How to put the significant level above the boxplot using Rstudio, and that this can be seen.

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#1

Hi! I am a beginner in RStudio, and I don't know how to do complex plotting. I would like to make the boxplot the same in this photo. I don't want to manually input all the data. I want to upload it to RStudio as a file.
These are my data comparing 2 groups:

Groups Temperature Humidity NH3 CO2 Dust
Control 24.5 71 5 836.37 37
Control 24.5 62 5 843.00 15
Control 24.5 68 0 860.22 18
Control 24.5 74 0 874.47 37
Control 24.5 75 5 854.26 21
Control 24.5 78 0 856.67 24
Control 24.5 79 0 885.11 45
Control 24.5 81 5 861.77 17
Control 24.5 81 5 845.24 43
Control 24.5 80 5 876.35 17
Control 24.5 80 1 869.74 26
Control 24.5 78 2 922.25 32
Control 24.5 78 5 907.81 77
Control 24.5 75 2 914.46 26
Control 24.5 78 2 888.16 43
Control 25 77 5 858.79 46
Control 25 77 4 884.28 54
Control 24.5 76 0 888.59 18
Control 24.5 79 0 894.50 74
Control 24.5 77 0 889.48 16
Control 25 77 6 918.86 41
Control 25 77 5 946.65 17
Control 25 79 5 962.78 14
Control 25.5 81 0 1006.41 11
Control 25.5 79 0 1003.43 35
Control 25 79 0 993.75 47
Control 25.5 79 4 1058.68 40
Control 25.5 80 10 963.79 5
Treatment 28 73 20 1366.64 41
Treatment 27.5 73 15 1378.89 30
Treatment 27.5 74 20 1430.82 35
Treatment 28.5 75 20 1496.02 45
Treatment 28.5 74 17 1416.31 24
Treatment 28.5 75 22 1441.09 32
Treatment 29 76 20 1487.65 58
Treatment 29.5 76 10 1505.16 26
Treatment 29.5 75 17 1488.01 56
Treatment 30 77 15 1575.61 19
Treatment 30 78 15 1537.48 39
Treatment 29.5 78 13 1560.28 34
Treatment 30 78 25 1586.12 74
Treatment 30 76 25 1519.39 40
Treatment 30 76 23 1523.35 55
Treatment 30.5 77 25 1537.46 54
Treatment 30.5 79 22 1616.99 63
Treatment 30.5 79 18 1636.41 48
Treatment 30.5 81 19 1677.99 89
Treatment 30.5 79 20 1592.36 19
Treatment 30.5 80 25 1653.60 47
Treatment 31 82 15 1763.91 24
Treatment 31 84 20 1875.77 20
Treatment 32 87 25 1940.81 16
Treatment 32 86 30 1869.95 40
Treatment 32 88 20 1857.33 56
Treatment 32.5 86 25 1985.47 58
Treatment 32 90 23 1505.03 17

Thank you for your help!
Boxplot

#2

You can do this sort of thing with the ggsignif package.

library(ggplot2)
library(tidyr)
library(ggsignif)
DF <- read.csv("~/R/Play/Dummy.csv")
DFlng <- DF |> pivot_longer(cols = -Groups, names_to = "Param")
ggplot(DFlng, aes(x = Groups, y = value)) + geom_boxplot() + 
  facet_wrap(~Param, scales = "free_y") +
  geom_signif(comparisons = list(c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment")),
              test = "t.test", textsize = 3)

Created on 2023-07-14 with reprex v2.0.2

#3

Rplot01
Thank you for being so helpful. This is the output. I want to adjust the background color (white), the same as with the picture I posted earlier. Also, I want to adjust the size to make the p-values visible.

#4

Also, I want to add color to the box to distinguish the groups.

#5

You can adjust the spacing below and above the plotted data by adjusting the first and second values in expand = expansion(mult = c(0.05,0.1)). By adjusting that and the textsize argument, you can make the display of the p values pretty. I believe 0.05 is the default value for both bottom and top spacing.
Setting fill = Groups colors the interior of the boxes.
Adding theme_bw() sets a white background.

ggplot(DFlng, aes(x = Groups, y = value, fill = Groups)) + geom_boxplot() + 
  facet_wrap(~Param, scales = "free_y") +
  geom_signif(comparisons = list(c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment"),
                                 c("Control", "Treatment")),
              test = "t.test", textsize = 3) +
  scale_y_continuous(expand = expansion(mult = c(0.05,0.1))) +
  theme_bw()
#6

Thank you very much for your time in helping me. I appreciate it so much.

#7

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