Using ChatGPT to analyze open data immigration tables
2026/11/05 Leave a comment
For my quarterly updates, I have been working on how best to compile and analyze the various tables in a more time-efficient manner. Next quarter report will largely use ChatGPT for data tables rather than my previous manual approach.
As an example, the prompt I use for country of citizenship analysis is the following:
Using the following excel file INSERT LINK, prepare a table of quarterly statistics, header row to be quarter, header column to be country, organized from highest to lowest in 2018. Top row should be Canada total. Create separate data table for the top 25 countries, 2018 basis. Create subsequent tables that shows year over year percentage change and one that shows two-year changes. Prepare additional table showing annual comparisons in numbers, and same year-over-year and two year comparison.
Prepare a comparative annual year-to-date table as well.
Ensure thousand separators for numbers with percentages to one decimal place.
Freeze header columns and rows (Country and Canada).
Create one separate table that provides a regional summary, where the six rows are Canada, Asia, Africa, Americas, Europe, Oceania, with the top rows being numbers and below rows by percentage of Canadian total. No separate individual region views.
And here is the result:
One of the better uses I have found for AI. Saves me from learning python (and yes, ChatGPT also creates python scripts).
