multiple scatter plots with 95 confidence interval

I have a dataset with groups and I want to plot three lines of each group representing one variable, the lines should show 95% CI.
I read about geom_ribbon but I couldn't success to do it. Can you please provide a clear example?




# Generate example data
(huron <- data.frame(year = 1875:1972, level1 = as.vector(LakeHuron),
                     level2 = 1.1*as.vector(LakeHuron)) %>% pivot_longer(
                       values_to = "level"
                     ) %>% mutate(
                       numbers_below_level = level-9,
                       numbers_above_level = level +5 

# plot the data
(h <- ggplot(huron, aes(x=year,group=group)) +
  geom_ribbon(aes(ymin = numbers_below_level,
                  ymax =numbers_above_level),
              fill = "grey70",alpha=.5) +
  geom_line(aes(y = level,colour=group),size=2))

I think I need to calculate summary statistics of my data first in order to define the ci bands!

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Because I didn't calculate anything with confidence intervals.... Once you have your data, you can plot your data. I thought you were asking a plotting question, are you asking a modelling question? :thinking:

Thanks. I already have the data as a csv. I need to define the ymin and ymax. I do not understand why in the example you use 9 and 5?