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Étiquettes de tracé aux extrémités des lignes

J'ai les données suivantes (temp.dat Voir note de fin pour les données complètes)

   Year State     Capex
1  2003   VIC  5.356415
2  2004   VIC  5.765232
3  2005   VIC  5.247276
4  2006   VIC  5.579882
5  2007   VIC  5.142464
...

et je peux produire le tableau suivant:

ggplot(temp.dat) + 
  geom_line(aes(x = Year, y = Capex, group = State, colour = State))

enter image description here

Au lieu de la légende, j'aimerais que les étiquettes soient

  1. de la même couleur que la série
  2. à droite du dernier point de données pour chaque série

J'ai remarqué les commentaires de baptiste dans la réponse au lien suivant, mais lorsque j'essaie d'adapter son code (geom_text(aes(label = State, colour = State, x = Inf, y = Capex), hjust = -1)), le texte n'apparaît pas.

ggplot2 - annoter en dehors de la parcelle

temp.dat <- structure(list(Year = c("2003", "2004", "2005", "2006", "2007", 
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003", 
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
"2012", "2013", "2014", "2003", "2004", "2005", "2006", "2007", 
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003", 
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
"2012", "2013", "2014"), State = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("VIC", 
"NSW", "QLD", "WA"), class = "factor"), Capex = c(5.35641472365348, 
5.76523240652641, 5.24727577535625, 5.57988239709746, 5.14246402568366, 
4.96786288162828, 5.493190785287, 6.08500616799372, 6.5092228474591, 
7.03813541623157, 8.34736513875897, 9.04992300432169, 7.15830329914056, 
7.21247045701994, 7.81373928617117, 7.76610217197542, 7.9744994967006, 
7.93734452080786, 8.29289899132255, 7.85222269563982, 8.12683746325074, 
8.61903784301649, 9.7904327253813, 9.75021175267288, 8.2950673974226, 
6.6272705639724, 6.50170524635367, 6.15609626379471, 6.43799637295979, 
6.9869551384028, 8.36305663640294, 8.31382617231745, 8.65409824343971, 
9.70529678167458, 11.3102788081848, 11.8696420977237, 6.77937303542605, 
5.51242844820827, 5.35789621712839, 4.38699327451101, 4.4925792218211, 
4.29934654081527, 4.54639175257732, 4.70040615159951, 5.04056109514957, 
5.49921208937735, 5.96590909090909, 6.18700407463007)), class = "data.frame", row.names = c(NA, 
-48L), .Names = c("Year", "State", "Capex"))
rggplot2legend
46
Hugh

Pour utiliser l'idée de Baptiste, vous devez désactiver le découpage. Mais quand vous le faites, vous obtenez des ordures. De plus, vous devez supprimer la légende et, pour geom_text, sélectionnez Capex pour 2014 et augmentez la marge pour laisser de la place aux étiquettes. (Ou vous pouvez ajuster le paramètre hjust pour déplacer les étiquettes à l'intérieur du panneau de traçage.)

library(ggplot2)
library(grid)

p = ggplot(temp.dat) + 
  geom_line(aes(x = Year, y = Capex, group = State, colour = State)) + 
  geom_text(data = subset(temp.dat, Year == "2014"), aes(label = State, colour = State, x = Inf, y = Capex), hjust = -.1) +
  scale_colour_discrete(guide = 'none')  +    
  theme(plot.margin = unit(c(1,3,1,1), "lines")) 

# Code to turn off clipping
gt <- ggplotGrob(p)
gt$layout$clip[gt$layout$name == "panel"] <- "off"
grid.draw(gt)

enter image description here

Mais, c’est le genre d’intrigue qui convient parfaitement à directlabels.

library(ggplot2)
library(directlabels)

ggplot(temp.dat, aes(x = Year, y = Capex, group = State, colour = State)) + 
  geom_line() +
  scale_colour_discrete(guide = 'none') +
  scale_x_discrete(expand=c(0, 1)) +
  geom_dl(aes(label = State), method = list(dl.combine("first.points", "last.points"), cex = 0.8))

enter image description here

Edit Pour augmenter l'espace entre le point final et les étiquettes:

ggplot(temp.dat, aes(x = Year, y = Capex, group = State, colour = State)) + 
  geom_line() +
  scale_colour_discrete(guide = 'none') +
  scale_x_discrete(expand=c(0, 1)) +
  geom_dl(aes(label = State), method = list(dl.trans(x = x + 0.2), "last.points", cex = 0.8)) +
  geom_dl(aes(label = State), method = list(dl.trans(x = x - 0.2), "first.points", cex = 0.8))
57
Sandy Muspratt

Une solution plus récente consiste à utiliser ggrepel:

library(ggplot2)
library(ggrepel)
library(dplyr)

temp.dat %>%
  mutate(label = if_else(Year == max(Year), as.character(State), NA_character_)) %>%
  ggplot(aes(x = Year, y = Capex, group = State, colour = State)) + 
  geom_line() + 
  geom_label_repel(aes(label = label),
                  Nudge_x = 1,
                  na.rm = TRUE)

enter image description here

45
Hugh

Cette question est ancienne mais doré, et je donne une autre réponse aux gens fatigués de ggplot.

Le principe de cette solution peut être appliqué de manière assez générale.

Plot_df <- 
  temp.dat %>% mutate_if(is.factor, as.character) %>%  # Who has time for factors..
  mutate(Year = as.numeric(Year))

Et maintenant, nous pouvons subdiviser nos données

ggplot() + 
geom_line(data = Plot_df, aes(Year, Capex, color = State)) +
geom_text(data = Plot_df %>% filter(Year == last(Year)), aes(label = State, 
                                                           x = Year + 0.5, 
                                                           y = Capex, 
                                                           color = State)) + 
          guides(color = FALSE) + theme_bw() + 
          scale_x_continuous(breaks = scales::pretty_breaks(10))

La dernière partie de pretty_breaks consiste simplement à fixer l’axe ci-dessous.

enter image description here

14
Nick

Pas sûr que ce soit la meilleure façon, mais vous pouvez essayer ce qui suit (jouer un peu avec xlim pour définir correctement les limites):

library(dplyr)
lab <- tapply(temp.dat$Capex, temp.dat$State, last)
ggplot(temp.dat) + 
    geom_line(aes(x = Year, y = Capex, group = State, colour = State)) +
    scale_color_discrete(guide = FALSE) +
    geom_text(aes(label = names(lab), x = 12, colour = names(lab), y = c(lab), hjust = -.02))

enter image description here

7
DatamineR

Vous n'avez pas imité la solution de @ Baptiste à 100%. Vous devez utiliser annotation_custom et parcourez tous vos Capex:

library(ggplot2)
library(dplyr)
library(grid)

temp.dat <- structure(list(Year = c("2003", "2004", "2005", "2006", "2007", 
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003", 
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
"2012", "2013", "2014", "2003", "2004", "2005", "2006", "2007", 
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003", 
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", 
"2012", "2013", "2014"), State = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("VIC", 
"NSW", "QLD", "WA"), class = "factor"), Capex = c(5.35641472365348, 
5.76523240652641, 5.24727577535625, 5.57988239709746, 5.14246402568366, 
4.96786288162828, 5.493190785287, 6.08500616799372, 6.5092228474591, 
7.03813541623157, 8.34736513875897, 9.04992300432169, 7.15830329914056, 
7.21247045701994, 7.81373928617117, 7.76610217197542, 7.9744994967006, 
7.93734452080786, 8.29289899132255, 7.85222269563982, 8.12683746325074, 
8.61903784301649, 9.7904327253813, 9.75021175267288, 8.2950673974226, 
6.6272705639724, 6.50170524635367, 6.15609626379471, 6.43799637295979, 
6.9869551384028, 8.36305663640294, 8.31382617231745, 8.65409824343971, 
9.70529678167458, 11.3102788081848, 11.8696420977237, 6.77937303542605, 
5.51242844820827, 5.35789621712839, 4.38699327451101, 4.4925792218211, 
4.29934654081527, 4.54639175257732, 4.70040615159951, 5.04056109514957, 
5.49921208937735, 5.96590909090909, 6.18700407463007)), class = "data.frame", row.names = c(NA, 
-48L), .Names = c("Year", "State", "Capex"))

temp.dat$Year <- factor(temp.dat$Year)

color <- c("#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072")

gg <- ggplot(temp.dat) 
gg <- gg + geom_line(aes(x=Year, y=Capex, group=State, colour=State))
gg <- gg + scale_color_manual(values=color)
gg <- gg + labs(x=NULL)
gg <- gg + theme_bw()
gg <- gg + theme(legend.position="none")

states <- temp.dat %>% filter(Year==2014)

for (i in 1:nrow(states))  {
  print(states$Capex[i])
  print(states$Year[i])
  gg <- gg + annotation_custom(
    grob=textGrob(label=states$State[i], 
                    hjust=0, gp=gpar(cex=0.75, col=color[i])),
    ymin=states$Capex[i],
    ymax=states$Capex[i],
    xmin=states$Year[i],
    xmax=states$Year[i])
}    

gt <- ggplot_gtable(ggplot_build(gg))
gt$layout$clip[gt$layout$name == "panel"] <- "off"
grid.newpage()
grid.draw(gt)

(Vous voudrez changer le jaune si vous conservez le fond blanc.)

enter image description here

3
hrbrmstr