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ggplot2 geom_rect() in R: Draw Rectangles

The geom_rect() function in ggplot2 draws rectangles from explicit xmin, xmax, ymin, ymax coordinates. Useful for highlighting regions, time-period shading, or custom annotations.

By Selva Prabhakaran  ·  Published May 11, 2026  ·  Last updated May 11, 2026
⚡ Quick Answer
ggplot(df, aes(xmin = x1, xmax = x2, ymin = y1, ymax = y2)) + geom_rect()
geom_rect(aes(...), fill = "yellow", alpha = 0.3)
geom_tile(...)                            # different: x, y, width, height
annotate("rect", xmin = ..., ...)         # one-off rectangle

Need explanation? Read on for examples and pitfalls.

📊 Is geom_rect() the right tool?
STARTexplicit corner coords (xmin/xmax/ymin/ymax)geom_rect()center + width/heightgeom_tile()one-off regionannotate("rect", ...)highlight a time periodgeom_rect()background bandsgeom_rect()

What geom_rect() does in one sentence

geom_rect() draws rectangles defined by xmin, xmax, ymin, ymax aesthetics. Each row produces ONE rectangle.

Syntax

geom_rect(mapping = NULL, data = NULL, fill = "grey50", alpha = 1, ...). Requires aes(xmin, xmax, ymin, ymax).

Run live
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RHighlight time periods
library(ggplot2) ggplot(economics, aes(date, unemploy)) + geom_line() + geom_rect( aes(xmin = as.Date("2008-09-01"), xmax = as.Date("2009-12-01"), ymin = -Inf, ymax = Inf), fill = "red", alpha = 0.2, inherit.aes = FALSE )

  

  





Tip
Use inherit.aes = FALSE when geom_rect's aesthetics differ from the main plot. Otherwise ggplot tries to apply parent aesthetics.



Five common patterns



1. Highlight time period




  

    
RRecession band

    
ggplot(econ_df, aes(date, value)) +
  geom_line() +
  geom_rect(
    aes(xmin = as.Date("2008-01-01"), xmax = as.Date("2009-06-01"),
        ymin = -Inf, ymax = Inf),
    fill = "red", alpha = 0.2,
    inherit.aes = FALSE
  )

    

      
      
    

    

  

  





2. Multiple rectangles




  

    
RSeveral highlight bands

    
bands <- tibble(start = c(2008, 2020), end = c(2009, 2021))

ggplot(df, aes(year, value)) +
  geom_line() +
  geom_rect(
    data = bands,
    aes(xmin = start, xmax = end, ymin = -Inf, ymax = Inf),
    fill = "red", alpha = 0.2,
    inherit.aes = FALSE
  )

    

      
      
    

    

  

  





3. Background grid cells




  

    
RMark specific regions

    
ggplot(df, aes(x, y)) +
  geom_rect(
    aes(xmin = 1, xmax = 3, ymin = 1, ymax = 3),
    fill = "yellow", alpha = 0.3,
    inherit.aes = FALSE
  ) +
  geom_point()

    

      
      
    

    

  

  





4. With borders




  

    
ROutlined rectangle

    
geom_rect(aes(xmin = ..., xmax = ..., ymin = ..., ymax = ...),
          color = "black", fill = NA)

    

      
      
    

    

  

  





5. annotate alternative




  

    
ROne-off rect

    
ggplot(df, aes(x, y)) +
  geom_point() +
  annotate("rect", xmin = 0, xmax = 1, ymin = 0, ymax = 1,
           fill = "yellow", alpha = 0.3)

    

      
      
    

    

  

  





Key Insight
For a SINGLE rectangle, annotate("rect", ...) is cleaner than geom_rect() because it doesn't require a data frame. For data-driven rectangles (multiple regions), use geom_rect.



geom_rect() vs geom_tile() vs annotate()







Function
Spec
Best for






geom_rect()
xmin/xmax/ymin/ymax
Data-driven rectangles




geom_tile()
x, y, width, height
Heatmaps




annotate("rect", ...)
Same as geom_rect
One-off rectangle







A practical workflow



Use geom_rect for time-period shading on time-series plots.




  

    
RInteractive R

    
recessions <- tibble(
  start = as.Date(c("2001-03-01","2008-01-01","2020-02-01")),
  end   = as.Date(c("2001-11-01","2009-06-01","2020-04-01"))
)

ggplot(econ, aes(date, value)) +
  geom_rect(
    data = recessions,
    aes(xmin = start, xmax = end, ymin = -Inf, ymax = Inf),
    fill = "grey80", alpha = 0.5,
    inherit.aes = FALSE
  ) +
  geom_line()

    

      
      
    

    

  

  





Recession bands behind a time-series line.



Common pitfalls



Pitfall 1: forgetting inherit.aes = FALSE. Without it, ggplot tries to apply the main plot's aesthetics to geom_rect, which may not have x/y mapped.



Pitfall 2: y range for full-height bands. Use ymin = -Inf, ymax = Inf for full-height shading.



Warning
geom_rect() requires all four corner aesthetics. Missing any errors at runtime.



Try it yourself





Try it: Add a yellow rectangle highlighting cars with 4-6 cyl in mtcars wt-mpg scatter. Save to ex_plot.



  

    
RYour turn: highlight region

    
ex_plot <- mtcars |>
  ggplot(aes(wt, mpg)) +
  # your code here

    

      
      
    

    

  

  





Click to reveal solution



  

    
RSolution

    
ex_plot <- ggplot(mtcars, aes(wt, mpg)) +
  annotate("rect", xmin = 2, xmax = 3.5, ymin = 20, ymax = 35,
           fill = "yellow", alpha = 0.3) +
  geom_point()

    

      
      
    

    

  

  





Explanation: annotate is cleaner for a one-off rectangle. Yellow band highlights light, efficient cars.










After mastering geom_rect, look at:



    


  • geom_tile(): heatmap tiles
    • 


  • annotate("rect", ...): one-off rectangle
    • 


  • geom_polygon(): irregular shapes
    • 


  • geom_ribbon(): between-curves area
    • 


  • geom_vline() / geom_hline(): reference lines
    • 





FAQ



What does geom_rect do in ggplot2?



geom_rect() draws rectangles from xmin/xmax/ymin/ymax aesthetics. Each row produces one rectangle.



What is the difference between geom_rect and geom_tile?



geom_rect uses corner coordinates (xmin/xmax/ymin/ymax). geom_tile uses center + width/height. geom_tile is more common for heatmaps.



How do I add a single rectangle annotation?



Use annotate("rect", xmin = ..., ...) instead of geom_rect. No data frame needed.



How do I make full-height bands?



Pass ymin = -Inf, ymax = Inf. This extends the rectangle to the plot's full y range.



Why does geom_rect error in my plot?



Often because the parent plot has different aesthetics. Pass inherit.aes = FALSE to make geom_rect ignore them.



          

        


        
      


      

        

        
© 2016-2026 Selva Prabhakaran.
          This work is licensed under the Creative Commons License.
        

        

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