使用ggplot2从水平时间轴更改为垂直时间轴时，标签重叠

Question

我想将本教程中介绍的时间轴转换为水平版本，其中将同一时间点的标签直接放置在彼此下方且不重叠：

http://benalexkeen.com/creating-a-timeline-graphic-using-r-and-ggplot2/

我已经稍微修改了网站上的代码，以手动将其调整为我的数据，但是代码非常相似。在水平时间轴上工作得很好。

我尝试在

中使用vjus

timeline_plot<- timeline_plot+geom_text(aes(x=text_position,label=events),size=2.5 , vjus=c(1:lenght(tl$events))

但这绝对不是正确的方法。

非常感谢， 达斯汀

library(ggplot2)
library(scales)
library(lubridate)

    tl$date <- as.Date(tl$date, format="%d-%m-%Y")

    unique(tl$status)
    status_levels <- c("Diagnosis", "Monitoring", "Symptoms", "Status", "Change", "Social")
    status_colors <- c("#0070C0", "#00B050", "#FFC000", "#C00000", "darksalmon", "darkorchid3")

    tl$status <- factor(tl$status, levels=status_levels, ordered=TRUE)
    # Der er 20 unique time points i datasættet                      
    positions <- c(0.2, 0.2, -0.5, 0.05, -0.3, 0.5, -0.5, 0.4, -0.2, -0.2, 0.1, 0.3, -0.7, 0.2, -0.4, -0.2, 0.5, -0.5, 0.2, -0.3) 
    directions <- c(1,   1,   -1,   1,   -1,   1,   -1,    1,   -1,  - 1,   1,  1,   -1,   1,    -1, - 1,   1,   -1,   1,   -1) 

    line_pos <- data.frame(
      "date"=unique(tl$date),
      "position"=rep(positions, length.out=length(unique(tl$date))),
      "direction"=rep(directions, length.out=length(unique(tl$date)))
    )

    tl <- merge(x=tl, y=line_pos, by="date", all = TRUE)
    tl <- tl[with(tl, order(date, status)), ]


    text_offset <- 0.1 

    tl$month_count <- ave(tl$date==tl$date, tl$date, FUN=cumsum)
    tl$text_position <- (tl$month_count * text_offset * tl$direction) +tl$position 


    month_buffer1 <- 6 
    month_buffer2 <- 12 
    month_date_range <- seq(min(tl$date) - months(month_buffer1), max(tl$date) + months(month_buffer2), by='month')
    month_format <- format(month_date_range, '%b')
    month_tl <- data.frame(month_date_range, month_format)


    year_date_range <- seq(min(tl$date) - months(month_buffer1), max(tl$date) + months(month_buffer2), by='year')
    year_date_range <- as.Date(
      intersect(
        ceiling_date(year_date_range, unit="year"),
        floor_date(year_date_range, unit="year")
      ),  origin = "1970-01-01"
    )
    year_format <- format(year_date_range, '%Y')
    year_tl <- data.frame(year_date_range, year_format)


    timeline_plot<-ggplot(tl,aes(x=0,y=date, col=status, label=events))
    timeline_plot<-timeline_plot+labs(col="") 
    timeline_plot<-timeline_plot+scale_color_manual(values=status_colors, labels=status_levels, drop = FALSE) values=status_colors, labels=status_levels
    timeline_plot<-timeline_plot+theme_classic()


    timeline_plot<-timeline_plot+geom_vline(xintercept=0, 
                                            color = "black", size=0.3)


    timeline_plot<-timeline_plot+geom_segment(data=tl[tl$month_count == 1,], aes(x=position,yend=date,xend=0), color='black', size=0.1) #size ændre fra 0.2 til 0.1

    # Plot scatter points at zero and date
    timeline_plot<-timeline_plot+geom_point(aes(x=0), size=3) 

    # Don't show axes, appropriately position legend
    timeline_plot<-timeline_plot+theme(axis.line.y=element_blank(),
                                       axis.text.y=element_blank(),
                                       axis.title.x=element_blank(),
                                       axis.title.y=element_blank(),
                                       axis.ticks.y=element_blank(),
                                       axis.text.x =element_blank(),
                                       axis.ticks.x =element_blank(),
                                       axis.line.x =element_blank(),
                                       legend.position = "bottom"
    )

    # Show text for each month
    # timeline_plot<-timeline_plot+geom_text(data=month_tl, aes(x=month_date_range,y=-0.1,label=month_format),size=2.5,vjust=0.5, color='black', angle=90)
    # Show year text
    timeline_plot<-timeline_plot+geom_text(data=year_tl, aes(y=year_date_range,x=-0.1,label=year_format, fontface="bold"),size=2, color='black') 
    # Show text for each milestone
    timeline_plot<-timeline_plot+geom_text(aes(x=text_position,label=events),size=2.5) 
    print(timeline_plot)