if (interactive()) {
trade_by_continent <- d3po::trade
trade_by_continent <- aggregate(
trade ~ year + reporter_continent,
data = trade_by_continent,
FUN = sum
)
# Assign colors to continents
# my_pal <- tintin::tintin_pal(option = "The Broken Ear")(7)
# [1] "#749972" "#7EA691" "#8EBCC5" "#9DB457" "#A8C17F" "#BBCC4D" "#C7D88F"
my_pal <- c("#749972", "#7EA691", "#8EBCC5", "#9DB457", "#A8C17F", "#BBCC4D", "#C7D88F")
names(my_pal) <- c(
"Africa", "Antarctica", "Asia",
"Europe", "North America", "Oceania", "South America"
)
d3po(trade_by_continent, width = 800, height = 600) %>%
po_line(daes(x = year, y = trade, group = reporter_continent, color = my_pal)) %>%
po_labels(
x = "Year",
y = "Trade (USD billion)",
title = "Trade Distribution by Reporter Continent in 2019 and 2023"
)
}
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