如何重新排序ggplotposition_dodge2barplot中的條形圖？

我有一個資料集，我希望能夠按降序排列其中的條形圖。我已經使用 position_dodge2 來查看每個類別中的子集，但我希望它是按 1. 總體類別（funct_type）和 2. 在這些類別中的降序排列，按 SPP。哦，如果有人有一種超級簡單的方法可以將它們放入（嘗試了一堆不起作用的東西），我也很想包括 y 軸網格線。這是我的資料集：

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))

這是我目前正在運行的代碼：

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")

甚至不知道我會從哪里開始！對于我試過的網格線

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

和

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

兩者都無濟于事！

uj5u.com熱心網友回復：

另一種選擇是按順序排列填充水平frequency。funct_type如果您按最大頻率而不是中值頻率排序，則降低的頻率可能看起來會更好。

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")

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