functional_ggplot

dat %>%
  filter(str_detect(cultivo_de_cosecha, 'Tr|Ceb')) %>%
  select(campana,Zona, cultivo_de_cosecha, variedad,rinde ) %>% 
  group_by(cultivo_de_cosecha, Zona, variedad) %>%
  filter(n() > 5) %>% ungroup %>% 
  mutate_if(is.character, as.factor) ->dat1

dat1%>%
  count(cultivo_de_cosecha, Zona, variedad) %>%
  arrange(cultivo_de_cosecha, desc(n))

trigo_zona = levels(dat1$Zona) %>% 
  map(~ subset(dat1, cultivo_de_cosecha== "Trigo" & Zona == . ) %>%   
        ggplot()+
        aes(x=reorder(variedad, rinde, mean), y=rinde)+
        geom_point(alpha=0.3)+
        stat_summary(fun.data = "mean_cl_boot", colour = "red", size = 0.5)+
        coord_flip()+
        theme_bw2+
        stat_summary(aes(label=round(..y..,0)), 
                     fun=mean, geom="text", size=4,vjust = -0.5)+
        scale_y_continuous(breaks= scales::pretty_breaks())+
        labs(title = paste0(.), 
             x="", y="kg/ha")
  ) 

trigo_zona[[1]] %>% ggsave(file = "plots/trigo_var_Costa.png", w=5, h=5)
trigo_zona[[2]] %>% ggsave(file = "plots/trigo_var_Madariaga.png", w=5, h=5)
trigo_zona[[3]] %>% ggsave(file = "plots/trigo_var_Sierra.png", w=5, h=5)