Fill region between two loess-smoothed lines in R with ggplot

A possible solution where the loess smoothed data is grabbed from the plot object and used for the geom_ribbon:

# create plot object with loess regression linesg1 <- ggplot(df) +   stat_smooth(aes(x = x, y = ymin, colour = "min"), method = "loess", se = FALSE) +  stat_smooth(aes(x = x, y = ymax, colour = "max"), method = "loess", se = FALSE)g1# build plot object for rendering gg1 <- ggplot_build(g1)# extract data for the loess lines from the 'data' slotdf2 <- data.frame(x = gg1$data[[1]]$x,                  ymin = gg1$data[[1]]$y,                  ymax = gg1$data[[2]]$y) # use the loess data to add the 'ribbon' to plot g1 +  geom_ribbon(data = df2, aes(x = x, ymin = ymin, ymax = ymax),              fill = "grey", alpha = 0.4)

Not an answer per se, but some code to borrow and run first if you want to run the answer from Henrik.

library(tidyverse)df <- tribble(~row, ~x, ~y,    ~ymin,   ~ymax,  ~grp, ~ydiff,1,   1,  3.285614,  3.285614, 10.14177, min, 6.8561586,2,   1, 10.141773,  3.285614, 10.14177, max, 6.8561586,3,   2,  5.061879,  5.061879, 11.24462, min, 6.1827368,4,   2, 11.244615,  5.061879, 11.24462, max, 6.1827368,5,   3,  8.614408,  8.614408, 13.45030, min, 4.8358931,6,   3, 13.450301,  8.614408, 13.45030, max, 4.8358931,7,   4,  6.838143,  6.838143, 12.34746, min, 5.5093150,8,   4, 12.347458,  6.838143, 12.34746, max, 5.5093150,9,   5, 10.390673, 10.390673, 14.55314, min, 4.1624713,10,  5, 14.553144, 10.390673, 14.55314, max, 4.1624713,11,  6, 12.166937, 12.166937, 15.65599, min, 3.4890495,12,  6, 15.655987, 12.166937, 15.65599, max, 3.4890495,13,  7, 13.943202, 13.943202, 16.75883, min, 2.8156277,14,  7, 16.758830, 13.943202, 16.75883, max, 2.8156277,15,  8,  5.950011,  5.950011, 11.79604, min, 5.8460259,16,  8, 11.796037,  5.950011, 11.79604, max, 5.8460259,17,  9, 17.495731, 17.495731, 18.96452, min, 1.4687841,18,  9, 18.964515, 17.495731, 18.96452, max, 1.4687841,19, 10, 15.719466, 15.719466, 17.86167, min, 2.1422059,20, 10, 17.861672, 15.719466, 17.86167, max, 2.1422059,21, 11, 19.271996, 19.271996, 20.06736, min, 0.7953623,22, 11, 20.067358, 19.271996, 20.06736, max, 0.7953623)