how to reorder bars in ggplot position_dodge2 barplot?-CodePudding

I have a dataset that I would love to be able to arrange the bars in it by descending order. I've used position_dodge2 to be able to look at the subsets within each category, but i want it to be by descending order of both 1. overall category (funct_type) and 2. within those, by SPP. oh i would also love to include y axis gridlines if anybody has a super easy way to put those in (tried a bunch of stuff that didn't work). here is my dataset:

structure(list(identifier = c(1L, 2L, 5L, 6L, 17L, 7L, 4L, 11L, 
20L, 24L, 8L, 18L, 22L, 10L, 15L, 3L, 9L, 13L, 23L, 34L, 14L, 
12L, 16L, 42L, 43L, 30L, 38L, 29L, 33L, 28L, 27L), SPP = c("Penstemon", 
"Rosaceae Group 1", "Saxifraga OR Micranthes OR Boykinia", "Eriogonum", 
"Boykinia OR Saxifraga", "Vaccinium", "Hypericum", "Chamerion OR Epilobium OR Oenothera", 
"Aster Group 2", "Chrysosplenium tetrandum", "Oenothera", "Aster Group 1", 
"Poaceae", "Chamerion", "Luzula", "Abies", "Oxyria digyna", "Pinus", 
"Castilleja", "Erigeron", "Ribes", "Thalictrum", "Salix", "Xerophyllum tenax", 
"Valeriana", "Rhododendron", "Caryophyllaceae", "Sedum lanceolatum", 
"Senecio", "Polygonaceae", "Phrymaceae"), max = c(0.520063568, 
0.479127183, 0.434079314, 0.362801825, 0.217608897, 0.191388889, 
0.717687654, 0.120278432, 0.140414455, 0.078553735, 0.219305556, 
0.437633588, 0.184346498, 0.383032052, 0.178396573, 0.503981446, 
0.263381525, 0.358707915, 0.165725191, 0.046200125, 0.350292287, 
0.644661654, 0.2640831, 0.016758773, 0.021521319, 0.039176109, 
0.031850659, 0.202567022, 0.067327894, 0.20080737, 0.331692794
), readsum = c(6.716942576, 5.503499137, 3.49976764, 2.309000619, 
1.103758598, 1.913782497, 3.798417906, 1.263140584, 0.76553868, 
0.574245876, 1.616440058, 0.866744904, 0.635800875, 1.478810665, 
1.124030263, 3.881683753, 1.59921115, 1.247338241, 0.634873939, 
0.234050052, 1.246069294, 1.262268812, 1.124014166, 0.097837052, 
0.092817485, 0.344979525, 0.183615231, 0.353545529, 0.246583949, 
0.386051108, 0.390301853), funct_type = c("Forb", "Forb", "Forb", 
"Forb", "Forb", "Shrub", "Forb", "Forb", "Forb", "Forb", "Forb", 
"Forb", "Graminoid", "Forb", "Graminoid", "Conifer", "Forb", 
"Conifer", "Forb", "Forb", "Shrub", "Forb", "Shrub", "Forb", 
"Forb", "Shrub", "Forb", "Forb", "Forb", "Forb", "Forb"), frequencyformula = c(52L, 
50L, 47L, 47L, 47L, 46L, 45L, 45L, 45L, 44L, 43L, 43L, 42L, 41L, 
41L, 40L, 40L, 37L, 37L, 36L, 30L, 29L, 29L, 27L, 27L, 25L, 23L, 
22L, 22L, 20L, 18L), frequency = c(1, 0.961538462, 0.903846154, 
0.903846154, 0.903846154, 0.884615385, 0.865384615, 0.865384615, 
0.865384615, 0.846153846, 0.826923077, 0.826923077, 0.807692308, 
0.788461538, 0.788461538, 0.769230769, 0.769230769, 0.711538462, 
0.711538462, 0.692307692, 0.576923077, 0.557692308, 0.557692308, 
0.519230769, 0.519230769, 0.480769231, 0.442307692, 0.423076923, 
0.423076923, 0.384615385, 0.346153846)), class = "data.frame", row.names = c(NA, 
-31L))

and here is the code i am currently running:

top32freq%>%
  ggplot(aes(x=reorder(funct_type, frequency), y=frequency))   
  geom_bar(aes(fill=SPP),position=position_dodge2(width = .9, preserve = "single"), stat="identity", color="black") 
  coord_cartesian(ylim=c(.3,1))  
  ylab("Frequency across samples") 
  xlab("functional plant types") 
  ggtitle("Diet Frequency by Functional Type") 
  theme_classic() scale_fill_viridis_d() 
  theme(axis.title = element_text(size = 16, face = "bold", family = "Caladea"),
        strip.text.y = element_text(size = 18, face="bold", family = "Caladea"),
        plot.title = element_text(size = 28, face = "bold", family = "Caladea", hjust = 0.5),
        axis.text = element_text(size = 18, face = "bold", family = "Caladea")
  )  theme(legend.position="none")

don't even know where i would start! for gridlines i tried

 scale_y_continuous(limits = c(0.4, 1), breaks = seq(0.4,1))

and

 
  grids(axis = c("y"), color = "grey92", size = 1, linetype = solid)

both to no avail!

CodePudding user response：

Another option is to arrange your fill levels in order of frequency. The decreasing frequency will probably look better if you order funct_type by the maximum, rather than median, frequency.

top32freq %>%
  mutate(funct_type = fct_reorder(.f = funct_type, .x = -frequency, min)) %>%
  ggplot(aes(x = funct_type, y = frequency))   
  geom_col(aes(fill = reorder(SPP, -frequency)),color = "black",
               position = position_dodge2(width = .9, preserve = "single"))  
  coord_cartesian(ylim = c(.3,1))  
  ylab("Frequency across samples")  
  xlab("functional plant types")  
  ggtitle("Diet Frequency by Functional Type")  
  theme_bw()  
  scale_fill_viridis_d()  
  theme(axis.title = element_text(size = 16, face = 2, family = "Caladea"),
        strip.text.y = element_text(size = 18, face = 2, family = "Caladea"),
        plot.title = element_text(size = 28, face = 2, family = "Caladea", 
                                  hjust = 0.5),
        axis.text = element_text(size = 18, face = 2, family = "Caladea"),
        legend.position = "none")