Last updated on January 13, 2020
All 6 datasets contain the same information, but represent data differently: two and three-letter codes (ISO2, ISO3), and full country names from no particular standard, as well as distance matrix and tidy formats.
In distance matrices (files with matrix
in the filename), the first column represents a passport (=from), each remaining column represents a destination (=to).
Files in tidy format (with tidy
in filename) have three columns: passport (from), destination (to), and the code. Note that unlike in the matrix, these files do not have instances were passport = destination
, and as a result there are no -1
code values.
Code | Explanation |
---|---|
3 | visa-free travel |
2 | visa on arrival |
1 | eTA (electronic travel authority) required |
0 | visa required |
-1 | where passport=destination |
You should be able to run the Jupyter notebook to update datasets whenever you want. The notebook uses BeautifulSoup to fetch PassportIndex source HTML and extract the <script>
tag with relevant visa data, then transforms the data using Js2Py
for Python processing, and then generates 6 datasets.
Since "Passport Index is a free tool, built with publicly available information and with content contributed by fans and government agencies around the world", feel free to use the dataset under the MIT license.
Source: https://www.passportindex.org