Canada Immigration Dashboard

Canada’s Immigration Journey: Insights from 2015 to 2023 using Tableau Public

9 min readOct 17, 2023

In search of some real-world data that gets updated regularly, I stumbled upon the IRCC Canadian Immigration Data. As an international student in Canada and a data nerd myself, I found the data to be intriguing to explore and find hidden insights. Also, this could be useful for many individuals researching Canada Immigration Programs and Provinces.

Getting into this, I had several questions after a brief observation of the data and initial EDA that we would be looking into in our analysis section. With the help of Tableau Public Serve, I was able to host my visualizations, using Flask as the backend and HTML/CSS/JS as the frontend, I was able to get the dashboard and create a web application dashboard for everybody to use. I will go into more detail in the subsequent sections.

Lastly, the dashboard is of a fixed size of 1920*1080 which is the standard resolution for a monitor. So, for this reason, the dashboard is not responsive and will not work smoothly on smartphones as it does on Laptops, Monitors, or Tablets.

About the Dataset

The dataset was taken from Permanent Residents — Monthly IRCC Update. It has data on all the immigrants coming to Canada under different categories from 2015 to August 2023.

As indicated on the above site, the data has been intentionally altered to ensure the anonymity of individuals when combining and contrasting datasets with other publicly available statistics.

Any values falling between 0 and 5 have been represented as “ — ” on the original dataset, but for our analysis, we have replaced “ — ” with a value of 2. Because we don’t want to lose all the valuable data and we want to represent the data as closely as possible to the total. While all other figures have been rounded to the nearest multiple of 5. As a consequence, the total sum of the data may not match the indicated totals

We have combined 3 datasets to get the dashboard and 1 dataset to get the running bar chart for the countries.

ETL (Extract, Transform, Load)

For the ETL process, we initially extracted the Immigration Category, Gender, Age, and Country of Citizenship as an Excel file.

Since the dataset was not too large, we decided to use Excel for basic data transformation.

The “Date” field was common to all the datasets, we will be using it to combine all the datasets to get a bigger picture of Canada as a whole. We will also be dividing our dataset into different sheets according to the Province to create a dashboard related to each province.

Since the data is frequently updated and for minimum data transformation and manipulation, we have not deleted any columns from the original dataset, some columns might be duplicates. On top of that, we will be using data until Q2 of 2023 but as of writing this article, it has data for July and August also but not for September i.e., all the data for Q3 is not provided to us. I am planning to update the dashboard every quarter.

For the rows, we have taken the month and year values (removed the hirechary of quarterly and yearly division), not the quarterly total and yearly total as most of the visualization tools (Tableau which I am using) have this feature built when we indicate the column to be a type of Date. Also, for the values indicated with “ — ”, we have replaced them with a value of 2, as mentioned above.

Since, we have 13 provinces in Canada, doing so again and again 13 times was trying. But after doing all this, we are now able to load the data to the tableau public and do some visualization, and find the hidden insights.

For the running bar chart, we have used to Country dataset of the top 30 immigrant countries. All the other transformation process is similar but in the end, we need to find the cumulative sum of all the countries which is a requirement to make a running bar chart.

Visualization

Visualization of the data was done in Tableau Public which helps us to store our visualizations in Tableau public server. This feature was crucial for us to show all 15 dashboards in one web application.

Let’s take one visualization out of 13 provinces and discuss the visualizations, as all other dashboards are similar to each other only slightly differing in the immigration category.

We will go through the Ontario Immigration Dashboard

We have 4 important sections for the dashboard.

The center visualization contains all the information about the immigration category. We have used a feature called page-swapping to make the dashboard more clean and informative. By using the selector, dive deeper, we can dive deeper into each category and see the trends and patterns.

The top left visualization gives us the total number of immigrants for each year and the total number of immigrants to Ontario from 2015 to 2023 June.

The bottom left visualization gives us information about the gender ratio of the immigrants using a Butterfly chart.

At the bottom, we have 5 different cards showing us the age group of the individuals who have immigrated to Canada.

And on the left side, we have a filter for each year. This will help us to analyze our data in more detail and find the nitty-gritty hidden information from our data.

For the main Canada Dashboard, we combine all the province sheets with the help of the Date column. This helped us to have a good overview of the overall Canadian province immigration data.

Finally, to make a running bar chart, we used a Python library called bar_chart_race. After passing the data in the correct format, it will produce a running bar chart and we can download it in an MP4 format.

Running Bar Chart

Analysis

I had many questions getting into the analysis but out of them, I have discussed 5 here. You are free to dive deeper and answer other interesting questions.

Let’s get started:

Which age group is more likely to move to Canada?

According to our analysis, the age group between 15 to 44 is more likely to move to Canada. Out of 2,808,096 immigrants, 1,921,805 individuals have moved to Canada from 2015 to 2023 Q2. This accounts for 68% of total immigrants.
The reason might be this age group people are more actively looking for better opportunities and better lifestyles. They are young, energetic, and willing to take more risks as compared to the individuals of 44+ age. So, they move to Canada leaving everything behind in their home country to start fresh and start from the bottom.

How has the immigrant's pattern changed, according to the country of immigrants in the last 8 years in Canada?

At the start of 2015, January, Canada invited around 10,260 people out of which the Philippines had the highest number of immigrants at 2535 followed by India (1560) and Iran with 1060.
Most of the people moving to Canada seem to be from developing countries like the Philippines, India, China, Pakistan, Mexico, Jamaica, and Nigeria or from war-affected countries like Iran, Syria, and Afghanistan. However, people from developed nations like the USA, the UK, France, and Korea are also moving into the country.

After 8 years, the trend is going on the same track with slight adjustments in the leaderboard i.e., now India is at the top of total immigrants who immigrated to Canada with 659,700 individuals which is 2.5X, the second most immigrated country the Philippines and China. Iran has been knocked out to the 9th position.
People from Syria, Nigeria, and Afghanistan have a significantly high number of people immigrating mostly because of the war reason and inhospitable environment in their homeland.

Which year did the highest number of immigrants come to Canada and what were the top 3 province choices for the immigrants?

As you can see, in 2022, Canada hosted about half a million people which is the highest of all other years. However, the data we have taken is until 2023 Q2 which means at the end of this year, 2023, the graph might look a bit different.
The trend seems to be increasing year after year with a little deviation in 2020 mostly probably due to Covid-19 and in 2017 with about 10,000 fewer immigrants coming to Canada the year prior to that.

Answering our second question, in the year 2022, about 42% of immigrants settled in Ontario, followed by Quebec and British Columbia.

The above result might not be surprising to people with some knowledge about Canada, as about 90% of Canadians live within 100 miles of the US border and most of the northern territories have harsh and extremely inhabitable weather and terrains. This can be summarized by the below population distribution of Canada.

How much difference is there in the gender ratio among the immigrants? Does it remain consistent?

The result of this analysis is quite interesting and eye-opening. Initially, when starting the analysis, I would have guessed either the male or female ratio to be higher but the ratio remained quite consistent over the course of 8 years with only a 0.86% difference between male and female immigrants.
This might be because of some Canadian Government policies to maintain the gender ratio or most of the immigrants who move to Canada are usually married or are planning to get married and when they move to Canada, they move together which has maintained the gender ratio of immigrants.

Which immigration category invites more immigrants?

There are three categories for immigrants to move to Canada. They are; Economic, Sponsored, and Resettled Refugees and Protected Persons.
Out of 3, the Economic category has the most flexibility for immigrants to move to Canada. It has different kinds of provincial programs, business programs, skilled work sections, PNP, and Canadian Experience (for students studying in Canada) which makes the Economy Category a more viable option for people wanting to move to Canada compared to other categories.

Conclusion

The project was fun as I explored something that I can relate to and that can be useful to myself and others. While it was fun, it was quite challenging at the same time. I had to learn a lot about Tableau, dashboard embedding, the deployment of a web app, ETL, the principle of visualization, and many more. This project has given me some much-needed encouragement to push out projects that can be useful to the masses.

Finally, as the dataset keeps on updating, I will try to update the dashboard quarterly and try to provide the latest visualization of the data.

PS: Please find the resources like video, articles, documentation, tableau workbooks, and code for the project in my GitHub repository.

Github: https://github.com/itsmeSamrat/Canada-Immigration-Dashboard