Prepare Data
The map is presented with the Bertin 1953 projection
thisbureau <- "Americas"
lastyear <- max(unhcrdatapackage::end_year_population_totals_long$Year)
end_year_population_totals_long.asy <- dplyr::left_join( x= unhcrdatapackage::end_year_population_totals_long,
y= unhcrdatapackage::reference,
by = c("CountryAsylumCode" = "iso_3"))
## Now get the rank from high to low for all countries per year and population type
rank_data <- dplyr::left_join( x= unhcrdatapackage::end_year_population_totals_long,
y= unhcrdatapackage::reference,
by = c("CountryAsylumCode" = "iso_3")) %>%
group_by(Year, CountryAsylumCode, CountryAsylumName ) %>%
summarise(Value = sum(Value) )
#> `summarise()` has grouped output by 'Year', 'CountryAsylumCode'. You can override using the `.groups` argument.
rank_data <- end_year_population_totals_long.asy %>%
group_by(REGION_UN, Year, Population.type, CountryAsylumName, CountryAsylumCode) %>%
summarise(Value2 = sum(Value) )
#> `summarise()` has grouped output by 'REGION_UN', 'Year', 'Population.type', 'CountryAsylumName'. You can override using the `.groups` argument.
#str(as.data.frame(rank_data))
rank_data <- as.data.frame(rank_data)
rank_data.ref <- rank_data %>%
group_by(REGION_UN, Year, Population.type) %>%
## Tried first rank but did not provided ranks as integer...
# mutate(ordering = rank(-Value), ties.method = "min") %>%
mutate(ordering = rank(-Value2)) %>%
ungroup()
## check our value for rank -- Note that there are different tie method
#levels(as.factor(rank_data.ref$ordering))
## need to fix manually issue when ex-aequo rank rank = 8.5
## In 1962
rank_data.ref$ordering[rank_data.ref$ordering == 10 &
rank_data.ref$Year == "1962" &
rank_data.ref$Population.type %in% c("REF")] <- 11
rank_data.ref$ordering[rank_data.ref$ordering == 8.5 &
rank_data.ref$Year == "1962" &
rank_data.ref$CountryAsylumName == "Burundi" &
rank_data.ref$Population.type %in% c("REF")] <- 9
rank_data.ref$ordering[rank_data.ref$ordering == 8.5 &
rank_data.ref$Year == "1962" &
rank_data.ref$CountryAsylumName == "Austria" &
rank_data.ref$Population.type %in% c("REF")] <- 10
## In 1978
rank_data.ref$ordering[rank_data.ref$ordering == 10 &
rank_data.ref$Year == "1978" &
rank_data.ref$Population.type %in% c("REF")] <- 11
rank_data.ref$ordering[rank_data.ref$ordering == 8.5 &
rank_data.ref$Year == "1978" &
rank_data.ref$CountryAsylumName == "Viet Nam" &
rank_data.ref$Population.type %in% c("REF")] <- 9
rank_data.ref$ordering[rank_data.ref$ordering == 8.5 &
rank_data.ref$Year == "1978" &
rank_data.ref$CountryAsylumName == "United Kingdom" &
rank_data.ref$Population.type %in% c("REF")] <- 10
## and for IPDs
rank_data.ref$CountryAsylumName <- as.character(rank_data.ref$CountryAsylumName)
## In 1996
rank_data.ref$ordering[rank_data.ref$ordering == 10 &
rank_data.ref$Year == "1996" &
rank_data.ref$Population.type %in% c("IDP")] <- 11
rank_data.ref$ordering[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1996" &
rank_data.ref$CountryAsylumName == "Somalia" &
rank_data.ref$Population.type %in% c("IDP")] <- 11
rank_data.ref$CountryAsylumName[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1996" &
rank_data.ref$CountryAsylumName == "Sri Lanka" &
rank_data.ref$Population.type %in% c("IDP")] <- "Sri Lanka / Somalia"
rank_data.ref$ordering[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1996" &
rank_data.ref$CountryAsylumName == "Sri Lanka / Somalia" &
rank_data.ref$Population.type %in% c("IDP")] <- 10
## in 1997
rank_data.ref$ordering[rank_data.ref$ordering == 10 &
rank_data.ref$Year == "1997" &
rank_data.ref$Population.type %in% c("IDP")] <- 11
rank_data.ref$ordering[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1997" &
rank_data.ref$CountryAsylumName == "Somalia" &
rank_data.ref$Population.type %in% c("IDP")] <- 11
rank_data.ref$CountryAsylumName[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1997" &
rank_data.ref$CountryAsylumName == "Sri Lanka" &
rank_data.ref$Population.type %in% c("IDP")] <- "Sri Lanka / Somalia"
rank_data.ref$ordering[rank_data.ref$ordering == 9.5 &
rank_data.ref$Year == "1997" &
rank_data.ref$CountryAsylumName == "Sri Lanka / Somalia" &
rank_data.ref$Population.type %in% c("IDP")] <- 10
rank_data.ref$CountryAsylumName <- as.factor(rank_data.ref$CountryAsylumName)
# Filter only top 10
rank_data.ref <- rank_data.ref[rank_data.ref$ordering <= 10, ]
#rank_data$Year = as.Date(as.character(rank_data$Year), format = "%Y")
## check our value for rank -- Note that there are different tie method
#levels(as.factor(rank_data.ref$ordering))
## Regnerate factors modality -
rank_data.ref$CountryAsylumName <- as.factor(as.character(rank_data.ref$CountryAsylumName))
# levels(as.factor(rank_data.ref$CountryAsylumName))
## Double checking country name
#table(end_year_population_totals_long$Country, useNA = "ifany")Generate Plot
p <- rank_data.ref[rank_data.ref$Population.type %in% c("REF"), ] %>%
ggplot(aes(y = Value2,
x = reorder(ordering, desc(ordering)),
group = CountryAsylumName ,)) +
geom_tile(aes(y = Value2 / 2,
height = Value2,
fill = REGION_UN), width = 0.9) +
geom_text(aes(label = CountryAsylumName),
hjust = "right", colour = "black",
fontface = "bold", nudge_y = -100000) +
geom_text(aes(label = scales::comma(Value2)),
hjust = "left", nudge_y = 100000, colour = "grey30") +
coord_flip(clip = "off") +
scale_fill_manual(name = 'REGION_UN', values = c("#7fc97f", "#beaed4", "#fdc086", "#ffff99", "#386cb0")) +
scale_x_discrete("") +
scale_y_continuous("",labels = unhcRstyle::format_si()) +
unhcRstyle::unhcr_theme() +
# hrbrthemes::theme_ipsum(plot_title_size = 32, subtitle_size = 24, caption_size = 12, base_size = 22) +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = c(0.8, 0.2),
legend.title = element_blank(),
plot.margin = margin(1,1,1,3,"cm"),
axis.text.y = element_blank()) +
# gganimate code to transition by year:
gganimate::transition_time(Year) +
gganimate::ease_aes('cubic-in-out') +
labs(title = 'Top 10 Refugee Hosting Countries',
subtitle = 'Refugee Population in {round(frame_time,0)}',
caption = 'Source: UNHCR http://popstats.unhcr.org')
library(gganimate)
#For GIF File Format:c
gganimate::animate(p, #plot
nframes = 1000, # The number of frames to render (default 100)
fps = 20, # The framerate of the animation in frames/sec (default 10)
width = 1000,
height = 700,
end_pause = 50,
renderer = gifski_renderer("anim_ref_race.gif"))