Name | n3_chennan_CS_jiudian_hotels_ctrip_com |
---|---|
Data | 1.42G (+ 0B) |
Tables | 12 (+ 0) |
Columns | 57 (+ 0) |
Table Rows | 7,694,803 (+ 0) |
Media | 1.84G (+ 0B) |
Files | 49,966 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
全国367个城市的329,923个酒店信息数据库。每个酒店信息中有评分,等级,价格,用户推荐,酒店简介,地址,服务评分,卫生评分等。除此之外,酒店信息中还有261个酒店设施信息, 11,024个酒店政策记录,49,268个周边设施信息和2,677,038张酒店图片。该酒店信息数据库中共有12个表。
From this China hotels database, it contains 329,923 hotels from 367 cities in China. Each hotel is comprised of score, grade, price, customer recommend, hotel profile, address, service rating, health rating, etc. Beside, there are 261 hotel facilities, 11,024 hotel policy records, 49,268 surrounding facilities and 2,677,038 hotel images in this data. The whole China hotels data set totally has 12 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
jiudian_x_jiudian_zhengce | 1,246,531 | jiudian_zhengce_id |
100%
|
jiudian_id |
100%
|
||
zhoubian_sheshi | 49,268 | value |
100%
|
key |
100%
|
||
jiudian_zhengce | 11,024 | value |
99.99%
|
key |
100%
|
||
jiudian_x_zhoubian_sheshi | 76,647 | zhoubian_sheshi_id |
100%
|
jiudian_id |
100%
|
||
jiudian_x_jiudian_sheshi | 2,973,161 | jiudian_sheshi_id |
100%
|
jiudian_id |
100%
|
||
jiudian_sheshi | 261 | value |
100%
|
category_1 | 24 | title |
100%
|
category_2 | 367 | title |
100%
|
category_1_id |
100%
|
||
category_2_x_jiudian | 330,559 | category_2_id |
100%
|
jiudian_id |
100%
|
||
image | 2,677,038 | jiudian_id |
100%
|
jiudian | 329,923 | title |
100%
|
pingfen |
66.5%
|
||
dengji |
33.22%
|
||
jiage |
100%
|
||
yonghu_tuijian |
79.56%
|
||
zhuke_dianping |
28.83%
|
||
zhuke_pinglun |
28.83%
|
||
jiudian_jianjie |
100%
|
||
dizhi |
100%
|
||
weizhi_pingfen |
80.03%
|
||
sheshi_pingfen |
80.03%
|
||
fuwu_pingfen |
80.03%
|
||
weisheng_pingfen |
80.03%
|
Size (Bytes) | Files |
---|---|
1.84G | 49,966 |
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2023-01-01 (+ 95 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2022-09-27 (+ 271 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2021-12-30 (+ 115 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2021-09-05 (+ 150 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2021-04-08 (+ 68 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2021-01-29 (+ 120 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2020-10-01 (+ 38 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2020-08-23 (+ 141 d) | 1.42G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2020-04-04 (+ 196 d) | 1.42G (- 0.71G) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (+ 0B) | 49,966 (+ 0) |
2019-09-21 (+ 197 d) | 2.13G (+ 743.42M) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 1.84G (- 38.49G) | 49,966 (- 1,110,517) |
2019-03-07 (+ 43 d) | 1.40G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 40.33G (+ 0B) | 1,160,483 (+ 0) |
2019-01-23 (+ 44 d) | 1.40G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 40.33G (+ 0B) | 1,160,483 (+ 0) |
2018-12-09 (+ 29 d) | 1.40G (+ 0B) | 12 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 40.33G (+ 36.17G) | 1,160,483 (+ 1,045,345) |
2018-11-09 (+ 27 d) | 1.40G (+ 1.18G) | 12 (+ 1) | 57 (+ 0) | 7,694,803 (+ 0) | 4.16G (+ 4.16G) | 115,138 (+ 115,138) |
2018-10-13 (+ 29 d) | 232.25M (+ 0B) | 11 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 232.25M (+ 0B) | 11 (+ 0) | 57 (+ 0) | 7,694,803 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 232.25M (+ 0B) | 11 (+ 0) | 57 (+ 0) | 7,694,803 (+ 1,082,437) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 | 232.25M | 11 | 57 | 6,612,366 | 0B | 0 |
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