How to change the order of groups on the x axis without loosing the info of the statistical tests?

Question

I want to make a graph with the package ggpubr, which shows significance difference between the group mean and overall mean. I managed to do so, but when I want to re-order the groups (Riv) on the x-axis according to (Reg), the starts that indicate significant differences disappear.

This codes works:

pboxHg_stat = ggboxplot(dtnew, x="Riv", y= "Hg_RecoveryCorrected", fill = "Reg")+
  rotate_x_text(angle = 90)+
  geom_hline(yintercept = mean(dtnew$Hg_RecoveryCorrected, na.rm = TRUE), linetype=2)+
  stat_compare_means(method = "anova", label.y = 1000, na.rm = TRUE)+
  stat_compare_means(label="p.signif", method = "t.test", ref.group = ".all.", hide.ns = TRUE)

But when I add the line of code to reorder the groups on the x-axis the "*" disappear.

pboxHg_stat = ggboxplot(dtnew, x="Riv", y= "Hg_RecoveryCorrected", fill = "Reg")+
  rotate_x_text(angle = 90)+
  geom_hline(yintercept = mean(dtnew$Hg_RecoveryCorrected, na.rm = TRUE), linetype=2)+
  stat_compare_means(method = "anova", label.y = 1000, na.rm = TRUE)+
  stat_compare_means(label="p.signif", method = "t.test", ref.group = ".all.", hide.ns = TRUE)+
  scale_x_discrete(limits = RivHg)

enter image description here

dput(dtnew1) structure(list(Reg = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("MA", "SE", "SW"), class = "factor"), Riv = structure(c(17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L), .Label = c("abe", "bos", "dom", "erk", "gel", "itt", "jek", "lak", "led", "mdb", "mei", "mlb", "mne", "mom", "mot", "osc", "vel", "vne", "waa", "win", "wit" ), class = "factor"), Hg = c(326.6, 278.6, 239.9, 344.7, 256.2, 364.2, 360.5, 244.3, 193.7, 195.9, 160.9, 254.1, 260.6, 125, 195.7, 87.2, 170.4, 105, 127.5, 115.9, 115.6, 200.7, 78.4, 193.6, 66.9, 102.9, 153.6, 188.6, 251.5, 213, 147.5, 187.8, 59.6, 201.4, 99.1, 259.1, 125.6, 129.4, 224.9, 334.3, 257, 227.6, 210.2, 0.4, 2.6, 138.3, 163.6, 206.8, 89.5, 132.1, 23.9, 95.1, 91.9, 105.7, 140.4, 71.7, 87.9, 88.5, 16.3, 35.6, 28, 154.3, 133.5, 86.7, 147.2, 118.9, 84.2, 127.1, 17.2, 164.8, 20.7, 10.2, 24.8, NA, NA, 133, 132.8, 73.2, 54.7, 82.3, 57.2, 6.1, 116.8, NA, 181, 61.9, 79.2, 147.6, 4.1, 220.9, 74.7, 233.2, 92.8, 24.5, 23.4, 6.2, 71.5, 82.2, 71.7, 109.7, 55.9, 309.9, 35.7, 29.9, 54.4, 71.5, 64.4, 55.1, 20.6, 48.3, 79, 5.1, 38.6, 355.9, 11.5, 52.7, 96, 32.4, 79, 75.3, 24.8, 79.9, 95.1, 297.2, 176.3, 167.1, 242.4, 117.9, 127.2, 166.6, 154.9, 209.6, 21.4, 180.8, 65, 18.3, 216, 124, 225.8, 202.8, 69.4, 143.6, 51.3, 34.3, 211, 183.4, 109.7, 94.3, 234.5, 61.5, 50.4, 50.6, 17.5, 63.5, 109.9, 182.2, 173.7, 95.4, NA, 81.4, 92.5, 129.2, 57.6, 136.1, 2.6, 79.7, 20.4, 77.4, 102.9, 87.9, 138.7, 6.2, 6.6, NA, 50.2, 45.9, 3.2, 8.1, 17.9, 3.2, 38.2, 31, 21.6, 37.4, 28, 24.7, 3.1, 10.2, 36.1, 38.9, 19.3, 16.1, 24.5, 4.3, 40.5, 36.1, 8.2, 33.3, 4, 17.3, 331.6, 396.4, 321.6, 396.6, 332, 287.8, 235.1, 315.2, 432.3, 352.1, 291, 267.1, 213.2, 364.8, 376.3, 403.4, 404.1, 278.8, 212.2, 336.9, 252.9, 524.6, 283.5, 217.1, NA, 90.2, 41.4, 38.9, 31.2, 10.6, 5.9, 56, 27.3, 34.2, 50, 4.6, 38.9, 49.4, 44.1, 83.3, 96.7, 61, 98, 118.3, 51, 68, 69.2, 70.3, 76.5, 63.3, 116.4, 129.2, 101.3, 84.2, 83.8, 112.7, 106.7, 153.3, 162.2, 100.9, 126.2, 142.4, 160, 84.5, 107.5, 114.5, 142.5, 118.4, 151.2, 139.4, 120.2, 134.7, 144.3, 189.2, NA, 435, 482.2, 34.2, 6.7, NA, 174.7, 46.5, 48.5, 107.4, 12.1, 9.8, 123.5, 38.1, 68.9, 9.4, 228.3, 51.2, 200.5, 91.4, 170.8, 35.1, 28.2, 45.2, 7.6, 2.9, 220.4, 146.6, 159.6, 70.2, 88.9, 182.6, 47.1, 122.2, 112.7, 161, 65.8, 199.7, 169.4, 197.8, 128.1, 128.7, 214.8, 143.4, 204, 141.5, 356.1, 203.9, 51.4, 234.7, 272.7, 21.9, 5.3, 117.3, 6, 39.5, 53.6, 8.4, 59.7, 15.5, 77.8, 114.4, 74.2, 71.1, 59.1, 58.1, 102.1, 94.4, 155.3, 146.4, 154.3, 179.7, 113.8, 116.4, 142.6, 139.4, 152.4, 144.5, 214.2, 148.9, 178.5, 176.5, 167.7, 168, 192.4, 155.7, 179.3, 202.5, 178.2, 184.1, 229.3, 243.6, 184.8, 145.9, 190.8, 180.7, 428.1, 230.8, 160.9, 176.9, 170.3, 161, 185.6, 153, 112.2, 127.9, 104.7, 92.1, 77.7, 149.8, 199, 111.5, 131.8, 150.7, 80.9, 105.6, 84.7, 109.5, 107.7, 102.1, 146.6, 95, 106.3, 127.4, 252.8, 117.9, 87.3, 112.9, 72.2, 90.3, 99.8, 105.6, 99.7, 92.8, 113.9, 88.7, 211.7, 345.2, 94.9, 76.1, 32.4, 211, 107.8, 94.4, 152.3, 89.6, 95.5, 121.9, 51.9, 71.3, 81.2, 184.1, 234.9, 167.6, 218.2, 190.5, 261.3, 189.5, 316.8, 257.2, 398.7, 229, 228.7, 336.2, 156.8, 128.4, 126, 152.9, 324.4, 215.7, 211.5, 152.5, 260.9, 254.8, 137.2, 273.3, 183.4, 326.5, 170.5, 148.2, 124, 135.9, 139.7, 227.2, 291, 143.3, 199.7, 177.9, 174.1, 138.7, 199.3, 146.1, 160.1, 184.6, 155.7, 140, 156, 123.8, 127.4, 226.1, 148, 343.3, 342.1, 151.1, 354.8, 551.4, 251.7, 316.7, 445.4, 258.6, 166.9, 318.4, 250.1, 327.9, 327.3, 420.6, 45.2, 877, 236, 250.8, 57.9, 302.7, 697, 276, 296.4, 182.4, 58.8, 41.7, 25.2, 75.3, 64.4, 52.2, 62.7, 35.5, 51.5, 50.3, 45.1, 35.3, 31.1, 73.8, 90.9, 41.9, 52, 34.1, 107.7, 31.6, 33.1, 19.9, 58, 44.1, 31)), .Names = c("Reg", "Riv", "Hg"), row.names = c(NA, -525L), class = "data.frame")

Can you post a reproducible example. We don't have your data! — mnm, Jun 21 '19 at 09:35
You need to reorder the factor `Riv` levels, not just the `limits` in `scale_x_discrete`. — Rui Barradas, Jun 21 '19 at 09:43
Thanks for sharing your data, please use something along `dput(dtnew)` to share it in a nice reproducible format so that we can easily help you. You can find more ways here [how-to-make-a-great-r-reproducible-example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) — cbo, Jun 21 '19 at 10:02

How to change the order of groups on the x axis without loosing the info of the statistical tests?

0 Answers0