Plot of the SFS index for South America

sfs-index-south-america.R

library(countrycode)
library(tidyverse)
library(ggrepel)

df <- readxl::read_excel("Sustainable_food_systems_global_index-1.xlsx", sheet = 1, skip = 5)

df <- df %>% 
  mutate(
    region = countrycode(origin = "iso3c",
                         sourcevar = ISO3,
                         destination = "region")
  ) %>% 
  mutate_at(
    3:8,
    as.numeric
  ) %>% 
  pivot_longer(
    cols = 3:8,
    names_to = "period",
    values_to = "sfs"
  ) %>% 
  mutate(
    period = str_remove(string = period, pattern = "SFS index ")
  )

sa <- df %>% 
  filter(
    region == "South America"
  )

sa_avg <- sa %>% 
  group_by(region, period) %>% 
  summarise(
    sfs = mean(sfs)
  ) %>% 
  mutate(
    Country = region,
    ISO3 = ""
  ) %>% 
  select(
    Country, ISO3, region, period, sfs
  )

sa <- bind_rows(sa, sa_avg)

ggplot(sa, aes(x = period, y = sfs, color = Country, group = Country)) +
  geom_point(show.legend = FALSE) +
  geom_line(show.legend = FALSE) +
  geom_label_repel(
    data = sa %>% filter(period == "2000-2003"),
    aes(label = Country, x = period, y = sfs, color = Country),
    hjust = 1, show.legend = FALSE, nudge_x = -.1
  ) +
  ylim(0.4, .65) +
  labs(
    y = "SFS Index",
    x = "Period",
    title = "Sustainable Food Systems Index -- South America",
    subtitle = "Source: hhttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GYEG59"
    caption = "2019-11-25 // @jmcastagnetto, Jesus M. Castagnetto"
  ) +
  scale_color_discrete() +
  theme_bw(16)