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ggplot2 scale_y_continuous() in R: Customize the Y Axis

The scale_y_continuous() function in ggplot2 customizes the Y axis on plots with a continuous (numeric) y mapping. It is the y-axis sister of scale_x_continuous().

By Selva Prabhakaran  ·  Published May 10, 2026  ·  Last updated May 10, 2026
⚡ Quick Answer
+ scale_y_continuous(breaks = seq(0, 100, 10))
+ scale_y_continuous(labels = scales::dollar)
+ scale_y_continuous(limits = c(0, 50))
+ scale_y_continuous(trans = "log10")
+ scale_y_continuous(name = "Revenue ($)")

Need explanation? Read on for examples and pitfalls.

📊 Is scale_y_continuous() the right tool?
STARTnumeric y axis customizationscale_y_continuous()log-scale yscale_y_log10()discrete yscale_y_discrete()date yscale_y_date()secondary axisscale_y_continuous(sec.axis = ...)

What scale_y_continuous() does in one sentence

scale_y_continuous() controls the Y axis: breaks (tick positions), labels (tick text), limits (range), transformations. Identical to scale_x_continuous but for y.

Syntax

scale_y_continuous(name = waiver(), breaks = waiver(), labels = waiver(), limits = NULL, trans = "identity", sec.axis = waiver(), ...).

Run live
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RDollar-formatted y axis
library(ggplot2) library(scales) ggplot(economics, aes(date, unemploy)) + geom_line() + scale_y_continuous( breaks = seq(0, 16000, 4000), labels = comma )

  

  





Tip
Use scales::dollar / scales::comma / scales::percent for common label formats. They're functions, not strings.



Five common patterns



1. Custom breaks




  

    
RTick every 1000

    
+ scale_y_continuous(breaks = seq(0, 10000, 1000))

    

      
      
    

    

  

  





2. Dollar-formatted labels




  

    
RMoney axis

    
+ scale_y_continuous(labels = scales::dollar)

    

      
      
    

    

  

  





3. Percent labels




  

    
RProportion to %

    
+ scale_y_continuous(labels = scales::percent)

    

      
      
    

    

  

  





4. Log scale




  

    
RLog y

    
+ scale_y_log10(labels = scales::comma)

    

      
      
    

    

  

  





5. Secondary y axis




  

    
RTwo y scales

    
+ scale_y_continuous(
    name = "Primary (count)",
    sec.axis = sec_axis(~ . / 100, name = "Secondary (%)")
)

    

      
      
    

    

  

  





Key Insight
For a secondary axis, both must be linearly related. ggplot intentionally restricts dual y-axes to discourage misleading visualizations.



scale_y_continuous() vs scale_y_log10() vs coord_cartesian







Function
Best for






scale_y_continuous()
General y customization




scale_y_log10()
Shortcut for log y




scale_y_sqrt()
Square-root y




coord_cartesian(ylim)
Zoom without dropping data







A practical workflow



Combine breaks, labels, and trans for production-ready axes.




  

    
RInteractive R

    
ggplot(sales, aes(month, revenue)) +
  geom_col() +
  scale_y_continuous(
    name = "Revenue (USD)",
    breaks = seq(0, 100000, 20000),
    labels = scales::dollar,
    expand = expansion(mult = c(0, 0.1))
  )

    

      
      
    

    

  

  





Dollar formatting + breaks + tight bottom expansion.



Common pitfalls



Pitfall 1: limits drops data. Use coord_cartesian(ylim = c(0, 100)) to zoom without dropping.



Pitfall 2: dual axes can mislead. ggplot's sec.axis allows it but only with a linear transformation; don't combine unrelated scales.



Warning
scale_y_continuous(limits = ...) DROPS data outside; coord_cartesian(ylim = ...) ZOOMS only. Use coord_cartesian when stats need the full data.



Try it yourself





Try it: Plot mtcars wt vs hp with y axis log-transformed and comma labels. Save to ex_plot.



  

    
RYour turn: log y with commas

    
library(scales)

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

    

      
      
    

    

  

  





Click to reveal solution



  

    
RSolution

    
ex_plot <- ggplot(mtcars, aes(wt, hp)) +
  geom_point() +
  scale_y_log10(labels = comma)

    

      
      
    

    

  

  





Explanation: scale_y_log10 with comma formatting.










After mastering scale_y_continuous, look at:



    


  • scale_x_continuous(): same for x
    • 


  • scale_y_log10() / scale_y_sqrt(): shortcuts
    • 


  • scale_y_date(): time-axis y
    • 


  • scale_y_discrete(): discrete y
    • 


  • coord_cartesian(ylim): zoom only
    • 


  • expand / expansion(): control axis padding
    • 





FAQ



What does scale_y_continuous do in ggplot2?



scale_y_continuous() customizes the Y axis when y is continuous numeric: breaks, labels, limits, transformations.



How do I add a secondary y axis?



Pass sec.axis = sec_axis(~ . / 100, name = "..."). The transformation must be linear.



What is the difference between scale_y_continuous limits and coord_cartesian?



limits drops data outside. coord_cartesian zooms only. Use coord_cartesian for stats integrity.



How do I format y as dollars?



scale_y_continuous(labels = scales::dollar). Use comma, percent similarly.



Can I log-transform with scale_y_continuous?



Yes: scale_y_continuous(trans = "log10"). Or use scale_y_log10() as a shortcut.



          

        


        
      


      

        

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

        

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