Name | n3_chennan_CS_used_car_xian_taoche_com |
---|---|
Data | 36.67M (+ 0B) |
Tables | 7 (+ 0) |
Columns | 36 (+ 0) |
Table Rows | 68,576 (+ 0) |
Media | 2.71G (+ 0B) |
Files | 35,683 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
这是一个中国二手车出售信息数据库,共计有2,496辆二手车, 每辆二手车信息中包含有价格,车主自述,名称,新车价格,参考价格,首付,月供,上牌时间,排量,销售城市等。数据中还包含有1,481个参数配置信息,446个汽车基本信息和35,691张二手车图片。该二手车信息数据库中共有7个表。
This second-hand cars database has 2,496 records with price, description by owner, name, new car price, reference price, down payment, monthly payment, card time, displacement, sale city, etc. in each. Besides, there are other 2 tables mostly related with these used cars in this data, they are parameter configuration with 1,481 records and 446 basic information records. It also comes with 35,691 images of these used cars in the 2.71G media set. The whole Chinese used cars data set has 7 tables in total.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
jibenxinxi | 446 | key |
100%
|
value |
100%
|
||
used_car | 2,496 | cankao_price |
99.84%
|
new_car_price |
99.84%
|
||
name |
99.84%
|
||
chezhuzishu |
53.81%
|
||
price |
100%
|
||
title |
100%
|
||
yuegong |
97.6%
|
||
sale_city |
99.84%
|
||
pailiang |
99.84%
|
||
biaolixiancheng |
99.84%
|
||
shangpai_time |
99.84%
|
||
shoufu |
97.6%
|
||
used_car_x_jibenxinxi | 10,486 | jibenxinxi_id |
100%
|
used_car_id |
100%
|
||
image | 35,691 | used_car_id |
100%
|
canshupeizhi | 1,481 | value |
99.93%
|
key |
100%
|
||
used_car_x_canshupeizhi | 17,976 | canshupeizhi_id |
100%
|
used_car_id |
100%
|
Size (Bytes) | Files |
---|---|
2.71G | 35,683 |
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2023-01-01 (+ 95 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2022-09-27 (+ 271 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2021-12-30 (+ 115 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2021-09-05 (+ 150 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2021-04-08 (+ 68 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2021-01-29 (+ 120 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2020-10-01 (+ 38 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2020-08-23 (+ 141 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2020-04-04 (+ 196 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2019-09-21 (+ 197 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2019-03-07 (+ 43 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2019-01-23 (+ 44 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-12-09 (+ 29 d) | 36.67M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-11-09 (+ 27 d) | 36.67M (+ 7.92M) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-10-13 (+ 29 d) | 28.75M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-09-13 (+ 34 d) | 28.75M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-08-09 (+ 27 d) | 28.75M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-07-12 (+ 31 d) | 28.75M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-06-10 (+ 31 d) | 28.75M (+ 0B) | 7 (+ 0) | 36 (+ 0) | 68,576 (+ 0) | 2.71G (+ 0B) | 35,683 (+ 0) |
2018-05-10 | 28.75M | 7 | 36 | 68,576 | 2.71G | 35,683 |
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.