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ggplot2 geom_bin2d() in R: 2D Rectangular Density Bins

The geom_bin2d() function in ggplot2 plots 2D point density using RECTANGULAR bins. It is the rectangle-bin sister of geom_hex(), useful for scatter plots with many overlapping points.

By Selva Prabhakaran  ·  Published May 12, 2026  ·  Last updated May 12, 2026
⚡ Quick Answer
ggplot(df, aes(x, y)) + geom_bin2d()
geom_bin2d(bins = 30)                   # control bin count
geom_bin2d(binwidth = c(0.5, 1))         # specific bin widths
geom_hex()                                # hexagonal alternative
geom_density_2d()                         # contour lines

Need explanation? Read on for examples and pitfalls.

📊 Is geom_bin2d() the right tool?
START2D density with rectangular binsgeom_bin2d()hexagonal binsgeom_hex()raw scatter (few points)geom_point()contour linesgeom_density_2d()transparent overplottinggeom_point(alpha = 0.3)

What geom_bin2d() does in one sentence

geom_bin2d() divides the (x, y) plane into rectangular bins and colors each by point count. Equivalent to a 2D histogram.

Syntax

geom_bin2d(bins = 30, binwidth = NULL, ...). Built into ggplot2; no extra packages.

Run live
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R2D histogram
library(ggplot2) ggplot(diamonds, aes(carat, price)) + geom_bin2d(bins = 50)

  

  





Tip
geom_bin2d doesn't need any extra package; geom_hex requires hexbin. Use bin2d if you want zero dependencies.



Five common patterns



1. Standard 2D histogram




  

    
RCarat vs price

    
ggplot(diamonds, aes(carat, price)) +
  geom_bin2d()

    

      
      
    

    

  

  





2. Finer bins




  

    
RMore resolution

    
ggplot(diamonds, aes(carat, price)) +
  geom_bin2d(bins = 100)

    

      
      
    

    

  

  





3. Custom binwidth




  

    
RSpecific bin sizes

    
ggplot(diamonds, aes(carat, price)) +
  geom_bin2d(binwidth = c(0.1, 200))

    

      
      
    

    

  

  





4. Color scale




  

    
RViridis

    
ggplot(diamonds, aes(carat, price)) +
  geom_bin2d() +
  scale_fill_viridis_c()

    

      
      
    

    

  

  





5. Compare to geom_hex




  

    
RSide by side

    
library(patchwork)
p1 <- ggplot(diamonds, aes(carat, price)) + geom_bin2d() + ggtitle("bin2d")
p2 <- ggplot(diamonds, aes(carat, price)) + geom_hex() + ggtitle("hex")
p1 + p2

    

      
      
    

    

  

  





Key Insight
geom_bin2d and geom_hex produce similar visualizations. Hex looks more organic; bin2d is simpler. Pick by aesthetic preference.



geom_bin2d() vs geom_hex() vs geom_point() with alpha







Function
Bin
Dependency






geom_bin2d()
Rectangular
None




geom_hex()
Hexagonal
hexbin




geom_point(alpha)
None
None







For dependency-free 2D density, geom_bin2d is the choice.



A practical workflow



Use geom_bin2d for dense scatter where rectangular bins suffice.




  

    
RInteractive R

    
ggplot(diamonds, aes(carat, price)) +
  geom_bin2d(bins = 50) +
  scale_fill_viridis_c() +
  scale_y_log10()

    

      
      
    

    

  

  





Common pitfalls



Pitfall 1: too few bins. Default 30 is often coarse. Try 50 or 100.



Pitfall 2: forgetting fill scale. Default fill is gradient blue. Use scale_fill_viridis_c() or similar for better visibility.



Warning
geom_bin2d colors bins by COUNT. For density (count per unit area), use stat_density_2d or normalize.



Try it yourself





Try it: Plot 2D bin histogram of mtcars wt vs mpg. Save to ex_plot.



  

    
RYour turn: 2d hist

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

    

      
      
    

    

  

  





Click to reveal solution



  

    
RSolution

    
ex_plot <- ggplot(mtcars, aes(wt, mpg)) +
  geom_bin2d(bins = 10) +
  scale_fill_viridis_c()

    

      
      
    

    

  

  





Explanation: mtcars has 32 points; few bins is appropriate.










After mastering geom_bin2d, look at:



    


  • geom_hex(): hexagonal bins
    • 


  • geom_density_2d(): contour lines
    • 


  • stat_density_2d(): smooth density
    • 


  • geom_point(alpha): scatter alternative
    • 





FAQ



What does geom_bin2d do in ggplot2?



geom_bin2d() plots 2D point density using rectangular bins; each bin is colored by point count.



What is the difference between geom_bin2d and geom_hex?



geom_bin2d uses rectangles; geom_hex uses hexagons. Hex is more organic-looking; bin2d is dependency-free.



Do I need a special package for geom_bin2d?



No. It is built into ggplot2.



How many bins should I use?



Default 30 is OK for medium data. For dense plots, try 50-100.



How do I show density (not count) per bin?



Use stat_density_2d for smoothed density, or normalize the count manually before plotting.



          

        


        
      


      

        

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

        

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