Erasmus Teaching Mobility

library(plotly)

library(readxl)

pwt <- read_excel("C:/Users/hutku/Downloads/pwt1001.xlsx", sheet = "Data")

dffk <- dff %>% left_join(pwt)

libraries <- c(
    "tidyverse", "sf", "rnaturalearth",
    "wbstats", "gganimate", "classInt"
)

invisible(lapply(libraries, library, character.only = TRUE))

crs <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

world_sf <- ne_countries(
    type = "countries", scale = "small"
) %>%
    sf::st_as_sf() %>%
    sf::st_transform(crs)

world_sf_no_antartica <- world_sf %>%
    dplyr::filter(region_un != "Antarctica")

dffk <- dplyr::left_join(
    world_sf_no_antartica, dffk,
    by = c("iso_a2" = "iso2c")
)

countries_Melanesia <- dffk %>%
  filter(year ==2022, subregion == "Melanesia") %>%
  pull(country)

countries_SouthernEurope <- dffk %>%
  filter(year ==2022, subregion == "Southern Europe") %>%
  pull(country)

countries_NorthernAfrica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Northern Africa" ) %>%
  pull(country)

countries_NA <- dffk %>%
  filter(year ==2022) %>%
  filter(is.na(subregion)) %>%
  pull(country)

countries_MiddleAfrica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Middle Africa" ) %>%
  pull(country)

countries_SouthAmerica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "South America" ) %>%
  pull(country)

countries_WesternAsia <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Western Asia" ) %>%
  pull(country)

countries_AustraliaandNewZealand <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Australia and New Zealand" ) %>%
  pull(country)

countries_WesternEurope <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Western Europe" ) %>%
  pull(country)

countries_Caribbean <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Caribbean" ) %>%
  pull(country)

countries_SouthernAsia <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Southern Asia" ) %>%
  pull(country)

countries_EasternEurope <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Eastern Europe" ) %>%
  pull(country)

countries_CentralAmerica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Central America" ) %>%
  pull(country)

countries_WesternAfrica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Western Africa" ) %>%
  pull(country)

countries_SouthernAfrica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Southern Africa" ) %>%
  pull(country)

countries_SouthEasternAsia <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "South-Eastern Asia" ) %>%
  pull(country)

countries_EasternAfrica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Eastern Africa" ) %>%
  pull(country)

countries_NorthernAmerica <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Northern America" ) %>%
  pull(country)

countries_EasternAsia <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Eastern Asia" ) %>%
  pull(country)

countries_NorthernEurope <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Northern Europe" ) %>%
  pull(country)

countries_CentralAsia <- dffk %>%
  filter(year ==2022) %>%
  filter(subregion == "Central Asia" ) %>%
  pull(country)

phi <- dffk %>% filter(country %in% countries_WesternAsia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_WA <- dff %>% 
  filter(
    country %in% countries_WesternAsia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_WA <- as_tibble(df_WA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_WA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = "Armenia", label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Western Asia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

df_SA <- dff %>% 
  filter(
    country %in% countries_SouthernAsia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_SA <- as_tibble(df_SA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_SA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Southern Asia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_SouthernAsia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_SEA <- dff %>% 
  filter(
    country %in% countries_SouthEasternAsia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_SEA <- as_tibble(df_SEA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_SEA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'South-Eastern Asia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_SouthEasternAsia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_CA <- dff %>% 
  filter(
    country %in% countries_CentralAsia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_CA <- as_tibble(df_CA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_CA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Central Asia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_CentralAsia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_EA <- dff %>% 
  filter(
    country %in% countries_EasternAsia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_EA <- as_tibble(df_EA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_EA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 2.5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Eastern Asia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_EasternAsia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_MAL <- dff %>% 
  filter(
    country %in% countries_Melanesia,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_MAL <- as_tibble(df_MAL)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_MAL %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Melanesia',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_Melanesia) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_SE <- dff %>% 
  filter(
    country %in% countries_SouthernEurope,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_SE <- as_tibble(df_SE)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_SE %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 6, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Southern Europe',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_SouthernEurope) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_WE <- dff %>% 
  filter(
    country %in% countries_WesternEurope,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_WE <- as_tibble(df_WE)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_WE %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 4, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Western Europe',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_WesternEurope) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_EE <- dff %>% 
  filter(
    country %in% countries_EasternEurope,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_EE <- as_tibble(df_EE)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_EE %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Eastern Europe',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_EasternEurope) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_NE <- dff %>% 
  filter(
    country %in% countries_NorthernEurope,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_NE <- as_tibble(df_NE)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_NE %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Northern Europe',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_NorthernEurope) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_NA <- dff %>% 
  filter(
    country %in% countries_NorthernAfrica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_NA <- as_tibble(df_NA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_NA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Northern Africa',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_NorthernAfrica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_MA <- dff %>% 
  filter(
    country %in% countries_MiddleAfrica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_MA <- as_tibble(df_MA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_MA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Middle Africa',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_MiddleAfrica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_WA <- dff %>% 
  filter(
    country %in% countries_WesternAfrica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_WA <- as_tibble(df_WA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_WA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Western Africa',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_WesternAfrica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_SA <- dff %>% 
  filter(
    country %in% countries_SouthernAfrica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_SA <- as_tibble(df_SA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_SA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Southern Africa',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_SouthernAfrica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_EA <- dff %>% 
  filter(
    country %in% countries_EasternAfrica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_EA <- as_tibble(df_EA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_EA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Eastern Africa',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_EasternAfrica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_SA <- dff %>% 
  filter(
    country %in% countries_SouthAmerica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_SA <- as_tibble(df_SA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_SA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'South America',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_SouthAmerica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")
count

animate(plot = phi,
        nframes = 30)

df_CA <- dff %>% 
  filter(
    country %in% countries_CentralAmerica,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_CA <- as_tibble(df_CA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_CA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 5, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Central America',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_CentralAmerica) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_NA <- dff %>% 
  filter(
    country %in% c(countries_NorthernAmerica,countries_AustraliaandNewZealand),
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_NA <- as_tibble(df_NA)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_NA %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'United States & New Zealand & Australia & New Zealand',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% c(countries_NorthernAmerica,countries_AustraliaandNewZealand)) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_CAR <- dff %>% 
  filter(
    country %in% countries_Caribbean,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_CAR <- as_tibble(df_CAR)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_CAR %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 3, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Caribbean',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

phi <- dffk %>% filter(country %in% countries_Caribbean) %>%
ggplot(aes(x = year,
           y = verim,
           col = country)) +
  geom_line(show.legend = FALSE) +
  facet_wrap(~country, scales = "free") +
  transition_reveal(year)  +
  labs(title = "Year: {frame_along}")

animate(plot = phi,
        nframes = 30)

df_OC <- dff %>% 
  filter(
    country %in% countries_NA,
    year %in% c(2003, 2022),
  ) %>%
  mutate(year = factor(year)) %>% 
  select(country, year, verim)

df_OC <- as_tibble(df_OC)  %>% 
  arrange(country, year) %>% 
  mutate(
    change_verim = diff(verim), 
    order_dumbbells = if_else(change_verim < 0, -1, 1) * verim[2],
    .by = country
  )  %>% 
  mutate(country = fct_reorder(country, order_dumbbells))

df_OC %>% 
  ggplot(aes(x = verim, y = country)) +
  geom_path(
    aes(color = (change_verim < 0)),
    linewidth = 1,
    arrow = arrow(length = unit(0.3, 'cm'), type = 'closed')
  ) +
  geom_vline(xintercept=1, linetype='dotted', col = 'red')+
  annotate("text", x = 1, y = 12, label = "Self-Sufficient Treshold", angle=90) +
  labs(
    title = 'Other Countries',
    x = 'Verim (2003 - 2022)', 
    y = element_blank(),
    fill = 'Year'
  ) +
  theme(
    panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = 'none'
  )

# Robinson
robinson_crs <- "+proj=robin +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs"
dffk_robinson <- dffk %>%
    sf::st_transform(robinson_crs)
vmin <- min(dffk$verim, na.rm = T)
vmax <- max(dffk$verim, na.rm = T)

brk <- round(classIntervals(
    dffk$verim,
    n = 77,
    style = "fisher"
)
$brks, 1) %>%
    head(-1) %>%
    tail(-1) %>%
    append(vmax)
breaks <- c(vmin, brk)

# Number of colors needed
num_colors <- 78

# Generate a color palette
new_cols <- rainbow(num_colors)

# Reverse the order if needed
new_cols <- rev(new_cols)

# Print or use the new color palette
print(new_cols)

cols <- rev(new_cols)

animated_map <- function() {
    world_map <- ggplot(
        data = dffk,
        aes(fill = verim)
    ) +
        geom_sf(color = "white", size = 0.05) +
        scale_fill_gradientn(
            name = "",
            colours = cols,
            breaks = breaks,
            labels = round(breaks, 1),
            limits = c(vmin, vmax),
            na.value = "grey70"
        ) +
        coord_sf(crs = robinson_crs) +
        guides(fill = guide_legend(
            direction = "vertical",
            keyheight = unit(1, units = "mm"),
            keywidth = unit(1, units = "mm"),
            title.position = "top",
            title.hjust = .5,
            label.hjust = .5,
            nrow = 6,
            byrow = T,
            reverse = F,
            label.position = "right"
        )) +
        theme_minimal() +
        theme(
            axis.line = element_blank(),
            axis.text.x = element_blank(),
            axis.text.y = element_blank(),
            axis.ticks = element_blank(),
            axis.title.x = element_blank(),
            axis.title.y = element_blank(),
            legend.position = c(.5, -.015),
            legend.text = element_text(size = 5, color = "grey10"),
            panel.grid.major = element_line(color = "white", size = .2),
            panel.grid.minor = element_blank(),
            plot.title = element_text(
                face = "bold", size = 20,
                color = "grey10", hjust = .5, vjust = -3
            ),
            plot.subtitle = element_text(
                size = 40, color = "#c43c4e",
                hjust = .5, vjust = -1
            ),
            plot.caption = element_text(
                size = 8, color = "grey10",
                hjust = .5, vjust = -10
            ),
            plot.margin = unit(c(t = -4, r = -4, b = -4, l = -4), "lines"),
            plot.background = element_rect(fill = "white", color = NA),
            panel.background = element_rect(fill = "white", color = NA),
            legend.background = element_rect(fill = "white", color = NA),
            panel.border = element_blank()
        ) +
        labs(
            x = "",
            y = "",
            title = "Verim",
            subtitle = "Year: {as.integer(closest_state)}",
            caption = ""
        )

    return(world_map)
}

world_map <- animated_map()
print(world_map)

timelapse_world_map <- world_map +
    transition_states(year) +
    enter_fade() +
    exit_fade() +
    ease_aes("quadratic-in-out", interval = .2)

animated_world <- gganimate::animate(
    timelapse_world_map,
    nframes = 120,
    duration = 22,
    start_pause = 3,
    end_pause = 30,
    height = 6,
    width = 7.15,
    res = 300,
    units = "in",
    fps = 15,
    renderer = gifski_renderer(loop = T)
)

animated_world

library(showtext)
library(ggtext)
library(ggrepel)

data <- dffk %>% filter(year==2019 & !is.na(hc) )

hcverim <- data %>%
  ggplot(aes(x= hc, y=verim)) + 
  geom_point() +
  geom_text(data= data, aes(y = verim + .25, label=iso_a2, colour = region),
            size = 2) +
  geom_hline(yintercept=1, linetype='dotted', col = 'black') +
  geom_vline(xintercept=2.5, linetype='dotted', col = 'black') +
  geom_smooth(data=subset(data,verim>1 & hc>2.5),
               method=lm,se=FALSE) +
  labs(title = "Verim vs Human Capital (2022)",
       subtitle = NULL,
       tag = NULL, 
       x = "Human Capital",
       y= "Verim",
       color = NULL) +
  theme(
    axis.title.x = element_markdown(),
    axis.title.y = element_markdown(),
    axis.ticks = element_blank(),
    axis.line = element_line(),
    panel.background = element_rect(fill="#FFFFFF")
  ) 

lm_eqn <- function(df){
    m <- lm(verim ~ hc, df);
    eq <- substitute(verim == a + b %.% hc*","~r^2~"="~r2, 
         list(a = format(unname(coef(m)[1]), digits = 2),
              b = format(unname(coef(m)[2]), digits = 2),
             r2 = format(summary(m)$r.squared, digits = 3)))
    as.character(as.expression(eq));
}

hcverim + geom_text(x = 4, y = 3, label = lm_eqn(data %>% filter(hc>2.5, verim>1)), size = 4, parse = TRUE) + 
  geom_text(x = 1.2, y = 8, label = "A", size = 6, parse = TRUE) + 
  geom_text(x = 1.2, y = 0, label = "B", size = 6, parse = TRUE) + 
  geom_text(x = 4.2, y = 8, label = "C", size = 6, parse = TRUE) + 
  geom_text(x = 4.2, y = 0, label = "D", size = 6, parse = TRUE)

govverim <- data %>%
  ggplot(aes(x= csh_g, y=verim)) + 
  geom_point() +
  geom_text(data= data, aes(y = verim + .25, label=iso_a2, colour = region),
            size = 2) +
  geom_hline(yintercept=1, linetype='dotted', col = 'black')  +
  geom_smooth(data=subset(data,verim>1),method=lm,se=FALSE) +
  labs(title = "Verim vs Government spending share",
       subtitle = NULL,
       tag = NULL, 
       x = "Government spending share",
       y= "Verim",
       color = NULL) +
  theme(
    axis.title.x = element_markdown(),
    axis.title.y = element_markdown(),
    axis.ticks = element_blank(),
    axis.line = element_line(),
    panel.background = element_rect(fill="#FFFFFF")
  ) 

govverim

lm_eqn2 <- function(df){
    m <- lm(verim ~ csh_g, df);
    eq <- substitute(verim == a + b %.% csh_g*","~r^2~"="~r2, 
         list(a = format(unname(coef(m)[1]), digits = 2),
              b = format(unname(coef(m)[2]), digits = 2),
             r2 = format(summary(m)$r.squared, digits = 3)))
    as.character(as.expression(eq));
}

govverim + geom_text(x = 0.09, y = 2.5, label = lm_eqn2(data %>% filter(verim>1)), size = 3, parse = TRUE)