Name | n3_chennan_veterinarian_yellowpages_com |
---|---|
Data | 98.89M (+ 0B) |
Tables | 4 (+ 0) |
Columns | 37 (+ 0) |
Table Rows | 331,882 (+ 0) |
Media | 0B (+ 0B) |
Files | 0 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
This is a veterinarians database with 63,563 records throughout 2,537 cities of 51 states in America. Each veterinarian is comprised of title, street address, phone number, address locality, address region and postal code. The whole United States veterinarians data set has 4 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
city | 2,537 | title |
100%
|
state_id |
100%
|
||
state |
100%
|
||
city_x_veterinarian | 265,731 | city_id |
100%
|
veterinarian_id |
100%
|
||
state | 51 | title |
100%
|
veterinarian | 63,563 | title |
100%
|
street_address |
93.89%
|
||
phone |
99.98%
|
||
general_info |
24.93%
|
||
services_or_products |
18.88%
|
||
amenities |
8.62%
|
||
address_locality |
95.42%
|
||
address_region |
95.42%
|
||
postal_code |
95.42%
|
||
latitude |
93.11%
|
||
longitude |
93.11%
|
||
brands |
24.79%
|
||
payment |
48.24%
|
||
location |
14.42%
|
||
neighborhoods |
32.59%
|
||
weblinks |
62.89%
|
||
categories |
95.87%
|
||
open_hours |
95.21%
|
No media sets.
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2023-01-01 (+ 95 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2022-09-27 (+ 271 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-12-30 (+ 115 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-09-05 (+ 150 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-04-08 (+ 68 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-01-29 (+ 120 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-10-01 (+ 38 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-08-23 (+ 141 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-04-04 (+ 196 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-09-21 (+ 197 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-03-07 (+ 43 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-01-23 (+ 44 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-12-09 (+ 29 d) | 98.89M (+ 0B) | 4 (+ 0) | 37 (+ 0) | 331,882 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-11-09 (+ 27 d) | 98.89M (- 55.47M) | 4 (- 2) | 37 (+ 4) | 331,882 (- 197,556) | 0B (+ 0B) | 0 (+ 0) |
2018-10-13 (+ 29 d) | 154.36M (+ 0B) | 6 (+ 0) | 33 (+ 0) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 154.36M (+ 0B) | 6 (+ 0) | 33 (+ 0) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 154.36M (+ 0B) | 6 (+ 0) | 33 (+ 0) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 (+ 31 d) | 154.36M (+ 0B) | 6 (+ 0) | 33 (+ 0) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-06-10 (+ 31 d) | 154.36M (+ 0B) | 6 (+ 0) | 33 (+ 0) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-05-10 (+ 28 d) | 154.36M (- 3M) | 6 (+ 0) | 33 (- 11) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-04-11 (+ 38 d) | 157.36M (- 43.33M) | 6 (+ 2) | 44 (+ 19) | 529,438 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-03-03 | 200.69M | 4 | 25 | 529,438 | 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.