I have 3 columns in a data frame from which I want to create a visualisation with geom_smooth() :

ggplot(my_data_frame)  
  aes(x = fin_enquete,
      y = intentions,
      colour = candidat)  
  geom_point(alpha = 1/6,
             shape = "circle", 
             size = .5L)  
  geom_smooth(mapping = aes(y = erreur_inf),
              size = .5L,
              span = .42,
              se = F)  
  geom_smooth(mapping = aes(y = erreur_sup),
              size = .5L,
              span = .42,
              se = F)  
  geom_smooth(method = "loess",
              size = 1.5L,
              span = .42,
              se = F)  
  labs(x = "Date de fin d'enquête", 
       y = "Pourcentage d'intentions de vote")  
  theme_minimal()  
  theme(text = element_text(family = "DIN Pro"))  
  coord_cartesian(expand = F)  
  easy_remove_legend()

CodePudding user response：

You could use lapply() smooth to calculate the range of df values such as (5,11,13) to calculate the smooths and plot only the two edges of the se.

Sample code:

      library(ggplot2)

ggplot(data = mtcars,
       mapping = aes(x = wt,
                     y = mpg))  
  geom_point(size = 2) 
  lapply(c(5,11, 13), function (i) {
  geom_smooth(
               data = ~ cbind(., facet_plots = i),
               method = lm,
               se=F,
               formula = y ~ splines::bs(x, i)
              ) 
  }) 
    #facet_wrap(vars(facet_plots))
  geom_ribbon( 
              stat = "smooth",
              method = "loess",
              se = TRUE,
              alpha = 0, # or, use fill = NA
              colour = "black",
              linetype = "dotted") 
  theme_minimal()

Plot: