Question

我正在尝试使用ggplot在R中创建一个图表，并且我需要一个图例来描述不同的文本标签。数据集（pfdavar）如下：

pfdavar <- read.table(header=TRUE,row.names=1,text="
Scientific_Name X1  X2  Function    Labels  Species
Accipiter_gentilis1 -4.89789193 -4.647159032    Carnivore   1   Accipiter_gentilis
Accipiter_gentilis2 -4.85572869 -4.136258682    Carnivore   1   Accipiter_gentilis
Accipiter_gentilis3 -4.53679492 -1.800944748    Carnivore   1   Accipiter_gentilis
Accipiter_gentilis4 -6.09443847 -0.959612873    Carnivore   1   Accipiter_gentilis
Accipiter_gentilis5 -6.05461651 -4.960788555    Carnivore   1   Accipiter_gentilis
Acciptiter_nisus1   -3.41413514 -0.895822312    Carnivore   2   Accipiter_nisus
Acciptiter_nisus2   -3.19652756 -0.888246165    Carnivore   2   Accipiter_nisus
Acciptiter_nisus3   -3.12483784 -0.999500166    Carnivore   2   Accipiter_nisus
Acciptiter_nisus4   -2.66618148 -2.960531036    Carnivore   2   Accipiter_nisus
Acciptiter_nisus5   -3.54795755 -2.818834269    Carnivore   2   Accipiter_nisus
Acciptiter_nisus6   -3.25976501 -2.356532832    Carnivore   2   Accipiter_nisus
Acciptiter_nisus7   -3.37935944 -1.968577396    Carnivore   2   Accipiter_nisus
Acciptiter_nisus8   -3.0595512  -2.562750671    Carnivore   2   Accipiter_nisus
Acciptiter_nisus9   -3.27594514 -1.773717162    Carnivore   2   Accipiter_nisus
Acciptiter_nisus10  -3.28664004 -2.111224987    Carnivore   2   Accipiter_nisus
Aix_sponsa1 -1.4390108  1.536380546 Omnivore    3   Aix_sponsa
Aix_sponsa2 -2.17774592 1.419977832 Omnivore    3   Aix_sponsa
Aix_sponsa3 -0.73377916 1.652091362 Omnivore    3   Aix_sponsa
Aix_sponsa4 -0.68365602 1.748682677 Omnivore    3   Aix_sponsa
Aix_sponsa5 -1.02730778 1.868245903 Omnivore    3   Aix_sponsa
Aix_sponsa6 -1.37813364 1.974331359 Omnivore    3   Aix_sponsa
Aix_sponsa7 -0.74135489 1.427638468 Omnivore    3   Aix_sponsa
Aix_sponsa8 -0.58858907 1.004532252 Omnivore    3   Aix_sponsa
Aix_sponsa9 -1.1451094  1.769762482 Omnivore    3   Aix_sponsa
Aix_sponsa10    -1.28796936 1.929869081 Omnivore    3   Aix_sponsa
Anas_crecca1    -1.35096092 1.419587444 Omnivore    4   Anas_crecca
Anas_crecca2    -1.15412046 1.551324297 Omnivore    4   Anas_crecca
Anas_crecca3    -0.46402248 1.09274552  Omnivore    4   Anas_crecca
Anas_crecca4    -0.45462158 1.766419599 Omnivore    4   Anas_crecca
Anas_crecca5    0.13085385  1.373888208 Omnivore    4   Anas_crecca
Anas_crecca6    -0.25686211 2.229749359 Omnivore    4   Anas_crecca
Anas_crecca7    -0.9650909  1.296567761 Omnivore    4   Anas_crecca
Anas_crecca8    -1.26040491 1.981659794 Omnivore    4   Anas_crecca
Anas_crecca9    -1.03942764 1.489003168 Omnivore    4   Anas_crecca
Anas_crecca10   -0.97216996 1.336046865 Omnivore    4   Anas_crecca
Apus_apus1  1.88334138  -0.100251918    Insectivore 5   Apus_apus
Apus_apus2  0.75592041  -0.934233835    Insectivore 5   Apus_apus
Apus_apus3  0.71275049  -1.327860015    Insectivore 5   Apus_apus
Apus_apus4  1.1990241   0.399503737 Insectivore 5   Apus_apus
Apus_apus5  2.14285406  0.39050903  Insectivore 5   Apus_apus
Apus_apus6  2.26623205  1.082865398 Insectivore 5   Apus_apus
Apus_apus7  2.19534512  1.170083188 Insectivore 5   Apus_apus
Apus_apus8  1.82943832  0.353572547 Insectivore 5   Apus_apus
Apus_apus9  1.32492464  -0.005098561    Insectivore 5   Apus_apus
Apus_apus10 3.33227261  -0.172660264    Insectivore 5   Apus_apus
Branta_bernicla1    -2.59541115 0.403284268 Graminivore 6   Branta_bernicla
Branta_bernicla2    -2.29101252 0.518276194 Graminivore 6   Branta_bernicla
Branta_bernicla3    -3.75432432 1.051798493 Graminivore 6   Branta_bernicla
Branta_bernicla4    -2.46565059 0.450162234 Graminivore 6   Branta_bernicla
Branta_bernicla5    -2.27965667 -0.298584584    Graminivore 6   Branta_bernicla
Branta_bernicla6    -2.52807499 0.221669554 Graminivore 6   Branta_bernicla
Branta_bernicla7    -3.19899834 -0.439541025    Graminivore 6   Branta_bernicla
Branta_bernicla8    -2.9235117  0.835465853 Graminivore 6   Branta_bernicla
Branta_bernicla9    -2.1349146  -0.461085227    Graminivore 6   Branta_bernicla
Branta_bernicla10   -2.72727687 0.858812955 Graminivore 6   Branta_bernicla
Branta_canadensis1  -2.61921103 0.197699691 Graminivore 7   Branta_canadensis
Branta_canadensis2  -1.84266453 -1.407186966    Graminivore 7   Branta_canadensis
Branta_canadensis3  -2.29562301 -0.538735389    Graminivore 7   Branta_canadensis
Branta_canadensis4  -1.57554385 0.566449848 Graminivore 7   Branta_canadensis
Bucephala_islandica1    -2.81886145 2.917895842 Omnivore    8   Bucephala_islandica
Bucephala_islandica2    -2.04171303 2.417351605 Omnivore    8   Bucephala_islandica
Bucephala_islandica3    -3.63391644 2.565876003 Omnivore    8   Bucephala_islandica
Bucephala_islandica4    -2.76309326 2.485341013 Omnivore    8   Bucephala_islandica
Bucephala_islandica5    -2.9319585  3.029284674 Omnivore    8   Bucephala_islandica
Caprimulgus_climacurus1 2.97008877  -0.649580557    Insectivore 9   Caprimulgus_climacurus
Caprimulgus_climacurus2 4.39486789  -0.729532552    Insectivore 9   Caprimulgus_climacurus
Caprimulgus_climacurus3 4.5143613   -0.226964193    Insectivore 9   Caprimulgus_climacurus
Caprimulgus_europaeus1  5.44615841  -1.021666961    Insectivore 10  Caprimulgus_europaeus
Caprimulgus_europaeus2  5.02364267  -0.890099077    Insectivore 10  Caprimulgus_europaeus
Caprimulgus_europaeus3  5.21067804  -1.578068157    Insectivore 10  Caprimulgus_europaeus
Clanga_clanga1  -4.29958313 -4.522075437    Carnivore   11  Clanga_clanga
Clanga_clanga2  -5.39490832 -4.828912341    Carnivore   11  Clanga_clanga
Clanga_pomarina1    -4.38077048 -2.784564708    Carnivore   12  Clanga_pomarina
Clanga_pomarina2    -4.6561379  -4.252797443    Carnivore   12  Clanga_pomarina
Clanga_pomarina3    -5.48538959 -3.579093142    Carnivore   12  Clanga_pomarina
Delichon_urbicum1   2.2925  0.430657351 Insectivore 13  Delichon_urbicum
Delichon_urbicum2   1.54099519  1.459719746 Insectivore 13  Delichon_urbicum
Delichon_urbicum3   0.99773878  0.274581581 Insectivore 13  Delichon_urbicum
Delichon_urbicum4   1.24467923  1.236789373 Insectivore 13  Delichon_urbicum
Delichon_urbicum5   0.53504479  0.154682421 Insectivore 13  Delichon_urbicum
Delichon_urbicum6   1.53214527  0.91890228  Insectivore 13  Delichon_urbicum
Delichon_urbicum7   1.49818001  1.089675735 Insectivore 13  Delichon_urbicum
Delichon_urbicum8   0.67390299  0.753096969 Insectivore 13  Delichon_urbicum
Delichon_urbicum9   1.93683118  0.918165987 Insectivore 13  Delichon_urbicum
Delichon_urbicum10  1.58513146  1.564374345 Insectivore 13  Delichon_urbicum
Hirundo_rustica1    2.62925523  1.651726581 Insectivore 14  Hirundo_rustica
Hirundo_rustica2    2.14444347  2.273743756 Insectivore 14  Hirundo_rustica
Hirundo_rustica3    2.44316384  1.305086968 Insectivore 14  Hirundo_rustica
Hirundo_rustica4    3.15948914  1.458235727 Insectivore 14  Hirundo_rustica
Hirundo_rustica5    2.45355055  1.365638627 Insectivore 14  Hirundo_rustica
Hirundo_rustica6    3.06169729  1.275884535 Insectivore 14  Hirundo_rustica
Hirundo_rustica7    2.38793666  1.636555833 Insectivore 14  Hirundo_rustica
Hirundo_rustica8    2.66767101  0.645046239 Insectivore 14  Hirundo_rustica
Hirundo_rustica9    3.71351475  1.661709624 Insectivore 14  Hirundo_rustica
Hirundo_rustica10   2.93209807  0.734178456 Insectivore 14  Hirundo_rustica
Mergus_merganser1   0.29942933  -2.433390971    Piscivore   15  Mergus_merganser
Mergus_merganser2   0.98081612  -2.572393002    Piscivore   15  Mergus_merganser
Mergus_merganser3   0.72001717  -2.569943671    Piscivore   15  Mergus_merganser
Mergus_merganser4   0.46411239  -2.786791001    Piscivore   15  Mergus_merganser
Mergus_merganser5   -0.44219165 -1.601086246    Piscivore   15  Mergus_merganser
Mergus_merganser6   -0.46454582 -1.360541224    Piscivore   15  Mergus_merganser
Mergus_merganser7   -1.15574664 -2.601269214    Piscivore   15  Mergus_merganser
Mergus_merganser8   0.16982656  -2.97723875 Piscivore   15  Mergus_merganser
Spatula_clypeata1   6.07310551  -2.358533867    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata2   7.22049562  -3.37755176 Filter-feeder   16  Spatula_clypeata
Spatula_clypeata3   6.50789136  -2.300145446    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata4   5.47730013  -2.176186104    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata5   5.53559984  -2.405227327    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata6   7.97963585  -2.70056017 Filter-feeder   16  Spatula_clypeata
Spatula_clypeata7   6.71942913  -1.932583426    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata8   5.81775012  -2.058246029    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata9   7.20591453  -2.997222777    Filter-feeder   16  Spatula_clypeata
Spatula_clypeata10  8.01402202  -3.384188559    Filter-feeder   16  Spatula_clypeata
Tachymarptis_melba1 4.93212078  -0.758952678    Insectivore 17  Tachymarptis_melba
Tadorna_tadorna1    -1.03512249 4.286499709 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna2    0.45753486  3.348021245 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna3    0.08608732  4.270813056 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna4    -1.43964831 3.38875373  Omnivore    18  Tadorna_tadorna
Tadorna_tadorna5    -0.96090197 4.416417469 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna6    -0.40120783 3.807289885 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna7    -0.90882097 4.452652604 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna8    -0.4036924  4.103030427 Omnivore    18  Tadorna_tadorna
Tadorna_tadorna9    -0.46248229 4.198274967 Omnivore    18  Tadorna_tadorna
")

我正在使用的代码如下所示：

library(ggplot2)
library(dplyr)
groups<-pfdavar$Function
labels<-pfdavar$Labels
species<-pfdavar$Species
find_hull <- function(df) df[chull(df$X1, df$X2), ]
hulls <- plyr::ddply(pfdavar, "groups", find_hull)
pfda_plot <- ggplot(data=pfdavar,aes(x=X1,y=X2,group=groups))+
  geom_point(aes(colour=groups))+
  geom_polygon(data=hulls,alpha=0.2,aes(fill=groups))+
  xlab("pFDA1")+
  ylab("pFDA2")+
  geom_text(aes(label=labels,fontface=1),hjust=0,vjust=0,size=3)+
  theme_classic()+
  theme(legend.title=element_blank())
pfda_plot

我不知道如何将数据集中的“种类”列分配给“标签”列，以便ggplot创建一个标签来描述每个数字代表哪些种类。我确定它与创建新的aes（）有关，但是到目前为止，我还没有成功使其发挥作用...

任何帮助将不胜感激！

谢谢

Carolina

Answer 1

geom_text的传说只能通过颜色调用，而您已经在geom_points（）中使用了它。

要获得所需的图并保持当前的配色方案，让我们尝试使用ggnewscale添加新的色标，我们仍将所有文本设为黑色（请参见scale_color_manual）：

library(ggplot2)
library(grid)
library(ggnewscale)

pfda_plot <- ggplot(data=pfdavar,aes(x=X1,y=X2,group=groups))+
  geom_point(aes(colour=groups))+
  geom_polygon(data=hulls,alpha=0.2,aes(fill=groups))+
  xlab("pFDA1")+
  ylab("pFDA2")+
  theme_classic()+
  theme(legend.title=element_blank())+
  new_scale_color()+
  geom_text(aes(label=labels,col=Species),
  fontface=1,hjust=0,vjust=0,size=3)+
  scale_color_manual(values=rep("black",18))

以上内容为您提供了接近的内容，只是geom_text图例全为“ a”。我们现在需要做的是更改默认值'a'，为此，我使用了@MarcoSandri's solution to change the default "a" in legend for geom_text()

g <- ggplotGrob(pfda_plot)
lbls <- 1:18
idx <- which(sapply(g$grobs[[15]][[1]][[1]]$grobs,function(i){
  "label" %in% names(i)}))
for(i in 1:length(idx)){
g$grobs[[15]][[1]][[1]]$grobs[[idx[i]]]$label <- lbls[i]
}
grid.draw(g)

Answer 2

您只需要创建另一个group_label和Labels组合而成的Species。如果需要，请使用factor()重新排列顺序。

library(dplyr)
library(ggplot2)

find_hull <- function(df) { df[chull(df$X1, df$X2), ] }
hulls <- plyr::ddply(pfdavar, "Function", find_hull)
### or do it the dplyr/purrr way
# hulls <- pfdavar %>% 
#   group_by(Function) %>% 
#   group_modify(~ find_hull(.x)) %>% 
#   ungroup()
# hulls

pfdavar <- pfdavar %>% 
  mutate(group_label = paste0(Labels, " - ", Species))

pfda_plot <- ggplot(data = pfdavar, aes(x = X1, y = X2, group = group_label)) +
  geom_point(aes(colour = group_label)) +
  geom_polygon(data = hulls, alpha = 0.2, 
               aes(x = X1, y = X2, fill = Function), inherit.aes = FALSE) +
  xlab("pFDA1") +
  ylab("pFDA2") +
  geom_text(aes(label = Labels, fontface = 1), hjust = 0, vjust = 0, size = 3) +
  scale_fill_brewer(palette = 'Dark2') +
  theme_classic() +
  theme(legend.title = element_blank()) 
pfda_plot

pfdavar <- pfdavar %>% 
  ### or use Tjebo's comment
  # mutate(group_label2 = reorder(group_label, gtools::mixedorder(group_label)))
  mutate(group_label2 = factor(group_label, levels = unique(pfdavar$group_label[order(pfdavar$Labels)])))
pfdavar

pfda_plot2 <- ggplot(data = pfdavar, aes(x = X1, y = X2, group = group_label2)) +
  geom_point(aes(colour = group_label2)) +
  geom_polygon(data = hulls, alpha = 0.2, 
               aes(x = X1, y = X2, fill = Function), inherit.aes = FALSE) +
  xlab("pFDA1") +
  ylab("pFDA2") +
  geom_text(aes(label = Labels, fontface = 1), hjust = 0, vjust = 0, size = 3) +
  scale_fill_brewer(palette = 'Dark2') +
  theme_classic() +
  guides(col = guide_legend(ncol = 4, byrow = TRUE)) +
  theme(legend.title = element_blank()) +
  theme(legend.position = 'bottom')
pfda_plot2

^{由reprex package（v0.3.0）于2019-11-28创建}

为带有文本标签的geom_text添加新图例作为图例键

2 个答案: