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ggplot2 geom_path() in R: Connect Points in Data Order

The geom_path() function in ggplot2 connects points with line segments in DATA ROW ORDER (not sorted by x). It is the right tool for trajectory plots, paths, and any sequence where order matters.

By Selva Prabhakaran  ·  Published May 12, 2026  ·  Last updated May 12, 2026
⚡ Quick Answer
ggplot(df, aes(x, y)) + geom_path()
ggplot(df, aes(x, y, color = step)) + geom_path()
geom_line()                              # different: sorts by x first
geom_path(arrow = arrow())               # add arrow at end

Need explanation? Read on for examples and pitfalls.

📊 Is geom_path() the right tool?
START2D trajectory in time ordergeom_path()traditional line plot (sorted x)geom_line()step functiongeom_step()closed polygongeom_polygon()

What geom_path() does in one sentence

geom_path() connects points with line segments in the ORDER they appear in the data. Unlike geom_line (which sorts by x first), geom_path respects row order.

Syntax

geom_path(mapping = NULL, data = NULL, lineend = "butt", linejoin = "round", linemitre = 10, arrow = NULL, ...).

Run live
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RRandom walk trajectory
library(ggplot2) set.seed(1) df <- tibble( step = 1:50, x = cumsum(rnorm(50)), y = cumsum(rnorm(50)) ) ggplot(df, aes(x, y)) + geom_path()

  

  





Tip
Use geom_path for spatial trajectories, animation paths, and any data where the connection order matters. Use geom_line for traditional trends.



Five common patterns



1. Random walk




  

    
R2D trajectory

    
df <- tibble(
  step = 1:100,
  x = cumsum(rnorm(100)),
  y = cumsum(rnorm(100))
)
ggplot(df, aes(x, y)) +
  geom_path()

    

      
      
    

    

  

  





2. Color by step




  

    
RShow progression

    
ggplot(df, aes(x, y, color = step)) +
  geom_path()

    

      
      
    

    

  

  





3. With arrow




  

    
RMark direction

    
ggplot(df, aes(x, y)) +
  geom_path(arrow = arrow(length = unit(0.3, "cm")))

    

      
      
    

    

  

  





4. Multiple paths (groups)




  

    
RPer-group trajectories

    
ggplot(df, aes(x, y, group = trial, color = trial)) +
  geom_path()

    

      
      
    

    

  

  





5. Closed loop




  

    
RConnect last to first

    
df_closed <- bind_rows(df, df[1, ])  # repeat first row
ggplot(df_closed, aes(x, y)) +
  geom_path()

    

      
      
    

    

  

  





Key Insight
geom_path is for SEQUENCED data where the order between points matters. geom_line sorts internally, so it's wrong for trajectories where the path crosses itself.



geom_path() vs geom_line() vs geom_step()







Function
Order
Best for






geom_path()
Row order
Trajectories, paths




geom_line()
Sorted by x
Traditional trends




geom_step()
Row order with steps
Piecewise-constant




geom_polygon()
Closed loop
Filled shapes







A practical workflow



Use geom_path for time-series with non-monotonic x.




  

    
RInteractive R

    
ggplot(market_data, aes(volatility, return, color = date)) +
  geom_path() +
  geom_point()

    

      
      
    

    

  

  





Plot return vs volatility over time; the PATH shows how each point connects chronologically.



Common pitfalls



Pitfall 1: confusing geom_path with geom_line. geom_path keeps row order; geom_line sorts. For trajectories with non-monotonic x, geom_line is WRONG.



Pitfall 2: forgetting to arrange data. geom_path follows row order. If you want chronological order, arrange by timestamp first.



Warning
geom_path() does NOT close the polygon. First and last points are not connected. To close, append the first row to the end before plotting.



Try it yourself





Try it: Plot a 2D random walk path with color showing step. Save to ex_plot.



  

    
RYour turn: random walk

    
set.seed(42)
df <- tibble(step = 1:50, x = cumsum(rnorm(50)), y = cumsum(rnorm(50)))

ex_plot <- df |>
  # your code here

    

      
      
    

    

  

  





Click to reveal solution



  

    
RSolution

    
ex_plot <- ggplot(df, aes(x, y, color = step)) +
  geom_path()

    

      
      
    

    

  

  





Explanation: geom_path connects points in row (= step) order; color gradient shows direction.










After mastering geom_path, look at:



    


  • geom_line(): sorted by x
    • 


  • geom_step(): piecewise-constant
    • 


  • geom_polygon(): closed shape
    • 


  • geom_segment(): explicit segments
    • 


  • arrow(): add direction markers
    • 





FAQ



What does geom_path do in ggplot2?



geom_path() connects points with line segments in DATA ROW ORDER. Unlike geom_line, it does not sort by x.



What is the difference between geom_path and geom_line?



geom_path keeps row order. geom_line sorts by x. For trajectories or non-monotonic x, geom_path is correct.



How do I add an arrow to geom_path?



Pass arrow = arrow(length = unit(0.3, "cm")): geom_path(arrow = arrow()). An arrowhead appears at the end.



Does geom_path close polygons?



No. First and last points are NOT connected. For closed loops, append the first row to the end of the data before plotting (or use geom_polygon).



Can I use geom_path for time-series?



Yes, especially when (x, y) are both varying and the chronological order matters. For x = time, y = value with monotonic time, geom_line is fine.



          

        


        
      


      

        

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

        

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