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geom_rect in ggplot2

How to make a timeline using geom_rect.

New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

geom_rect with a line graph

geom_rect is defined by its four sides (xmin, xmax, ymin, ymax), which are all included in the dataset. Fill refers to the colour of the rectangle, colour refers to the border, and size refers to the border width.

This line graph shows the unemployment number in the United States every month, beginning in July 1967. (This dataset comes with R.) We use geom_rect to shade the background according to the President's party. An important note: the President does not control economic policy, something that this graph hopefully makes apparent. This is for illutrustive purposes, using a simple case and a default dataset.



df <- data.frame(name = c("Nixon", "Ford", "Carter", "Reagan", "Bush", "Clinton", "Bush", "Obama"),
                   start = as.Date(c("1969-01-20", "1974-08-09", "1977-01-20", "1981-01-20",
                             "1989-01-20", "1993-01-20", "2001-01-20", "2009-01-20")),
                   end = as.Date(c("1974-08-09", "1977-01-20", "1981-01-20", "1989-01-20", 
                           "1993-01-20", "2001-01-20", "2009-01-20", "2017-01-20")),
                   party = c("R", "R", "D", "R", "R", "D", "R", "D"),
                   stringsAsFactors = FALSE) %>%
  mutate(median_x = start + floor((end-start)/2))

p <- ggplot(economics, aes(x=date,y=unemploy)) +
  geom_rect(data=df, aes(NULL,NULL,xmin=start,xmax=end,fill=party),
            ymin=0,ymax=16000, colour="white", size=0.5, alpha=0.2) +
  scale_fill_manual(values=c("R" = "red", "D" = "blue")) +
  geom_line() +
  geom_text(data=df,aes(x=median_x,y=3000,label=name), size=3) +
  labs(title = "Unemmployment numbers since 1967",
       y = "No. unemployed (x 1000)")
fig <- ggplotly(p)


A Timeline Using geom_rect

geom_rect could also be the "main course" rather than just the background, for example by making a timeline. Here are the leaders of the current European Union member countries, since 2000. Data comes from ParlGov (which is where the parties' left-right scores come from, so please direct your complaints elsewhere). The LaCroixColoR package is used and can be installed using the instructions in the GitHub Readme.


european_leaders <- read.csv("",
                             stringsAsFactors = FALSE) %>%
  mutate(stint_start = as.Date(stint_start),
         stint_end = as.Date(stint_end),
         median_x = as.Date(median_x),
         left_right = as.character(left_right))

p <- ggplot(european_leaders, aes(xmin=stint_start, xmax=stint_end, ymin=vert_min, ymax=vert_max, fill=left_right)) +
  geom_rect(colour="white", size=0.1) +
  geom_text(aes(x=median_x, y=median_y, size=size, label=pm_name, #all names of separate variables
                text=paste(party_name_english, " (",country_name,")", sep=""))) +
  scale_fill_manual(values=lacroix_palette("PassionFruit",type = "continuous", n=8)) + #matches left/right colours
  labs(title = "Timeline of European leaders since 2000",
       x = "year",
       y = "",
       fill = "Party's \nleft-right \nscore",
       size = NULL) +
  theme(axis.text.y = element_blank(), #y-axis doesn't have actual values; no need for labels
        axis.ticks.y = element_blank())
fig <- ggplotly(fig, tooltip = c("label", "text")) #how to select what shows on the tooltip


What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:


fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 


app <- Dash$new()

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)