rough work.R

total_prod_year <-  continents %>% 
  group_by(Year) %>% 
  summarise(total_production = sum(production))


p <- total_prod_year %>% 
  ggplot(aes(x = Year, y=total_production ))+
  geom_line(color = "steelblue",linewidth = 1)+
  geom_point(color = "red")+
  labs(title = "Global Production",
       x = "Year",
       y = "Production (Metric Tons)",           
       caption = "Source:Ourworldindata.org"
  )+
  theme( plot.title = element_text(hjust = 0.5, size = 14, face = "bold"),
         axis.title = element_text(size = 12),
         axis.text = element_text(size = 10))









q <- continents %>% 
  ggplot(aes(x = Year,y = production, colour = Entity))+
  geom_line(size = 1)+
  labs(title = "Trends in Beans Production Across Continents ",
     x = "Year",
       y = "Production (Metric Tons)",           
       color = "Continent"
  )+
  theme(
    plot.title = element_text(hjust = 0.5, size = 14, face = "bold"), 
    plot.subtitle = element_text(hjust = 0.5, size = 12),            
    legend.position = "right",                                    
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10)
  )


k <- countries %>%  
  group_by(Entity) %>% 
  summarise(Total_production = sum(production)) %>% 
  slice_max(order_by =  Total_production, n= 5) %>%  
  ggplot(aes(x = reorder(Entity,Total_production),y = Total_production,fill = Entity))+
  geom_col(show.legend = FALSE)+
  coord_flip()+
  labs(
    title = "Top 5 Beans Producing Countries",
    x = "Country",
    y = "Total Production (Metric Tons)"
  )+
  theme( plot.title = element_text(hjust = 0.5, size = 14, face = "bold"))

m <- continents %>% 
  ggplot(aes(x = Year,y = Entity,fill = production))+
  geom_tile()+
  scale_fill_viridis_c(option = "viridis")+
  labs(title = "Regional Production",
   
    x = "Year",
    y = "Region",
    fill = "Production"
  )+
  theme( plot.title = element_text(hjust = 0.5, size = 14, face = "bold"))

library(patchwork)

(p + q)

q + m

p+ m