[OC] Über 50 Jahre Einwanderung nach Kanada

R code to reproduce

library(cansim)
library(tidyverse)
library(ggplot2)
library(janitor)
library(lubridate)
library(glue)

df_raw <-
cansim::get_cansim(’17-10-0008′) |>
janitor::clean_names()

pop_raw <-
cansim::get_cansim(’17-10-0009′) |>
janitor::clean_names()

dat <-
df_raw |>
filter(geo == ‘Canada’ &
(components_of_population_growth == ‘Net non-permanent residents’ |
components_of_population_growth == ‘Immigrants’)
) |>
separate(col = ref_date, sep = ‘/’, into = c(‘year_start’, ‘year_end’), convert = TRUE, remove = FALSE) |>
select(ref_date, year_start, components_of_population_growth, value) |>
summarise(value = sum(value), .by = c(‘ref_date’ , ‘year_start’)) |>
mutate(components_of_population_growth = ‘Immigrants + Net non-permanent’)

pop <-
pop_raw |>
filter(geo == ‘Canada’
) |>
separate(col = ref_date, sep = ‘-‘, into = c(‘year’, ‘mon’), convert = TRUE) |>
filter(mon == ‘4’) |>
select(year, value) |>
rename(pop := value)

p_dat <-
inner_join(
pop,
dat,
by = join_by(year == year_start)
) |>
mutate(f = value/pop, p = f*100)

##################
# Results from Wikipedia
elections <-
read.csv(text = c(‘year, gov, leader
2021, Liberal, J. Trudeau
2019, Liberal, J. Trudeau
2015, Liberal, J. Trudeau
2011, Conservative, Harper
2008, Conservative, Harper
2006, Conservative, Harper
2004, Liberal, Martin
2000, Liberal, Chrétien
1997, Liberal, Chrétien
1993, Liberal, Chrétien
1988, Conservative, Mulroney
1984, Conservative, Mulroney
1980, Liberal, P. Trudeau
1979, Conservative, Clark
1974, Liberal, P. Trudeau
1972, Liberal, P. Trudeau
1968, Liberal, P. Trudeau’)) |>
tibble() |>
mutate_if(is.character, trimws)

govs <-
p_dat |>
distinct(year) |>
full_join(elections, by = ‘year’) |>
arrange(year) |>
fill(gov , .direction = “down”) |>
fill(leader , .direction = “down”)

color_mapping = c(‘Liberal’ = ‘darkred’, ‘Conservative’ = ‘darkblue’)

leaders <-
p_dat |>
left_join(govs, by = ‘year’) |>
summarise(p = max(p) + 0.3,
year = mean(range(year)), .by = c(leader, gov)
)

library(scales)

yrs_rng <- paste0(range(p_dat$year), collapse = ‘-‘)

p_dat |>
left_join(govs, by = ‘year’) |>
ggplot(aes(x = year, y = p)) +
geom_line(aes(group = components_of_population_growth, fill = gov, color = gov ), size = 1.1, color = ‘grey’, linetype = ‘dashed’ ) +
geom_point(aes(color = gov, size = 1.1)) +
geom_text(data = leaders, mapping = aes(label = leader, color = gov), size = 6) +
scale_color_manual(values = color_mapping ) +
scale_fill_manual(values = color_mapping ) +
scale_y_continuous(labels = function(x) paste0(x, “%”)) +
#facet_grid(rows = ~components_of_population_growth) +
guides(color = ‘none’, size = ‘none’, fill = ‘none’) +
labs(title = glue(’50+ years of Immigration in Canada {yrs_rng}’) , subtitle = ‘Immigrants + Net non-permanent residents, as a percentage of the population.’, x = ”, y = ”, caption = ‘CanSim : 17-10-0008 & 17-10-0009’) +
theme_minimal() +
theme(
plot.title = element_text(hjust = 0.5, size = 20),
plot.subtitle = element_text(hjust = 0.5, size = 15, color = ‘grey’),
axis.text = element_text(size = 18)
)

Excellent! Data suggests that immigration is a significant benefit to developed nations, so this is good news for Canada.

looks like an invasion to me

You get what you vote for

For further reading, check out the “Century Initiative”. Some scary stuff if our infrastructure remains on the back burner, which you can see shades of in smaller towns (in Ontario at least) that are expanding quickly.

Bring in the people, but schools, roads, parks, rec centres, telecomms, etc.. are lagging too far behind to support the amount of people, which is only causing tension between those who have lived in these towns for years, against those moving in from cities.

Who knew bringing in people in unchecked and in massive quantity would create havoc in all aspect of Canadian lives. House price sky rocking, people can’t afford rent, food… national debt doubled in a couple of years….

At least the current government is finally hearing it from the people. Good bye Trudeau.