Combining time trend plot with timeline

Question

I want to create a plot (preferable using ggplot2) where I visualize a timeline together with a time-trend plot.

To put it in a practical example, I have aggregated unemployment rates for each year. I also have a data set denoting important legislation changes that are related to the labor market. Hence, I want to create a timeline where the unemployment rate is shown following the same x-axis (time).

I have generated some toy-data, see code below:

set.seed(2110)
year <- c(1950:2020)
unemployment <- rnorm(length(year), 0.05, 0.005)
un_emp <- data.frame(cbind(year, unemployment))


year <- c( 1957, 1961, 1975, 1976, 1983, 1985, 1995, 1999, 2011, 2018)
events <- c("Implemented unemployment benefit", 
            "Pre-school became free", 
            "Five-day workweek were introduced", 
            "Labor law reform 1976", 
            "Unemployment benefit were cut in half", 
            "Apprenticeship Act allows on-the-job training",
            "Changes in discrimination law",
            "Equal Pay for Equal Work was", 
            "9 weeks vacation were introduced",
            "Unemployment benefit were removed")

imp_event  <- data.frame(year, events)

I can easily plot the time-trend across the years:

library(tidyverse)
                      
ggplot(data = un_emp, aes(x = year, y = unemployment)) + 
  geom_line(color = "#FC4E07", size = 0.5) +
  theme_bw()

But how do I include the events (found in imp_event) in the plot in a nice and efficient way? How can I do this?

My aim is to make a timeline looking like the one from here but to combine it with the time-trend plot shown above. How can I do this?

I have tried to use vline but I cannot add the label of the event.

Thanks!

Answer 1

I think this should do the trick:

First, I created the axis with hline, using the mean you set for the data as the y intercept. Then I added a variable "height" to the events' dataframe, which takes the value of the axis and adds a value drawn from a normal distribution. I used this to draw the segments that create the lines towards each point. Finally, I inverted the y position of the year label so it's always in the opposite side of the segment.

library(tidyverse)

set.seed(2110)
year <- c(1950:2020)
unemployment <- rnorm(length(year), 0.05, 0.005)
un_emp <- data.frame(cbind(year, unemployment))

year <- c( 1957, 1961, 1975, 1976, 1983, 1985, 1995, 1999, 2011, 2018)
events <- c("Implemented unemployment benefit", 
            "Pre-school became free", 
            "Five-day workweek were introduced", 
            "Labor law reform 1976", 
            "Unemployment benefit were cut in half", 
            "Apprenticeship Act allows on-the-job training",
            "Changes in discrimination law",
            "Equal Pay for Equal Work was", 
            "9 weeks vacation were introduced",
            "Unemployment benefit were removed")

imp_event  <- data.frame(year, events) %>% 
  mutate(height = mean(unemployment) + rnorm(n(), 0, 0.02))

    ggplot(un_emp) +
  
  geom_hline(yintercept = 0.05) +
  
  geom_line(aes(x = year,
                y = unemployment),
            color = "red",
            alpha = 0.3,
            size = 1) +
  
  geom_segment(data = imp_event,
               aes(x = year,
                   xend = year,
                   y = 0.05,
                   yend = height)) +
  
  geom_text(data = imp_event,
            aes(label = year, 
                x = year,
                y = 0.05 + 0.002 * sign(0.05 - height)), 
            angle = 90, 
            size = 3.5, 
            fontface = "bold",
            check_overlap = T) +
  
  geom_point(data = imp_event,
             aes(x = year,
                 y = height,
                 fill = as.factor(events)),
             shape = 21,
             size = 4) +
  
  scale_x_continuous(name = NULL, 
                     labels = NULL) +
  
  scale_fill_discrete(name = "Event") +
  
  scale_y_continuous(name = "Unemployment Rate") +
  
  theme_bw() + 
  
  theme(panel.border = element_blank(),
        axis.line.y  = element_line(),
        axis.ticks.x = element_blank(),
        panel.grid = element_blank(),
        legend.position="bottom")

Answer 2

I worked with Jon Spring's solution but replaced geom_segment with geom_vline which gave a result close to what I wanted. The final code looked like this:

joined_data <- un_emp %>% left_join(imp_event, by = "year")

ggplot(data = joined_data, aes(x = year, y = unemployment)) + 
  geom_line(color = "red", size = 0.5) +

  theme_classic() +
  labs(y = "Unemployment rate", 
       x = "Years", 
       caption = "Data from XXXX") +
  geom_vline(data = joined_data %>% filter(!is.na(events)),  aes(xintercept = year), color = "gray70",  linetype = "dashed") +   
  ggrepel::geom_text_repel(data = joined_data, aes(x = year, y = unemployment-0.03, label = str_wrap(events, 10)), color = "gray70", direction = "y", size = 2.5, lineheight = 0.7, point.padding = 0.8)

Which produces the following plot:

I want to reward @Jon Spring the bounty but not sure how I reward a comment.

Answer 3

You can achieve this by overlaying a geom_text() call, but that requires the x and y values to be the same length as in the other plot so you can't just feed it a new df and overlay that.

Instead, you can achieve what you want by doing a left_join from un_emp to imp_events on year. Because there is only one row per year in imp_events you'll be left with a majority of missing values for events in the df which is perfect as I suspect you only want each event to appear as a label once.

For example:

joined_data <- un_emp %>% left_join(imp_event, by = "year")

ggplot(data = joined_data, aes(x = year, y = unemployment)) + 
  geom_line(color = "#FC4E07", size = 0.5) +
  geom_text(data = joined_data, aes(x = year, y = unemployment, label = (events), size = 3)) +
  theme_bw() 

Which gives you something like this:

You can have a look at the available options and play around with geom_text() here.