Data Source - Statistics Canada
We found these data sets on Stat Canada, a great data tool that enabled us to refine our focus on particular labor force characteristics and age brackets. Opting for the age range of 25 to 54 years, we selected data encompassing all provinces, including Canada as a whole.
Click this link to visit Stat Canada.
Please note: We included the codes that we utilized in R to create the charts, graphs, and visuals.
Unemployment Rate of individuals BORN in Canada
This chart below illustrates the cumulative average unemployment rates by PROVINCE from 2015 to 2023 among Canadian-born citizens in descending order.
As we can see Newfoundland and Labrador is the outlier with an unemployment rate of 11.01, compared to Quebec’s low unemployment rate of 4.48.
immi_data %>% group_by(Province) %>% summarize(Avg_Unemploy_Rate=mean(`Born.in.Canada...Unemp..Rate`)) %>% arrange(desc(Avg_Unemploy_Rate))## # A tibble: 11 × 2
## Province Avg_Unemploy_Rate
## <chr> <dbl>
## 1 Newfoundland and Labrador 11.0
## 2 Prince Edward Island 7.79
## 3 New Brunswick 7.02
## 4 Nova Scotia 6.58
## 5 Alberta 5.8
## 6 Canada 5.08
## 7 Saskatchewan 4.98
## 8 Ontario 4.89
## 9 Manitoba 4.52
## 10 British Columbia 4.51
## 11 Quebec 4.48This chart below illustrates the cumulative average unemployment rates by YEAR from 2015 to 2023 among Canadian-born citizens throughout all of Canada.
Throughout the year of 2020, the unemployment rate rapidly rose to 7.77. As we know, Covid occurred throughout 2020 and 2021, but the unemployment rate made its way down to 4.53 last year.
## # A tibble: 9 × 2
## Year Avg_Unemploy_Rate
## <int> <dbl>
## 1 2015 6.49
## 2 2016 6.79
## 3 2017 6.4
## 4 2018 5.95
## 5 2019 5.51
## 6 2020 7.77
## 7 2021 6.45
## 8 2022 4.65
## 9 2023 4.53The below graph combines the data from the preceding charts, presenting it graphically on a provincial basis for enhanced visualization.
immi_data %>% ggplot(aes(Year, `Born.in.Canada...Unemp..Rate`, color=Province))+
geom_line(linewidth=1, show.legend = FALSE)+facet_wrap(~Province)+
labs(title = "Born in Canada",x="Year",y="Unemployment Rate")
Unemployment Rate of individuals LANDED IMMIGRANTS in Canada
This chart below illustrates the cumulative average unemployment rates by PROVINCE from 2015 to 2023 among landed immigrants in Canada in descending order.
Prince Edward Island recorded the highest unemployment rate at 8.38, while the lowest rate recorded was Manitoba at 5.3.
immi_data %>% group_by(Province) %>% summarize(Avg_Unemploy_Rate=mean(`Landed.Immigrants...Unemp..Rate`, na.rm = TRUE)) %>% arrange(desc(Avg_Unemploy_Rate))## # A tibble: 11 × 2
## Province Avg_Unemploy_Rate
## <chr> <dbl>
## 1 Prince Edward Island 8.38
## 2 Newfoundland and Labrador 8.25
## 3 Quebec 8
## 4 Alberta 7.43
## 5 Nova Scotia 7.03
## 6 Canada 6.62
## 7 New Brunswick 6.57
## 8 Ontario 6.44
## 9 Saskatchewan 5.9
## 10 British Columbia 5.5
## 11 Manitoba 5.33This chart below illustrates the cumulative average unemployment rates by YEAR from 2015 to 2023 among landed immigrants throughout all of Canada.
Throughout the year of 2020, the unemployment rate rapidly rose to 9.24. As we know, Covid occurred throughout 2020 and 2021, but the unemployment rate made its way down to 5.9 last year.
immi_data %>% group_by(Year) %>% summarize(Avg_Unemploy_Rate=mean(`Landed.Immigrants...Unemp..Rate`, na.rm = TRUE))## # A tibble: 9 × 2
## Year Avg_Unemploy_Rate
## <int> <dbl>
## 1 2015 7.43
## 2 2016 6.74
## 3 2017 6.92
## 4 2018 6.23
## 5 2019 5.63
## 6 2020 9.24
## 7 2021 7.84
## 8 2022 5.06
## 9 2023 5.9The below graph combines the data from the preceding charts, presenting it graphically on a provincial basis for enhanced visualization.
immi_data %>% ggplot(aes(Year, `Landed.Immigrants...Unemp..Rate`, color=Province))+
geom_line(linewidth=1, show.legend = FALSE)+facet_wrap(~Province)+
labs(title = "Landed Immigrants",x="Year",y="Unemployment Rate")
Conclusion
In conclusion, through the utilization of data obtained from Stat Canada, we have meticulously crafted several charts to elucidate key insights regarding labor force characteristics within the age range of 25 to 54 years across all provinces, as well as Canada as a whole. This focused approach has allowed us to refine our analysis and provide a comprehensive understanding of the dynamics at play within this demographic segment. By delving into specific age brackets and pertinent labor force attributes, our charts serve as valuable tools for informing strategic decisions and policy initiatives aimed at addressing workforce needs and fostering economic growth. The data-driven nature of our findings underscores the importance of utilizing robust sources such as Stat Canada to inform research endeavors and contribute to evidence-based decision-making processes.
Insights
Impact of COVID-19: During the pandemic, lower consumer spending resulted in lower profits for businesses, which forced them to minimize expenses by hiring fewer people and working fewer hours. Lock downs imposed by the government as a result of COVID-19 forced numerous firms to temporarily close, which resulted in severe unemployment. As you can see from the charts above, 2020 recorded the highest unemployment rates throughout all provinces across Canada. As we reached 2022, unemployment rates began to decrease as the economy started to recover from COVID-19. Business started to operate again, the government released the lock down policy, and life returned back to normal.
About Us
Leena Moussa - I’m a junior, graduating in May, majoring in Finance and Data Analytics. I am also a student athlete at Mercy University on the Women’s Lacrosse team. I’m grateful to have gotten the opportunity to work on this project for a real company because it allows us to gain experience and give us a glimpse of the work force lifestyle. With majority of us graduating soon, working with Saad was beneficial to gain a better understanding of how start up companies function. Thank you Saad and team for trusting us with this project!
Daniel Rodriguez - I’m a senior, graduating in May, majoring in Data Analytics. Also a student athlete at Mercy University on the Men’s Soccer Team. This was a really good and helpful opportunity for us to work with Immican and Saad, being able to do this project, help them to develop something new to their company and website.
Franco Acri - I’m a junior, graduating in December, majoring in Data Analytics and Marketing.I’m a student athlete at Mercy University on the Men’s Soccer Team. I really appreciate the opportunity to work for Immican because I was able to work on an actual real-life project, a project that matters and a project that really interests me. I believe I gained a lot of real work experience and I will always be thankful for that. Thank you for trusting us with such a special and important project.
