mirror of
https://github.com/BreizhHardware/TD-R.git
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58 lines
1.5 KiB
R
58 lines
1.5 KiB
R
if (!require("ggplot2")) {
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install.packages("ggplot2")
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}
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if (!require("rnaturalearth")) {
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install.packages("rnaturalearth")
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}
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if (!require("rnaturalearthdata")) {
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install.packages("rnaturalearthdata")
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}
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if (!require("dplyr")) {
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install.packages("dplyr")
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}
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library(ggplot2)
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library(rnaturalearth)
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library(rnaturalearthdata)
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library(dplyr)
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# Create a mapping between Olympic codes and ISO codes
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olympic_to_iso <- c(
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"GER" = "DEU" # Germany
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# Add other mappings here if needed
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# For example: "USA" = "USA", "GBR" = "GBR", etc.
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)
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participants_iso <- test_R$Pays_unique
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# Convert Olympic codes to ISO codes where needed
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participants_iso_fixed <- participants_iso
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for (i in 1:length(participants_iso)) {
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code <- participants_iso[i]
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if (code %in% names(olympic_to_iso)) {
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participants_iso_fixed[i] <- olympic_to_iso[code]
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}
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}
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# Load world map
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world <- ne_countries(scale = "medium", returnclass = "sf")
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# Check Germany's data
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germany_data <- world %>% filter(admin == "Germany")
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print("Germany data:")
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print(germany_data %>% select(admin, iso_a3, iso_a3_eh))
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# Mark participating countries
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world <- world %>%
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mutate(participant = ifelse(iso_a3 %in% participants_iso_fixed |
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iso_a3_eh %in% participants_iso_fixed, "Oui", "Non"))
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# Create the map
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ggplot(data = world) +
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geom_sf(aes(fill = participant), color = "black") +
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scale_fill_manual(values = c("Oui" = "lightgreen", "Non" = "lightgrey")) +
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theme_minimal() +
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labs(title = "Pays participants aux Jeux Olympiques de Paris 2024",
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fill = "Participation") |