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R中的ggplo2:geom\U段显示的线与geom\U线不同

segment shape line ggplot2 r

Y.Coch · 技术社区 · 7 年前

假设我有这个数据框:

treatment <- c(rep("A",6),rep("B",6),rep("C",6),rep("D",6),rep("E",6),rep("F",6))
year <- as.numeric(c(1999:2004,1999:2004,2005:2010,2005:2010,2005:2010,2005:2010))
variable <- c(runif(6,4,5),runif(6,5,6),runif(6,3,4),runif(6,4,5),runif(6,5,6),runif(6,6,7))
se <- c(runif(6,0.2,0.5),runif(6,0.2,0.5),runif(6,0.2,0.5),runif(6,0.2,0.5),runif(6,0.2,0.5),runif(6,0.2,0.5))
id <- 1:36
df1 <- as.data.table(cbind(id,treatment,year,variable,se))

df1$year <- as.numeric(df1$year)
df1$variable <- as.numeric(df1$variable)
df1$se <- as.numeric(df1$se)

draw two lines with the same origin using ggplot2 in R

我使用以下脚本成功地做到了这一点:

y1 <- df1[df1$treatment=='A'&df1$year==2004,]$variable
y2 <- df1[df1$treatment=='B'&df1$year==2004,]$variable
y3 <- df1[df1$treatment=='C'&df1$year==2005,]$variable
y4 <- df1[df1$treatment=='D'&df1$year==2005,]$variable
y5 <- df1[df1$treatment=='E'&df1$year==2005,]$variable
y5 <- df1[df1$treatment=='E'&df1$year==2005,]$variable
y6 <- df1[df1$treatment=='F'&df1$year==2005,]$variable

p <- ggplot(df1,aes(x=year,y=variable,group=treatment,color=treatment))+
geom_line(aes(y = variable, group = treatment, linetype = treatment, color = treatment),size=1.5,lineend = "round") +
scale_linetype_manual(values=c('solid','solid','solid','dashed','solid','dashed')) +
geom_point(aes(colour=factor(treatment)),size=4)+
geom_errorbar(aes(ymin=variable-se,ymax=variable+se),width=0.2,size=1.5)+
guides(colour = guide_legend(override.aes = list(shape=NA,linetype = c("solid", "solid",'solid','dashed','solid','dashed'))))

p+labs(title="Title", x="years", y = "Variable 1")+
  theme_classic() +
scale_x_continuous(breaks=c(1998:2010), labels=c(1998:2010),limits=c(1998.5,2010.5))+
  geom_segment(aes(x=2004, y=y1, xend=2005, yend=y3),colour='blue1',size=1.5,linetype='solid')+
  geom_segment(aes(x=2004, y=y1, xend=2005, yend=y4),colour='blue1',size=1.5,linetype='dashed')+
  geom_segment(aes(x=2004, y=y2, xend=2005, yend=y5),colour='red3',size=1.5,linetype='solid')+
  geom_segment(aes(x=2004, y=y2, xend=2005, yend=y6),colour='red3',size=1.5,linetype='dashed')+
  scale_color_manual(values=c('blue1','red3','blue1','blue1','red3','red3'))+
  theme(text = element_text(size=12))

size=1.5 和 linetype='solid' dashed ).

当然,我可以手动更改线段的大小以获得类似的线,但当我这样做时,线段不如使用 geom_line . 此外,通过包含 size 或 linetype aes()

1 回复 | 直到 7 年前

Dave Gruenewald 7 年前

这似乎是geom_段的抗混叠问题,但从一开始,这似乎是一种有点麻烦的方法。我想我通过复制 A 和 B 原始数据帧中的处理。

# First we are going to duplicate and rename the 'shared' treatments
library(dplyr)
library(ggplot2)

df1 %>% 
  filter(treatment %in% c("A", "B")) %>% 
  mutate(treatment = ifelse(treatment == "A",
                            "AA", "BB")) %>% 
  bind_rows(df1) %>% # This rejoins with the original data
  # Now we create `treatment_group` and `line_type` variables
  mutate(treatment_group = ifelse(treatment %in% c("A", "C", "D", "AA"),
                                  "treatment1",
                                  "treatment2"), # This variable will denote color
         line_type = ifelse(treatment %in% c("AA", "BB", "D", "F"),
                            "type1",
                            "type2")) %>% # And this variable denotes the line type

# Now pipe into ggplot
  ggplot(aes(x = year, y = variable,
             group = interaction(treatment_group, line_type), # grouping by both linetype and color
             color = treatment_group)) +
  geom_line(aes(x = year, y = variable, linetype = line_type), 
            size = 1.5, lineend = "round") +
  geom_point(size=4) +
  # The rest here is more or less the same as what you had
  geom_errorbar(aes(ymin = variable-se, ymax = variable+se), 
                width = 0.2, size = 1.5) +
  scale_color_manual(values=c('blue1','red3')) +
  scale_linetype_manual(values = c('dashed', 'solid')) +
  labs(title = "Title", x = "Years", y = "Variable 1") +
  scale_x_continuous(breaks = c(1998:2010), 
                     limits = c(1998.5, 2010.5))+
  theme_classic() +
  theme(text = element_text(size=12))

我的数字不同,因为它们是随机生成的。

然后,您可以根据自己的喜好修改图例,但我的建议是使用以下内容 geom_label check_overlap = TRUE

希望这有帮助!