classic_yield_plot

library("tidyverse")

cebada <- tibble::tribble(
  ~trt,        ~trat_id, ~bq,       ~rend_seco,
  1,          "Test",   1,  7527.0792385361,
  2,  "Allegro 1000",   1, 7834.14085058484,
  3, "Azoxy Pro 400",   1, 7105.33761425004,
  1,          "Test",   2,  7073.4451399919,
  2,  "Allegro 1000",   2, 8198.71524530747,
  3, "Azoxy Pro 400",   2, 7312.61874119017,
  1,          "Test",   3, 8263.95165943664,
  2,  "Allegro 1000",   3, 8342.18786257771,
  3, "Azoxy Pro 400",   3, 7980.40317044249
)

cebada %>% 
  group_by(trt) %>% 
  summarise(rend_seco = mean(rend_seco)) %>%
  mutate(respuesta = ((rend_seco-first(rend_seco))/first(rend_seco)*100) %>%
           round(1) %>% 
           paste0(ifelse(. >= 0, "+", ""), ., "%")) -> cebada_sum

cebada %>% 
  ggplot()+
  aes(x=factor(trt), y=rend_seco)+
  geom_bar(stat = 'summary', fun = 'mean') +
  scale_x_discrete(labels = unique(cebada$trat_id))+
  stat_summary(fun.data=mean_cl_boot, geom="errorbar", width = 0.1) + 
  geom_point(shape = 21)+
  geom_hline(aes(yintercept = 
                   cebada_sum %>% 
                   dplyr::filter(trt==1) %>% 
                   pull(rend_seco)),
             linetype=2, col="gray30")+
  theme_bw()+
  geom_text(data = cebada_sum, 
            aes(label = respuesta, x = trt, y = rend_seco, vjust= 1.2), 
            size =3, col = "white")+
  labs(x = "", y = "kg/ha")+
  theme(axis.text.x = element_text(angle = 60, vjust = 1, hjust=1))