df_countries <- df.export %>% pivot_longer(!Country,names_to ="year", values_to ="value") %>%
  mutate(year = as.numeric(year)) %>%
  select(c(Country,year,value))

# Impute missing values in value with their mean
df_countries<- df_countries %>%
  mutate(value = ifelse(is.na(value), mean_value, value))
#Using ggplot to show the total values in different countries as the sample

# The distribution on export country in 2021
tb_inc <- df_countries %>%
  filter(year == 2021) %>%
  group_by(Country) %>%
  summarise(value = sum(value, na.rm = TRUE)) %>%
  ungroup()
tb_inc <- tb_inc %>% 
  mutate(country=recode(Country, 
                        "United States"="USA", 
                        "United Kingdom"="UK",
                        "Republic of Korea"="Korea"))
tb_map <- left_join(world_map, tb_inc, by=c("region"="country"))
ggplot(tb_map) + 
  geom_polygon(aes(x=long, y=lat, group=group, fill= value)) +
  theme_map() +
  scale_fill_viridis(na.value = "grey", name="ExportValue")

ggplot(df.export2)  + 
  geom_line(aes(x=Year, y=NaturalGas,colour="NaturalGas"),linewidth=1.5)+
  geom_line(aes(x=Year, y=IronOre,colour = "IronOre"),linewidth=1.5)+
  geom_line(aes(x=Year, y=Gold,colour = "Gold"),linewidth=1.5)+
  geom_line(aes(x=Year, y=Coal,colour = "Coal"),linewidth=1.5)+
  
  geom_point(shape=1, aes(x=Year, y=NaturalGas),size=2)+
  geom_point(shape=2, aes(x=Year, y=IronOre),size=2)+
  geom_point(shape=5, aes(x=Year, y=Coal),size=2)+
  geom_point(shape=11, aes(x=Year, y=Gold),size=2)+
  
  theme(legend.title = element_blank(),
        legend.position = 'bottom',
        axis.title.x = element_text(size=11, face = 'bold'),
        axis.title.y = element_text(size=11, face='bold'),
        legend.box.background = element_rect(colour = 'black'),
        legend.background = element_blank())+
  scale_x_continuous(breaks = round(seq(min(df.export2$Year), max(df.export2$Year), by = 1),1)) +
  labs(y='Commodity', x='Year')

ggplot(df.export2) +
  geom_bar(aes(x = Year, y = IronOre, fill = "IronOre"), stat = "identity", color = "green", size = 0.5) +
  geom_line(aes(x = Year, y = Education, color = "Education"), stat = "identity", group = 1, size = 1.5) +
  geom_text(aes(label = round(IronOre), x = Year, y = IronOre), color = "blue") +
  geom_text(aes(label = round(Education), x = Year, y = 0.9 * Education), color = "blue") +
  ggtitle("Comparison on Export of Iron Ore and Education from 2016 to 2021") +
  ggeasy::easy_center_title() +
  theme(legend.title = element_blank(),
        legend.position = "bottom",
        axis.title.x = element_text(size = 11, face = "bold"),
        axis.title.y = element_text(size = 11, face = "bold"),
        legend.box.background = element_rect(colour = "black"),
        legend.background = element_blank()) +
  scale_fill_manual(values = "#87CEEB") +
  scale_color_manual(values = c(Education = "purple")) +
  scale_x_continuous(breaks = round(seq(min(df.export2$Year), max(df.export2$Year), by = 1), 1)) +
  labs(y = "Commodity", x = "Year")