Name | n3zm_QuanGuoYiLiaoJiGou_pharmnet_com_cn |
---|---|
Data | 18.48M (+ 0B) |
Tables | 4 (+ 0) |
Columns | 34 (+ 0) |
Table Rows | 55,614 (+ 0) |
Media | 0B (+ 0B) |
Files | 0 (+ 0) |
Last Commit | 2023-06-19 19:57:45 (+ 169 d) |
这是一个来自全国34个省,494个市的27,543个医疗机构信息数据库。每个医疗机构包含有医院地址,邮编,联系电话,医院名称,等级,类型,病床数,门诊量,地址等。该全国医疗机构信息数据库共有4个表。
In the medical institutions database, there are 27,543 records from 494 cities of 34 provinces in China. Each medical institution is comprised of hospital address, zip codes, contact telephone, name, level, type, number of beds, outpatient, address, etc. The whole China medical institutions totally has 4 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
sheng | 34 | title |
100%
|
shi | 494 | title |
100%
|
sheng_id |
100%
|
||
sheng |
100%
|
||
shi_x_yiliao_jigou | 27,543 | shi_id |
100%
|
yiliao_jigou_id |
100%
|
||
yiliao_jigou | 27,543 | yiyuan_dixzhi |
99.91%
|
youbian |
99.99%
|
||
lianxi_dianhua |
97.66%
|
||
yiyuan_mingcheng |
95.93%
|
||
dengji |
39.32%
|
||
leixing |
44.76%
|
||
shifouyibaodingdian |
95.93%
|
||
bingchuangshu |
51.47%
|
||
menzhenliang |
49.08%
|
||
dizhi |
95.84%
|
||
wangzhi |
13.75%
|
||
chengche_luxian |
8.06%
|
||
zhuyao_shebei |
32.36%
|
||
tese_zhuanke |
43.24%
|
||
yiyuan_jieshao |
1.5%
|
No media sets.
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2023-01-01 (+ 95 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2022-09-27 (+ 271 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-12-30 (+ 115 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-09-05 (+ 150 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-04-08 (+ 68 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-01-29 (+ 120 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-10-01 (+ 38 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-08-23 (+ 141 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-04-04 (+ 196 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-09-21 (+ 197 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-03-07 (+ 43 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-01-23 (+ 44 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-12-09 (+ 29 d) | 18.48M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-11-09 (+ 27 d) | 18.48M (+ 32K) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-10-13 (+ 30 d) | 18.45M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 18.45M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 18.45M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 (+ 31 d) | 18.45M (+ 0B) | 4 (+ 0) | 34 (+ 0) | 55,614 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-06-10 | 18.45M | 4 | 34 | 55,614 | 0B | 0 |
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