Name | n3_chennan_zipcode_zip_codes_com |
---|---|
Data | 23.89M (+ 0B) |
Tables | 3 (+ 0) |
Columns | 26 (+ 0) |
Table Rows | 122,099 (+ 0) |
Media | 0B (+ 0B) |
Files | 0 (+ 0) |
Last Commit | 2023-06-19 18:36:38 (+ 169 d) |
In the zip codes data, there are 60,376 records with title, postal code, area name, provice, time zone, latitude & longitude, elevation, population and dwelling, etc. in each from 1,254 cities of Canada. The whole Canada zip codes data set consists of 3 tables.
Tables | Rows | Columns | Non-empty |
---|---|---|---|
city | 1,254 | title |
100%
|
city_x_zipcode | 60,469 | city_id |
100%
|
zipcode_id |
100%
|
||
zipcode | 60,376 | title |
100%
|
postal_code |
100%
|
||
city |
0%
|
||
area_name |
100%
|
||
provice |
100%
|
||
area_code |
0%
|
||
time_zone |
100%
|
||
day_light_saving |
100%
|
||
latitude |
100%
|
||
longitude |
100%
|
||
elevation |
100%
|
||
population |
100%
|
||
dwelling |
100%
|
No media sets.
Time | Data | Tables | Columns | Rows | Media | Files |
---|---|---|---|---|---|---|
2023-06-19 (+ 169 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2023-01-01 (+ 95 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2022-09-27 (+ 271 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-12-30 (+ 115 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-09-05 (+ 150 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-04-08 (+ 68 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2021-01-29 (+ 120 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-10-01 (+ 38 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-08-23 (+ 141 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2020-04-04 (+ 196 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-09-21 (+ 197 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-03-07 (+ 43 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2019-01-23 (+ 44 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-12-09 (+ 29 d) | 23.89M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-11-09 (+ 27 d) | 23.89M (+ 5.08M) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-10-13 (+ 29 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-09-13 (+ 34 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-08-09 (+ 27 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-07-12 (+ 31 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-06-10 (+ 31 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-05-10 (+ 28 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-04-11 (+ 38 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-03-03 (+ 35 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2018-01-27 (+ 29 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2017-12-29 (+ 20 d) | 18.81M (+ 0B) | 3 (+ 0) | 26 (+ 0) | 122,099 (+ 0) | 0B (+ 0B) | 0 (+ 0) |
2017-12-08 | 18.81M | 3 | 26 | 122,099 | 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.