Name | n3_chennan_CS_lvshishiwusuo_chinalawedu_com |
---|---|
Data | 9.73M (+ 0B) |
Tables | 5 (+ 0) |
Columns | 26 (+ 0) |
Table Rows | 54,908 (+ 0) |
Media | 0B (+ 0B) |
Files | 0 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
来自全国2,312个城市的8,606家律师事务所。这些律师事务所按照业务范围被分为以下6大类,分别是民事类、经济类,刑事行政,涉外,公司专项法律服务和其它非诉讼法律事务。每个律师事务所包含有联系方式和地址。这个全国律师事务所共有5个表。
From this lawyer offices database, it has 8,606 records from 2,312 cities of China. Each lawyer office consists of contact information and address. All these lawyer offices are classified into 6 categories and they are civil legal affairs, economic legal affairs, criminal administrative legal affairs, foreign legal affairs, company's special legal services and other non-litigation legal matters. The whole China lawyer offices database totally has 5 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
category_1 | 6 | title |
100%
|
category_2 | 68 | title |
100%
|
category_1_id |
100%
|
||
chengshi | 2,312 | title |
100%
|
category_2_id |
100%
|
||
category_2 |
100%
|
||
chengshi_x_lvshishiwusuo | 43,916 | chengshi_id |
100%
|
lvshishiwusuo_id |
100%
|
||
lvshishiwusuo | 8,606 | title |
100%
|
lianxi_fangshi |
100%
|
||
dizhi |
88.89%
|
No media sets.
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2023-01-01 (+ 95 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2022-09-27 (+ 271 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-12-30 (+ 115 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-09-05 (+ 150 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-04-08 (+ 68 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-01-29 (+ 120 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-10-01 (+ 38 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-08-23 (+ 141 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-04-04 (+ 196 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-09-21 (+ 197 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-03-07 (+ 43 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-01-23 (+ 44 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-12-09 (+ 29 d) | 9.73M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-11-09 (+ 27 d) | 9.73M (- 1.06M) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-10-13 (+ 29 d) | 10.80M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 10.80M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 10.80M (+ 0B) | 5 (+ 0) | 26 (+ 0) | 54,908 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 | 10.80M | 5 | 26 | 54,908 | 0B | 0 |
Contact us for pricing to download the latest commit / release of this database.
In the same time, you can also access this data set via API.
Select a membership plan and sign up. Return to this page, click Online Query to access the API query maker. Create and open an API call to acquire the data.
The scanning and profiling of data size increments are done separately from those of the number of rows.
Subscribe to be notified of major data releases and updates.
STAY IN THE LOOP.