在行尾绘制标签
Plot labels at ends of lines
我有以下数据（temp.dat完整数据见尾注）
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
...
并且我可以生成以下图表：
ggplot(temp.dat) +
geom_line(aes(x = Year, y = Capex, group = State, colour = State))
我希望标签不是图例
- 颜色与系列相同
- 每个系列最后一个数据点的右侧
我注意到 baptiste 在以下答案中的评论 link，但是当我尝试修改他的代码时 (geom_text(aes(label = State, colour = State, x = Inf, y = Capex), hjust = -1))，文本没有出现。
ggplot2 - annotate outside of plot
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"))
不确定这是否是最好的方法，但您可以尝试以下方法（尝试一下 xlim 以正确设置限制）：
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))
您没有 100% 效仿@Baptiste 的解决方案。您需要使用 annotation_custom 并遍历所有 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$name == "panel"] <- "off"
grid.newpage()
grid.draw(gt)
（如果保留白色背景，则需要更改黄色。）
要使用 Baptiste 的想法，您需要关闭裁剪。但是当你这样做时，你会得到垃圾。此外，您需要取消图例，并且对于 geom_text、select 2014 年的资本支出，并增加边距以为标签留出空间。 （或者您可以调整 hjust 参数以在绘图面板内移动标签。）像这样：
library(ggplot2)
library(grid)
p = ggplot(temp.dat) +
geom_line(aes(x = Year, y = Capex, group = State, colour = State)) +
geom_text(data = subset(temp.dat, Year == "2014"), aes(label = State, colour = State, x = Inf, y = Capex), hjust = -.1) +
scale_colour_discrete(guide = 'none') +
theme(plot.margin = unit(c(1,3,1,1), "lines"))
# Code to turn off clipping
gt <- ggplotGrob(p)
gt$layout$clip[gt$layout$name == "panel"] <- "off"
grid.draw(gt)
但是，这种情节非常适合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)
编辑增加终点和标签之间的space：
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))
更新的解决方案是使用 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)
这个问题很老但很重要，我为厌倦了 ggplot 的人提供了另一个答案。
这个方案的原理可以很普遍地应用。
Plot_df <-
temp.dat %>% mutate_if(is.factor, as.character) %>% # Who has time for factors..
mutate(Year = as.numeric(Year))
现在，我们可以对数据进行子集化
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))
最后pretty_breaks部分只是固定下面的轴。
我想为标签名称较长的情况添加一个解决方案。在提供的所有解决方案中，标签都在绘图 canvas 内，但如果名称较长，它们将被截断。以下是我解决该问题的方法：
library(tidyverse)
# Make the "State" variable have longer levels
temp.dat <- temp.dat %>%
mutate(State = paste0(State, '-a-long-string'))
ggplot(temp.dat, aes(x = Year, y = Capex, color = State, group = State)) +
geom_line() +
# Add labels at the end of the line
geom_text(data = filter(temp.dat, Year == max(Year)),
aes(label = State),
hjust = 0, nudge_x = 0.1) +
# Allow labels to bleed past the canvas boundaries
coord_cartesian(clip = 'off') +
# Remove legend & adjust margins to give more space for labels
# Remember, the margins are t-r-b-l
theme(legend.position = 'none',
plot.margin = margin(0.1, 2.6, 0.1, 0.1, "cm"))
我来到这个问题是为了在最后一个拟合点而不是最后一个数据点直接标记一条拟合线（例如 loess()）。我最终找到了一种方法来做到这一点，主要基于 tidyverse 它也应该适用于带有一些 mod 的线性回归，所以我把它留在这里以供后代使用。
library(tidyverse)
temp.dat$Year <- as.numeric(temp.dat$Year)
temp.dat$State <- as.character(temp.dat$State)
#example of loess for multiple models
#
models <- temp.dat %>%
tidyr::nest(-State) %>%
dplyr::mutate(
# Perform loess calculation on each CpG group
m = purrr::map(data, loess,
formula = Capex ~ Year, span = .75),
# Retrieve the fitted values from each model
fitted = purrr::map(m, `[[`, "fitted")
)
# Apply fitted y's as a new column
results <- models %>%
dplyr::select(-m) %>%
tidyr::unnest()
#find final x values for each group
my_last_points <- results %>% group_by(State) %>% summarise(Year = max(Year, na.rm=TRUE))
#Join dataframe of predictions to group labels
my_last_points$pred_y <- left_join(my_last_points, results)
# Plot with loess line for each group
ggplot(results, aes(x = Year, y = Capex, group = State, colour = State)) +
geom_line(alpha = I(7/10), color="grey", show.legend=F) +
#stat_smooth(size=2, span=0.3, se=F, show_guide=F)
geom_point(size=1) +
geom_smooth(se=FALSE)+
geom_text(data = my_last_points, aes(x=Year+0.5, y=pred_y$fitted, label = State))
有一个新程序包可以解决这个非常普遍的问题。 {geomtextpath} 为直接标记提供了一些非常灵活的选项，而不是最后的“仅”标记...
此外，标签会跟随曲线！这可能不是每个人的口味，但我觉得这是一个非常整洁的外观。
library(geomtextpath)
## end of line
ggplot(temp.dat) +
geom_textline(aes(
x = Year, y = Capex, group = State, colour = State, label = State
),
hjust = 1
) +
theme(legend.position = "none")
## somewhere in the middle
ggplot(temp.dat) +
geom_textline(aes(
x = Year, y = Capex, group = State, colour = State, label = State
),
hjust = .7
) +
theme(legend.position = "none")
有很多geom，还有一个基于geom_smooth的预测曲线。 （回答用户 Mark Neal）
ggplot(temp.dat, aes(x = Year, y = Capex, group = State, colour = State)) +
geom_line() +
## note you currently have to specify method argument, otherwise the disambiguation of some function fails. see also https://github.com/AllanCameron/geomtextpath/issues/79) +
theme(legend.position = "none")
#> `geom_smooth()` using formula 'y ~ x'
我有以下数据（temp.dat完整数据见尾注）
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
...
并且我可以生成以下图表：
ggplot(temp.dat) +
geom_line(aes(x = Year, y = Capex, group = State, colour = State))
我希望标签不是图例
- 颜色与系列相同
- 每个系列最后一个数据点的右侧
我注意到 baptiste 在以下答案中的评论 link，但是当我尝试修改他的代码时 (geom_text(aes(label = State, colour = State, x = Inf, y = Capex), hjust = -1))，文本没有出现。
ggplot2 - annotate outside of plot
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"))
不确定这是否是最好的方法，但您可以尝试以下方法（尝试一下 xlim 以正确设置限制）：
library(dplyr)
lab <- tapply(temp.dat$Capex, temp.dat$State, last)
ggplot(temp.dat) +
geom_line(aes(x = Year, y = Capex, group = State, colour = State)) +
scale_color_discrete(guide = FALSE) +
geom_text(aes(label = names(lab), x = 12, colour = names(lab), y = c(lab), hjust = -.02))
您没有 100% 效仿@Baptiste 的解决方案。您需要使用 annotation_custom 并遍历所有 Capex：
library(ggplot2)
library(dplyr)
library(grid)
temp.dat <- structure(list(Year = c("2003", "2004", "2005", "2006", "2007",
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003",
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011",
"2012", "2013", "2014", "2003", "2004", "2005", "2006", "2007",
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2003",
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011",
"2012", "2013", "2014"), State = structure(c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("VIC",
"NSW", "QLD", "WA"), class = "factor"), Capex = c(5.35641472365348,
5.76523240652641, 5.24727577535625, 5.57988239709746, 5.14246402568366,
4.96786288162828, 5.493190785287, 6.08500616799372, 6.5092228474591,
7.03813541623157, 8.34736513875897, 9.04992300432169, 7.15830329914056,
7.21247045701994, 7.81373928617117, 7.76610217197542, 7.9744994967006,
7.93734452080786, 8.29289899132255, 7.85222269563982, 8.12683746325074,
8.61903784301649, 9.7904327253813, 9.75021175267288, 8.2950673974226,
6.6272705639724, 6.50170524635367, 6.15609626379471, 6.43799637295979,
6.9869551384028, 8.36305663640294, 8.31382617231745, 8.65409824343971,
9.70529678167458, 11.3102788081848, 11.8696420977237, 6.77937303542605,
5.51242844820827, 5.35789621712839, 4.38699327451101, 4.4925792218211,
4.29934654081527, 4.54639175257732, 4.70040615159951, 5.04056109514957,
5.49921208937735, 5.96590909090909, 6.18700407463007)), class = "data.frame", row.names = c(NA,
-48L), .Names = c("Year", "State", "Capex"))
temp.dat$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)
（如果保留白色背景，则需要更改黄色。）
要使用 Baptiste 的想法，您需要关闭裁剪。但是当你这样做时，你会得到垃圾。此外，您需要取消图例，并且对于 geom_text、select 2014 年的资本支出，并增加边距以为标签留出空间。 （或者您可以调整 hjust 参数以在绘图面板内移动标签。）像这样：
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)
但是，这种情节非常适合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)
编辑增加终点和标签之间的space：
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))
更新的解决方案是使用 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)
这个问题很老但很重要，我为厌倦了 ggplot 的人提供了另一个答案。
这个方案的原理可以很普遍地应用。
Plot_df <-
temp.dat %>% mutate_if(is.factor, as.character) %>% # Who has time for factors..
mutate(Year = as.numeric(Year))
现在，我们可以对数据进行子集化
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))
最后pretty_breaks部分只是固定下面的轴。
我想为标签名称较长的情况添加一个解决方案。在提供的所有解决方案中，标签都在绘图 canvas 内，但如果名称较长，它们将被截断。以下是我解决该问题的方法：
library(tidyverse)
# Make the "State" variable have longer levels
temp.dat <- temp.dat %>%
mutate(State = paste0(State, '-a-long-string'))
ggplot(temp.dat, aes(x = Year, y = Capex, color = State, group = State)) +
geom_line() +
# Add labels at the end of the line
geom_text(data = filter(temp.dat, Year == max(Year)),
aes(label = State),
hjust = 0, nudge_x = 0.1) +
# Allow labels to bleed past the canvas boundaries
coord_cartesian(clip = 'off') +
# Remove legend & adjust margins to give more space for labels
# Remember, the margins are t-r-b-l
theme(legend.position = 'none',
plot.margin = margin(0.1, 2.6, 0.1, 0.1, "cm"))
我来到这个问题是为了在最后一个拟合点而不是最后一个数据点直接标记一条拟合线（例如 loess()）。我最终找到了一种方法来做到这一点，主要基于 tidyverse 它也应该适用于带有一些 mod 的线性回归，所以我把它留在这里以供后代使用。
library(tidyverse)
temp.dat$Year <- as.numeric(temp.dat$Year)
temp.dat$State <- as.character(temp.dat$State)
#example of loess for multiple models
#
models <- temp.dat %>%
tidyr::nest(-State) %>%
dplyr::mutate(
# Perform loess calculation on each CpG group
m = purrr::map(data, loess,
formula = Capex ~ Year, span = .75),
# Retrieve the fitted values from each model
fitted = purrr::map(m, `[[`, "fitted")
)
# Apply fitted y's as a new column
results <- models %>%
dplyr::select(-m) %>%
tidyr::unnest()
#find final x values for each group
my_last_points <- results %>% group_by(State) %>% summarise(Year = max(Year, na.rm=TRUE))
#Join dataframe of predictions to group labels
my_last_points$pred_y <- left_join(my_last_points, results)
# Plot with loess line for each group
ggplot(results, aes(x = Year, y = Capex, group = State, colour = State)) +
geom_line(alpha = I(7/10), color="grey", show.legend=F) +
#stat_smooth(size=2, span=0.3, se=F, show_guide=F)
geom_point(size=1) +
geom_smooth(se=FALSE)+
geom_text(data = my_last_points, aes(x=Year+0.5, y=pred_y$fitted, label = State))
有一个新程序包可以解决这个非常普遍的问题。 {geomtextpath} 为直接标记提供了一些非常灵活的选项，而不是最后的“仅”标记...
此外，标签会跟随曲线！这可能不是每个人的口味，但我觉得这是一个非常整洁的外观。
library(geomtextpath)
## end of line
ggplot(temp.dat) +
geom_textline(aes(
x = Year, y = Capex, group = State, colour = State, label = State
),
hjust = 1
) +
theme(legend.position = "none")
## somewhere in the middle
ggplot(temp.dat) +
geom_textline(aes(
x = Year, y = Capex, group = State, colour = State, label = State
),
hjust = .7
) +
theme(legend.position = "none")
有很多geom，还有一个基于geom_smooth的预测曲线。 （回答用户 Mark Neal）
ggplot(temp.dat, aes(x = Year, y = Capex, group = State, colour = State)) +
geom_line() +
## note you currently have to specify method argument, otherwise the disambiguation of some function fails. see also https://github.com/AllanCameron/geomtextpath/issues/79) +
theme(legend.position = "none")
#> `geom_smooth()` using formula 'y ~ x'