How do you ignore the "NS" and just show those which are significantly different?

Hello everyone, I have a question regarding the statistical functionality applied in this boxplot. Is there any way I can only represent the graphs that have significant differences (***, **, *), I'm not interested in those that have no significant difference (NS), and I would like to eliminate that indication (NS.), In addition to this infringement (NS.) Does not make the graphics look good.

SCRIPT:

#Comparación por punto de muestreo
# Sample data on a copy/paste friendly format
rm(list = ls())
metadata <- data.frame(stringsAsFactors=FALSE,
                       SampleID = c("1A", "1B", "1C", "1D", "1E", "1F", "1G", "1H", "2A",
                                    "2B", "2C", "2D", "2E", "2F", "2G", "2H", "3A", "3B",
                                    "3C", "3D", "3E", "3F", "3G", "3H", "4A", "4B", "4C",
                                    "4D", "4E", "4F", "4G", "4H", "5A", "5B", "5C", "5D",
                                    "5E", "5F", "5G", "5H", "6A", "6B", "6C", "6D", "6E", "6F",
                                    "6G", "6H", "7A", "7B", "7C", "7D", "7E", "7F", "7G",
                                    "7H", "8A", "8B", "8C", "8D", "8E", "8F", "8G", "8H",
                                    "9A", "9B", "9C", "9D", "9E", "9F", "9G", "9H", "10A",
                                    "10B", "10C", "10D", "10E", "10F", "10G", "10H", "11A",
                                    "11B", "11C", "11D", "11E", "11F", "11G", "11H", "12A",
                                    "12B", "12C", "12D", "12E", "12F", "12G", "12H"),
                       SamplingPoint = c("CAJ-1", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5",
                                         "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-2", "CAJ-4", "CAJ-1",
                                         "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-2",
                                         "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4",
                                         "CAJ-1", "CAJ-3", "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5",
                                         "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-4", "CAJ-1", "CAJ-3",
                                         "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5",
                                         "CAJ-1", "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1",
                                         "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-3",
                                         "CAJ-5", "CAJ-1", "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4",
                                         "CAJ-1", "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-3", "CAJ-5", "CAJ-2",
                                         "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-3",
                                         "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-3", "CAJ-5",
                                         "CAJ-2", "CAJ-4", "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1",
                                         "CAJ-3", "CAJ-5", "CAJ-2", "CAJ-4", "CAJ-1", "CAJ-2", "CAJ-4",
                                         "CAJ-1", "CAJ-3", "CAJ-5"),
                       Depth = c("80 cm", "80 cm", "Interstitial", "80 cm", "80 cm",
                                 "80 cm", "80 cm", "80 cm", "80 cm", "Interstitial",
                                 "Interstitial", "80 cm", "80 cm", "80 cm", "80 cm",
                                 "80 cm", "Interstitial", "Interstitial", "80 cm",
                                 "Interstitial", "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "Interstitial", "80 cm", "Interstitial",
                                 "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "Interstitial", "80 cm", "80 cm", "Interstitial",
                                 "80 cm", "80 cm", "80 cm", "80 cm", "80 cm", "80 cm",
                                 "Interstitial", "80 cm", "80 cm", "Interstitial",
                                 "Interstitial", "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "80 cm", "80 cm", "80 cm", "80 cm",
                                 "80 cm", "80 cm", "Interstitial", "80 cm", "Interstitial",
                                 "80 cm", "80 cm", "80 cm", "80 cm", "80 cm", "80 cm",
                                 "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "Interstitial", "Interstitial", "Interstitial",
                                 "80 cm", "Interstitial", "80 cm", "Interstitial",
                                 "Interstitial", "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "80 cm", "Interstitial", "80 cm", "80 cm",
                                 "80 cm", "80 cm", "80 cm", "Interstitial", "80 cm",
                                 "Interstitial", "Interstitial", "Interstitial",
                                 "Interstitial", "Interstitial", "Interstitial"),
                       Month = c("July", "July", "July", "August", "August", "August",
                                 "September", "September", "July", "July", "July",
                                 "August", "August", "August", "September", "September",
                                 "July", "July", "July", "August", "August", "August",
                                 "September", "September", "July", "July", "July", "August",
                                 "August", "August", "September", "September", "July",
                                 "July", "July", "August", "August", "August", "September",
                                 "September", "July", "July", "July", "August", "August",
                                 "August", "September", "September", "July", "July",
                                 "July", "August", "August", "September", "September",
                                 "September", "July", "July", "July", "August", "August",
                                 "September", "September", "September", "July", "July",
                                 "July", "August", "August", "September", "September",
                                 "September", "July", "July", "July", "August", "August",
                                 "September", "September", "September", "July", "July", "July",
                                 "August", "August", "September", "September",
                                 "September", "July", "July", "August", "August", "August",
                                 "September", "September", "September"),
                       Filter = c("20-25 um", "0.45 um", "20-25 um", "20-25 um",
                                  "20-25 um", "20-25 um", "20-25 um", "20-25 um",
                                  "0.45 um", "20-25 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "20-25 um", "0.45 um",
                                  "0.45 um", "20-25 um", "20-25 um", "20-25 um", "20-25 um",
                                  "20-25 um", "0.45 um", "20-25 um", "20-25 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "0.45 um", "20-25 um",
                                  "0.45 um", "0.45 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "20-25 um", "20-25 um",
                                  "20-25 um", "0.45 um", "0.45 um", "0.45 um", "0.45 um",
                                  "20-25 um", "0.45 um", "0.45 um", "20-25 um", "20-25 um",
                                  "20-25 um", "20-25 um", "20-25 um", "0.45 um",
                                  "0.45 um", "20-25 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "20-25 um", "20-25 um", "0.45 um",
                                  "20-25 um", "20-25 um", "20-25 um", "20-25 um", "20-25 um",
                                  "0.45 um", "0.45 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "20-25 um", "20-25 um",
                                  "20-25 um", "0.45 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "0.45 um", "0.45 um",
                                  "0.45 um", "0.45 um", "0.45 um", "0.45 um"),
                       SampleorReplica = c("Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Sample", "Sample", "Sample", "Replica",
                                           "Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Replica", "Sample", "Replica", "Replica", "Replica",
                                           "Replica", "Replica", "Replica", "Replica", "Sample", "Sample",
                                           "Replica", "Replica", "Replica", "Replica", "Replica",
                                           "Replica", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Sample", "Replica", "Replica", "Sample",
                                           "Sample", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Replica", "Sample", "Sample", "Sample", "Sample",
                                           "Sample", "Sample", "Replica", "Replica", "Replica",
                                           "Sample", "Sample", "Sample", "Sample", "Sample", "Replica",
                                           "Sample", "Replica", "Replica", "Replica", "Replica",
                                           "Replica", "Replica", "Replica", "Replica", "Replica",
                                           "Replica", "Replica", "Replica", "Replica", "Replica"),
                       DO = c(4.24, 2.58, 2.85, 3.81, 2.64, 4.61, 5.74, 3.69, 4.24,
                              2.66, 2.85, 3.81, 2.64, 4.61, 5.74, 3.69, 2.51, 2.66,
                              3.14, 2.92, 1.83, 1.82, 3.02, 3.3, 2.51, 3.04, 2.85,
                              2.92, 1.83, 1.82, 3.02, 3.3, 4.24, 3.04, 2.85, 3.81, 2.64,
                              4.61, 5.74, 3.69, 4.24, 2.09, 2.98, 3.81, 1.83, 1.82,
                              3.02, 3.3, 2.51, 2.09, 2.98, 8.17, 2.63, 7.69, 3.07, 3.7,
                              2.51, 3.04, 2.18, 8.17, 2.63, 7.69, 3.07, 3.7, 2.58,
                              2.09, 2.18, 2.16, 1.7, 6.8, 1.95, 4.28, 2.58, 2.09, 2.98,
                              2.16, 1.7, 6.8, 1.95, 4.28, 2.66, 3.14, 2.18, 8.17, 2.63,
                              7.69, 3.07, 3.7, 2.66, 3.14, 2.92, 2.16, 1.7, 6.8,
                              1.95, 4.28),
                       pH = c(9.94, 10.06, 9.98, 9.07, 8.99, 8.93, 9.24, 9.32, 9.94,
                              10, 9.98, 9.07, 8.99, 8.93, 9.24, 9.32, 10.04, 10, 10,
                              9.06, 8.99, 8.92, 9.18, 9.32, 10.04, 9.96, 9.98, 9.06,
                              8.99, 8.92, 9.18, 9.32, 9.94, 9.96, 9.98, 9.07, 8.99,
                              8.93, 9.24, 9.32, 9.94, 9.95, 10.09, 9.07, 8.99, 8.92,
                              9.18, 9.32, 10.04, 9.95, 10.09, 9.04, 9, 9.53, 9.31, 9.14,
                              10.04, 9.96, 9.97, 9.04, 9, 9.53, 9.31, 9.14, 10.06,
                              9.95, 9.97, 8.96, 9.02, 9.51, 9.39, 8.85, 10.06, 9.95,
                              10.09, 8.96, 9.02, 9.51, 9.39, 8.85, 10, 10, 9.97, 9.04, 9,
                              9.53, 9.31, 9.14, 10, 10, 9.06, 8.96, 9.02, 9.51, 9.39,
                              8.85),
                       Temperature = c(24.48, 24.95, 24.01, 26.67, 24.01, 23.5, 24.46, 24.65,
                                       24.48, 24.92, 24.01, 26.67, 24.01, 23.5, 24.46, 24.65,
                                       24.35, 24.92, 24, 26.46, 23.99, 23.43, 24.14, 24.67,
                                       24.35, 24.04, 24.01, 26.46, 23.99, 23.43, 24.14, 24.67,
                                       24.48, 24.04, 24.01, 26.67, 24.01, 23.5, 24.46, 24.65,
                                       24.48, 24.01, 24.36, 26.67, 23.99, 23.43, 24.14, 24.67,
                                       24.35, 24.01, 24.36, 24.88, 24.7, 26.14, 24.19, 22.65,
                                       24.35, 24.04, 24.4, 24.88, 24.7, 26.14, 24.19, 22.65, 24.95,
                                       24.01, 24.4, 24.3, 24.72, 26.15, 23.9, 20.65, 24.95,
                                       24.01, 24.36, 24.3, 24.72, 26.15, 23.9, 20.65, 24.92, 24,
                                       24.4, 24.88, 24.7, 26.14, 24.19, 22.65, 24.92, 24,
                                       26.46, 24.3, 24.72, 26.15, 23.9, 20.65),
                       Turbidity = c(87.3, 95.2, 98.8, 24.9, 43.1, 49.1, 68.6, 69.8, 87.3,
                                     113, 98.8, 24.9, 43.1, 49.1, 68.6, 69.8, 87.7, 113,
                                     96.9, 39.7, 49, 47.6, 66.6, 74.1, 87.7, 98.5, 98.8, 39.7,
                                     49, 47.6, 66.6, 74.1, 87.3, 98.5, 98.8, 24.9, 43.1,
                                     49.1, 68.6, 69.8, 87.3, 95.9, 97.2, 24.9, 49, 47.6, 66.6,
                                     74.1, 87.7, 95.9, 97.2, 46.9, 37.2, 74.2, 69.9, 71.3,
                                     87.7, 98.5, 100.6, 46.9, 37.2, 74.2, 69.9, 71.3, 95.2, 95.9,
                                     100.6, 42, 36.1, 74.4, 44.4, 71.3, 95.2, 95.9, 97.2,
                                     42, 36.1, 74.4, 44.4, 71.3, 113, 96.9, 100.6, 46.9, 37.2,
                                     74.2, 69.9, 71.3, 113, 96.9, 39.7, 42, 36.1, 74.4, 44.4,
                                     71.3),
                       ORP = c(97, 108.4, 102.9, 94, 63.9, 64.7, 40.3, 48.1, 97,
                               111.9, 102.9, 94, 63.9, 64.7, 40.3, 48.1, 91.3, 111.9,
                               108, 23.7, 64.1, 60.4, 40.6, 49.8, 91.3, 98.9, 102.9,
                               23.7, 64.1, 60.4, 40.6, 49.8, 97, 98.9, 102.9, 94, 63.9,
                               64.7, 40.3, 48.1, 97, 92.8, 106.9, 94, 64.1, 60.4, 40.6,
                               49.8, 91.3, 92.8, 106.9, 90.4, 74.9, 67.7, 42, 37.1,
                               91.3, 98.9, 102.7, 90.4, 74.9, 67.7, 42, 37.1, 108.4,
                               92.8, 102.7, 53, 63.4, 73.9, 42, 37.5, 108.4, 92.8, 106.9,
                               53, 63.4, 73.9, 42, 37.5, 111.9, 108, 102.7, 90.4, 74.9,
                               67.7, 42, 37.1, 111.9, 111.9, 23.7, 53, 63.4, 73.9, 42,
                               37.5),
                       Ammonium = c(4.46, 4.62, 4.37, 5.6, 3.38, 3.21, 1.93, 2.21, 4.46,
                                    4.75, 4.37, 5.6, 3.38, 3.21, 1.93, 2.21, 4.5, 4.75,
                                    4.48, 7.64, 3.18, 3.09, 2.19, 2.14, 4.5, 3.97, 4.37, 7.64,
                                    3.18, 3.09, 2.19, 2.14, 4.46, 3.97, 4.37, 5.6, 3.38,
                                    3.21, 1.93, 2.21, 4.46, 4.06, 4.43, 5.6, 3.18, 3.09, 2.19,
                                    2.14, 4.5, 4.06, 4.43, 2.81, 4.2, 4.5, 1.99, 2.07, 4.5,
                                    3.97, 5.47, 2.81, 4.2, 4.5, 1.99, 2.07, 4.62, 4.06,
                                    5.47, 3.19, 3.97, 3.3, 3.38, 1.18, 4.62, 4.06, 4.43, 3.19,
                                    3.97, 3.3, 3.38, 1.18, 4.75, 4.48, 5.47, 2.81, 4.2, 4.5,
                                    1.99, 2.07, 4.75, 4.48, 7.64, 3.19, 3.97, 3.3, 3.38,
                                    1.18),
                       Nitrates = c(3.6, 3.98, 3.57, 3.53, 2.55, 2.28, 0.71, 1.2, 3.6,
                                    3.21, 3.57, 3.53, 2.55, 2.28, 0.71, 1.2, 3.36, 3.21,
                                    3.76, 3.66, 2.44, 2.06, 0.67, 0.87, 3.36, 4.35, 3.57,
                                    3.66, 2.44, 2.06, 0.67, 0.87, 3.6, 4.35, 3.57, 3.53, 2.55,
                                    2.28, 0.71, 1.2, 3.6, 3.68, 3.34, 3.53, 2.44, 2.06,
                                    0.67, 0.87, 3.36, 3.68, 3.34, 2.25, 2.99, 1.3, 0.74, 0.68,
                                    3.36, 4.35, 4.11, 2.25, 2.99, 1.3, 0.74, 0.68, 3.98,
                                    3.68, 4.11, 2.1, 2.55, 1.11, 0.69, 0.69, 3.98, 3.68, 3.34,
                                    2.1, 2.55, 1.11, 0.69, 0.69, 3.21, 3.76, 4.11, 2.25,
                                    2.99, 1.3, 0.74, 0.68, 3.21, 3.76, 3.66, 2.1, 2.55, 1.11,
                                    0.69, 0.69),
                       BGA = c(279133, 279113, 265304, 11603, 218471, 226658, 267389,
                               267144, 279133, 270193, 265304, 11603, 218471, 226658,
                               267389, 267144, 267716, 270193, 279119, 66608, 213497,
                               242331, 267007, 261363, 267716, 279109, 265304, 66608,
                               213497, 242331, 267007, 261363, 279133, 279109, 265304,
                               11603, 218471, 226658, 267389, 267144, 279133, 279100,
                               279099, 11603, 213497, 242331, 267007, 261363, 267716,
                               279100, 279099, 246979, 169175, 272332, 269519, 272096,
                               267716, 279109, 278137, 246979, 169175, 272332, 269519,
                               272096, 279113, 279100, 278137, 174271, 159046, 271503,
                               261124, 271303, 279113, 279100, 279099, 174271, 159046,
                               271503, 261124, 271303, 270193, 279119, 278137, 246979,
                               169175, 272332, 269519, 272096, 270193, 279119, 66608,
                               174271, 159046, 271503, 261124, 271303),
                       Chlrophyll = c(36.6, 38.9, 40, 44, 35, 32.8, 44, 44.8, 36.6, 39.8,
                                      40, 44, 35, 32.8, 44, 44.8, 39.6, 39.8, 38.5, 45.1,
                                      42.2, 50.2, 43.6, 45.1, 39.6, 43, 40, 45.1, 42.2, 50.2,
                                      43.6, 45.1, 36.6, 43, 40, 44, 35, 32.8, 44, 44.8, 36.6,
                                      50, 43, 44, 42.2, 50.2, 43.6, 45.1, 39.6, 50, 43, 34,
                                      38.4, 58.5, 44.3, 40, 39.6, 43, 53.8, 34, 38.4, 58.5, 44.3,
                                      40, 38.9, 50, 53.8, 50.3, 55.9, 51.3, 68.2, 34.2, 38.9,
                                      50, 43, 50.3, 55.9, 51.3, 68.2, 34.2, 39.8, 38.5, 53.8,
                                      34, 38.4, 58.5, 44.3, 40, 39.8, 38.5, 45.1, 50.3, 55.9,
                                      51.3, 68.2, 34.2)
)

library(tidyverse)
library(ggplot2)
library(ggsignif)

metadata$SamplingPoint <- factor(metadata$SamplingPoint,labels = c("1","2","3","4","5"))

#Comparación por punto de muestreo
metadata %>% 
  select(SamplingPoint, DO:Chlrophyll) %>% 
  gather(Parameter, Value, -SamplingPoint) %>% 
  ggplot(aes(SamplingPoint, Value, fill = SamplingPoint)) +
  geom_boxplot ()+
  geom_signif(comparisons = list(c("1", "2")),
              map_signif_level=TRUE,
              margin_top = 0.05)+
  geom_signif(comparisons = list(c("1", "3")),
              map_signif_level=TRUE,
              margin_top = 0.2)+
  geom_signif(comparisons = list(c("1", "4")),
              map_signif_level=TRUE,
              margin_top = 0.4)+
  geom_signif(comparisons = list(c("1", "5")),
              map_signif_level=TRUE,
              margin_top = 0.6)+
  geom_signif(comparisons = list(c("2", "3")),
              map_signif_level=TRUE,
              margin_top = 0.8)+
  geom_signif(comparisons = list(c("2", "4")),
              map_signif_level=TRUE,
              margin_top = 1)+
  geom_signif(comparisons = list(c("2", "5")),
                map_signif_level=TRUE,
                margin_top = 2)+
  geom_signif(comparisons = list(c("3", "4")),
                map_signif_level=TRUE,
                margin_top = 3)+
  geom_signif(comparisons = list(c("3", "5")),
                map_signif_level=TRUE,
                margin_top = 4)+
  geom_signif(comparisons = list(c("4", "5")),
                map_signif_level=TRUE,
                margin_top = 5)+
  geom_boxplot(show.legend = FALSE) +
  facet_wrap(~Parameter, scales = "free_y") +
  scale_y_continuous(expand = c(0.2,0.2))+
  theme_bw()+
  theme(panel.grid.major = element_line(colour = "white"),
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        plot.title = element_text(hjust = 0.5, size = 14, family = "Tahoma", face = "bold"),
        text=element_text(family = "Tahoma", face ="bold"),
        axis.title = element_text(face="bold"),
        axis.text.x = element_text(colour="black", size = 11),
        axis.text.y = element_text(colour="black", size = 9),
        axis.line = element_line(size=0.5, colour = "black"))

modify the option map_signif_level inside the geom_signif as example below

geom_signif(comparisons = list(c("1", "2")),
                    map_signif_level=c("***"=0.001,"**"=0.01, "*"=0.05, " "=2),
                    margin_top = 0.05)

Thank you for your suggestion, but I had already done that. The problem now is that I cannot delete the lines, I don't want the lines and the indication (NS).

I read this example online, but I didn't know how to apply it in my analysis.

I see.

The only way I can think about is following the example on the github page, i.e., setting up annotation_df manually.

https://github.com/const-ae/ggsignif

Hi,

I have been working on this a bit, and was able to get rid of non-significant pairs by creating a custom function for the map_signif_level based on the p-value. It says in the documentation this is possible and thus I replaced non-significant results with NA, thereby removing those bars

sigFunc = function(x){
  if(x < 0.001){"***"} 
  else if(x < 0.01){"**"}
  else if(x < 0.05){"*"}
  else{NA}}

#Comparación por punto de muestreo
metadata %>% 
  select(SamplingPoint, DO:Chlrophyll) %>% 
  gather(Parameter, Value, -SamplingPoint) %>% 
  ggplot(aes(SamplingPoint, Value, fill = SamplingPoint)) +
  geom_boxplot ()+
  geom_signif(comparisons = list(c("1", "2")),
              map_signif_level= sigFunc,
              margin_top = 0.05)+
  geom_signif(comparisons = list(c("1", "3")),
              map_signif_level=sigFunc,
              margin_top = 0.2)+
  geom_signif(comparisons = list(c("1", "4")),
              map_signif_level=sigFunc,
              margin_top = 0.4)+
  geom_signif(comparisons = list(c("1", "5")),
              map_signif_level=sigFunc,
              margin_top = 0.6)+
  geom_signif(comparisons = list(c("2", "3")),
              map_signif_level=sigFunc,
              margin_top = 0.8)+
  geom_signif(comparisons = list(c("2", "4")),
              map_signif_level=sigFunc,
              margin_top = 1)+
  geom_signif(comparisons = list(c("2", "5")),
              map_signif_level=sigFunc,
              margin_top = 2)+
  geom_signif(comparisons = list(c("3", "4")),
              map_signif_level=sigFunc,
              margin_top = 3)+
  geom_signif(comparisons = list(c("3", "5")),
              map_signif_level=sigFunc,
              margin_top = 4)+
  geom_signif(comparisons = list(c("4", "5")),
              map_signif_level=sigFunc,
              margin_top = 5)+
  geom_boxplot(show.legend = FALSE) +
  facet_wrap(~Parameter, scales = "free_y") +
  scale_y_continuous(expand = c(0.2,0.2))+
  theme_bw()+
  theme(panel.grid.major = element_line(colour = "white"),
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        plot.title = element_text(hjust = 0.5, size = 14, family = "Tahoma", face = "bold"),
        text=element_text(family = "Tahoma", face ="bold"),
        axis.title = element_text(face="bold"),
        axis.text.x = element_text(colour="black", size = 11),
        axis.text.y = element_text(colour="black", size = 9),
        axis.line = element_line(size=0.5, colour = "black"))


Unfortunately, although not displaying the bars, the plot still remembers their position and thus a lot of empty space is created that prevents the boxplots from using all white space... I can't seem to be able to alter this as this is generated by the margin_top argument and I can't get it to be responsive to the value of map_signif_level.

So a small step in the right direction, but not a full solution yet :slight_smile:

Hope this helps,
PJ

2 Likes

Thank you very much for your help. I made the decision to present my results without that analysis in those graphs, due to what you comment. The value of the Y for each parameter is lost. I will better present that statistic in a table with only the significant variables, comparing it with the graphs.

Have a good day!!

O.

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