| Name | n3zm_ShiPu_28ms_cn |
|---|---|
| Data | 20.03M (+ 0B) |
| Tables | 4 (+ 0) |
| Columns | 35 (+ 0) |
| Table Rows | 39,642 (+ 0) |
| Media | 0B (+ 0B) |
| Files | 0 (+ 0) |
| Last Commit | 2023-06-19 19:57:45 (+ 169 d) |
这是一个中国食谱大全，共有11个主分类下的19,553个食谱记录。这些主分类分别是特色菜谱，植物菜单，动物菜单，营养食疗，中华菜谱，外国菜谱，功能调理，人群膳食，脏腑调理，疾病调理和特色小吃。每个食谱中包含有描述，做法，网站，时间，来源，工艺，人数，口味，准备时间，所需食材等。该中国食谱数据库共有4个表。
This is a Chinese recipes database having 19,553 records by 11 categories. These categories are special recipes, plant menu, animal menu, nutritional diet, Chinese recipes, foreign recipes, functional conditioning, crowd diet, viscera conditioning, disease conditioning and snacks. Each record consists of description, practice, website, time, source, workmanship, number of people, taste, prepare time, ingredients needed, etc. The whole Chinese recipes database has 4 tables in total.
| Tables | Rows | Columns | Non-empty |
|---|---|---|---|
| category_1 | 11 | title |
100%
|
| category_2 | 525 | title |
100%
|
| category_1_id |
100%
|
||
| category_1 |
100%
|
||
| category_2_x_shipu | 19,553 | category_2_id |
100%
|
| shipu_id |
100%
|
||
| shipu | 19,553 | title |
100%
|
| miaoshu |
79.2%
|
||
| zuofa |
8.56%
|
||
| wangzhan |
91.01%
|
||
| shijian |
100%
|
||
| laiyuan |
99.99%
|
||
| gongyi |
1.77%
|
||
| renshu |
1.66%
|
||
| kouwei |
1.68%
|
||
| zhunbeishijian |
1.66%
|
||
| pengrenshijian |
0%
|
||
| suoxushicai |
34.09%
|
||
| fuliao |
12.14%
|
||
| jiqiao |
1.1%
|
No media sets.
| Time | Data | Tables | Columns | Rows | Media | Files |
|---|---|---|---|---|---|---|
| 2023-06-19 (+ 169 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2023-01-01 (+ 95 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2022-09-27 (+ 271 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-12-30 (+ 115 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-09-05 (+ 150 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-04-08 (+ 68 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2021-01-29 (+ 120 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-10-01 (+ 38 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-08-23 (+ 141 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2020-04-04 (+ 196 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-09-21 (+ 197 d) | 20.03M (+ 0B) | 4 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
| 2019-03-07 (+ 43 d) | 20.03M (- 2.47M) | 4 (- 1) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 0 (- 9,035) |
| 2019-01-23 (+ 44 d) | 22.50M (+ 0B) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-12-09 (+ 29 d) | 22.50M (+ 0B) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-11-09 (+ 27 d) | 22.50M (+ 10.27M) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-10-13 (+ 30 d) | 12.23M (+ 0B) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-09-13 (+ 34 d) | 12.23M (+ 0B) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-08-09 (+ 27 d) | 12.23M (+ 0B) | 5 (+ 0) | 35 (+ 0) | 39,642 (+ 0) | 0B (+ 0B) | 9,035 (+ 0) |
| 2018-07-12 | 12.23M | 5 | 35 | 39,642 | 0B | 9,035 |
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.
