Show standard devation using geom_smooth and ggplot

Question

We have some data which represents many model runs under different scenarios. For a single scenario, we\'d like to display the smoothed mean, with the filled areas representing

Answer 1

The accepted answer just works if measurements are aligned/discretized on x. In case of continuous data you could use a rolling window and add a custom ribbon

iris %>%
    ## apply same grouping as for plot
    group_by(Species) %>%
    ## Important sort along x!
    arrange(Petal.Length) %>%
    ## calculate rolling mean and sd
    mutate(rolling_sd=rollapply(Petal.Width, width=10, sd,  fill=NA), rolling_mean=rollmean(Petal.Width, k=10, fill=NA)) %>%  # table_browser()
    ## build the plot
    ggplot(aes(Petal.Length, Petal.Width, color = Species)) +
    # optionally we could rather plot the rolling mean instead of the geom_smooth loess fit
    # geom_line(aes(y=rolling_mean), color="black") +
    geom_ribbon(aes(ymin=rolling_mean-rolling_sd/2, ymax=rolling_mean+rolling_sd/2), fill="lightgray", color="lightgray", alpha=.8) +
    geom_point(size = 1, alpha = .7) +
    geom_smooth(se=FALSE)