 24,996 | diqu_id |
100%
|
| yanglaoyuan_id |
100%
|
||
| image | 32,600 | yanglaoyuan_id |
100%
|
| alt |
100%
|
No media sets.
| Time | Data | Tables | Columns | Rows | Media | Files |
|---|---|---|---|---|---|---|
| 2023-06-19 (+ 169 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2023-01-01 (+ 95 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2022-09-27 (+ 271 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-12-30 (+ 115 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-09-05 (+ 150 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-04-08 (+ 68 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-01-29 (+ 120 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-10-01 (+ 38 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-08-23 (+ 141 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-04-04 (+ 196 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-09-21 (+ 197 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-03-07 (+ 43 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-01-23 (+ 44 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-12-09 (+ 29 d) | 45.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-11-09 (+ 27 d) | 45.66M (- 2M) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-10-13 (+ 29 d) | 47.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-09-13 (+ 34 d) | 47.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-08-09 (+ 27 d) | 47.66M (+ 0B) | 4 (+ 0) | 38 (+ 0) | 82,626 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2018-07-12 | 47.66M | 4 | 38 | 82,626 | 0B | 0 |
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