Ggplot2 Add a geometry line for each face in the almanac plantation

Question

I have the following data frame

structure(list(Lightbox = c(84L, 67L, 80L, 63L, 76L, 66L, 79L, 81L, 77L, 82L, 84L, 67L, 80L, 63L, 76L, 66L, 79L, 81L, 77L, 82L, 84L, 67L, 80L, 63L, 76L, 66L, 79L, 81L, 77L, 82L, 84L, 67L, 80L, 63L, 76L, 66L, 79L, 81L, 77L, 82L, 84L, 67L, 80L, 63L, 76L, 66L, 79L, 81L, 77L, 82L), variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("S1", "S2", "S3", "S4", "S5"), class = "factor"), value = c(82L, 65L, 73L, 50L, 50L, 50L, 72L, 56L, 76L, 78L, 88L, 66L, 71L, 60L, 54L, 55L, 63L, 68L, 73L, 75L, 73L, 65L, 76L, 57L, 51L, 57L, 75L, 65L, 69L, 66L, 77L, 67L, 79L, 58L, 55L, 56L, 77L, 66L, 73L, 80L, 78L, 62L, 78L, 52L, 63L, 59L, 71L, 64L, 69L, 89L), mean = c(83, 66, 76.5, 56.5, 63, 58, 75.5, 68.5, 76.5, 80, 86, 66.5, 75.5, 61.5, 65, 60.5, 71, 74.5, 75, 78.5, 78.5, 66, 78, 60, 63.5, 61.5, 77, 73, 73, 74, 80.5, 67, 79.5, 60.5, 65.5, 61, 78, 73.5, 75, 81, 81, 64.5, 79, 57.5, 69.5, 62.5, 75, 72.5, 73, 85.5), diff = c(2L, 2L, 7L, 13L, 26L, 16L, 7L, 25L, 1L, 4L, -4L, 1L, 9L, 3L, 22L, 11L, 16L, 13L, 4L, 7L, 11L, 2L, 4L, 6L, 25L, 9L, 4L, 16L, 8L, 16L, 7L, 0L, 1L, 5L, 21L, 10L, 2L, 15L, 4L, 2L, 6L, 5L, 2L, 11L, 13L, 7L, 8L, 17L, 8L, -7L)), .Names = c("Lightbox", "variable", "value", "mean", "diff"), row.names = c(NA, -50L), class = "data.frame") 

I want to plot a bold altman, different from the average for 5 phase groups S1-> S5, which is quite simple

p <- ggplot(df_melt, aes(mean, diff))+ geom_point(na.rm=TRUE)+ facet_wrap(~variable)

However, I would also like to add some geometry to each face, showing the average value for each group and standard deviations. If I had only one group, I would do the following:

 yintercepts_mean <- c(mean(df_melt$diff, na.rm = TRUE)) yintercepts_mean_r <- round(yintercepts_mean,3) yintercepts_sd_p <- c(mean(df_melt$diff, na.rm = TRUE) + c(2) * sd(df_melt$diff, na.rm = TRUE)) yintercepts_sd_n <- c(mean(df_melt$diff, na.rm = TRUE) + c(-2) * sd(df_melt$diff, na.rm = TRUE)) yintercepts_sd_p_r <- round(yintercepts_sd_p,3) yintercepts_sd_n_r <- round(yintercepts_sd_n,3) #ylabels <- c("- 2SD", "+ 2SD", "Mean") ylabels <- c("mean") ylabels2 <- c("+ 2SD") ylabels3 <- c("- 2SD") p + geom_hline(yintercept = yintercepts_mean_r, linetype=1, color='blue') + geom_hline(yintercept = yintercepts_sd_p_r, linetype=2, color='blue') + geom_hline(yintercept = yintercepts_sd_n_r, linetype=2, color='blue') 

How can I include the above when faceting my data?

Answer 1

 library(plyr) df2 <- ddply(df_melt,.(variable),summarise,mean=mean(diff, na.rm = TRUE), sd=sd(diff, na.rm = TRUE)) library(ggplot2) p <- ggplot(df_melt, aes(mean, diff)) + geom_point(na.rm=TRUE) + geom_hline(data=df2,aes(yintercept=c(round(mean,3), round(mean+2*sd,3), round(mean-2*sd,3))), linetype=c(1,2,2), color='blue') + facet_wrap(~variable) print(p)