Comparison over time by Region
Source:vignettes/Comparison over_time_by_Region.Rmd
Comparison over_time_by_Region.RmdPrepare Data
## Loading the stat tables
data <- dplyr::left_join( x= unhcrdatapackage::end_year_population_totals_long,
y= unhcrdatapackage::reference,
by = c("CountryAsylumCode" = "iso_3")) %>%
filter(#Population.type == "REF" &
!(is.na(UNHCRBureau))) %>%
group_by(Year, UNHCRBureau ) %>%
summarise(Value2 = sum(Value) )
#> `summarise()` has grouped output by 'Year'. You can override using the `.groups` argument.
lastyear <- max(unhcrdatapackage::end_year_population_totals_long$Year)generate plot
#Make plot
ggplot(data, aes(x = Year, y = Value2,
colour = UNHCRBureau)) + # Adding reference to color
geom_line(size = 1) + # Here we mention that it will be a line chart
geom_hline(yintercept = 0, size = 1, colour = "#333333") +
scale_y_continuous( label = scales::label_number_si()) + ## Format axis number
xlim(c(1960, lastyear + 8)) +
#scale_colour_viridis_d() + ## Add color for each lines based on color-blind friendly palette
#scale_fill_manual(name = 'UNHCRBureau', values = c("#b2df8a", "#fb9a99", "#1f78b4", "#33a02c", "#a6cee3")) +
# "WestAfrica"
scale_fill_manual(name = 'UNHCRBureau', values = c( "Americas" = "#a6cee3",
"Asia" = "#1f78b4",
"EastAfrica" = "#b2df8a",
"Europe" = "#33a02c",
"MENA" = "#fb9a99",
"SouthAfrica" = "#e31a1c",
"WestAfrica"= "#fdbf6f")) +
geom_label(aes(x = lastyear + .5 ,
y = as.numeric(data[data$UNHCRBureau == "Americas" & data$Year == lastyear , c("Value2")]),
label = "Americas"),
hjust = 0,
vjust = 0.5,
colour = "#a6cee3",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear +.5,
y = as.numeric(data[data$UNHCRBureau == "Asia" & data$Year == lastyear , c("Value2")]),
label = "Asia"),
hjust = 0,
vjust = 0.5,
colour = "#1f78b4",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear + .5,
y = as.numeric(data[data$UNHCRBureau == "EastAfrica" & data$Year == lastyear , c("Value2")]),
label = "Eastern Africa"),
hjust = 0,
vjust = 0.5,
colour = "#b2df8a",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear + .5,
y = as.numeric(data[data$UNHCRBureau == "Europe" & data$Year == lastyear , c("Value2")]),
label = "Europe"),
hjust = 0,
vjust = 0.5,
colour = "#33a02c",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear + .5,
y = as.numeric(data[data$UNHCRBureau == "MENA" & data$Year == lastyear , c("Value2")]),
label = "Middle East / North Africa"),
hjust = 0,
vjust = 0.5,
colour = "#fb9a99",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear + .5,
y = as.numeric(data[data$UNHCRBureau == "SouthAfrica" & data$Year == lastyear , c("Value2")]),
label = "Southern Africa"),
hjust = 0,
vjust = 0.5,
colour = "#e31a1c",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
geom_label(aes(x = lastyear + .5,
y = as.numeric(data[data$UNHCRBureau == "WestAfrica" & data$Year == lastyear , c("Value2")]),
label = "Western Africa"),
hjust = 0,
vjust = 0.5,
colour = "#fdbf6f",
fill = "white",
label.size = NA,
family = "Lato",
size = 6) +
unhcRstyle::unhcr_theme() + ## Insert UNHCR Style
## and the chart labels
labs(title = "Refugees Population are not equally spread",
subtitle = "World wide refugee population 1951-2017",
x = "",
y = "",
caption = "UNHCR https://www.unhcr.org/refugee-statistics/")