Name | n3_chennan_house_ikman_lk |
---|---|
Data | 91.56M (+ 0B) |
Tables | 5 (+ 0) |
Columns | 21 (+ 0) |
Table Rows | 147,861 (+ 0) |
Media | 190.92M (+ 0B) |
Files | 59,184 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
This is a property database with 20,175 records with title, price, location, description and per night price in each. It also contians 10,609 details of these houses. There are 59,184 house images in this data. The whole houses data set has 5 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
detail | 10,609 | key |
100%
|
value |
100%
|
||
image | 59,184 | image_url |
100%
|
property_id |
100%
|
||
property | 20,175 | title |
100%
|
price |
100%
|
||
location |
81.38%
|
||
per_night_price |
77.48%
|
||
description |
81.38%
|
||
property_x_detail | 57,893 | property_id |
100%
|
detail_id |
100%
|
Size (Bytes) | Files |
---|---|
190.92M | 59,184 |
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2023-01-01 (+ 95 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2022-09-27 (+ 271 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2021-12-30 (+ 115 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2021-09-05 (+ 150 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2021-04-08 (+ 68 d) | 91.56M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2021-01-29 (+ 120 d) | 91.56M (+ 33.72M) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2020-10-01 (+ 38 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2020-08-23 (+ 141 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2020-04-04 (+ 196 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2019-09-21 (+ 197 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2019-03-07 (+ 43 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2019-01-23 (+ 44 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 0B) | 59,184 (+ 0) |
2018-12-09 (+ 29 d) | 57.84M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 190.92M (+ 52.06M) | 59,184 (+ 16,192) |
2018-11-09 (+ 27 d) | 57.84M (+ 33.55M) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 138.86M (+ 138.86M) | 42,992 (+ 42,992) |
2018-10-13 (+ 29 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 (+ 31 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-06-10 (+ 31 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-05-10 (+ 28 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-04-11 (+ 38 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-03-03 (+ 35 d) | 24.30M (+ 0B) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-01-27 (+ 29 d) | 24.30M (+ 17.89M) | 5 (+ 0) | 21 (+ 0) | 147,861 (+ 126,294) | 0B (+ 0B) | 0 (+ 0) |
2017-12-29 | 6.41M | 5 | 21 | 21,567 | 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.