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tidyr unchop() in R: Expand Vector List Column Into Rows

The unchop() function in tidyr expands vector list-columns into multiple rows; each element of each vector becomes a row. It is the opposite of chop().

By Selva Prabhakaran  ·  Published May 12, 2026  ·  Last updated May 12, 2026
⚡ Quick Answer
df |> unchop(col)                       # vectors to rows
df |> unchop(c(col1, col2))              # multiple parallel cols
df |> unchop(col, keep_empty = TRUE)    # preserve empty cells
df |> unnest_longer(col)                  # similar; alternative

Need explanation? Read on for examples and pitfalls.

📊 Is unchop() the right tool?
STARTvector list-col -> rowsunchop()tibble list-col -> rowsunnest()vector list-col -> rows with indexunnest_longer(indices_to)preserve empty cellskeep_empty = TRUE

What unchop() does in one sentence

unchop(data, cols, keep_empty = FALSE) expands a vector list-column into multiple rows; each element becomes its own row. Other columns are duplicated.

Syntax

unchop(data, cols, keep_empty = FALSE, ptype = NULL). cols are list columns to expand.

Run live
Run live, no install needed. Every R block on this page runs in your browser. Click Run, edit the code, re-run instantly. No setup.
RRound-trip chop/unchop
library(tidyr) library(dplyr) library(purrr) df <- tibble(g = c("a","b"), v = list(c(1,2,3), c(4,5))) df |> unchop(v) #> g v #> 1 a 1 #> 2 a 2 #> 3 a 3 #> 4 b 4 #> 5 b 5

  

  





Tip
unchop and unnest_longer are nearly identical for vector list-cols. unchop is older; unnest_longer is the unified family.



Five common patterns



1. Standard unchop




  

    
RVector list -> rows

    
df |> unchop(v)

    

      
      
    

    

  

  





2. Multiple parallel list-cols




  

    
RTwo list-cols expanded together

    
df <- tibble(g = "a", v = list(c(1,2)), w = list(c(10,20)))
df |> unchop(c(v, w))
#>   g v  w
#> 1 a 1 10
#> 2 a 2 20

    

      
      
    

    

  

  





3. Keep empty cells




  

    
RPreserve as NA rows

    
df <- tibble(g = c("a","b","c"), v = list(c(1,2), integer(0), c(3)))
df |> unchop(v, keep_empty = TRUE)

    

      
      
    

    

  

  





4. Round-trip




  

    
Rchop then unchop

    
df_orig <- tibble(g = c("a","a","b"), v = c(1, 2, 3))
df_orig |> chop(v) |> unchop(v) |> identical(df_orig)

    

      
      
    

    

  

  





5. unnest_longer alternative




  

    
RBoth work for vector list cols

    
df |> unchop(v)
df |> unnest_longer(v)

    

      
      
    

    

  

  





Key Insight
**unchop and unnest_longer are functionally similar for vector list-cols.* unchop predates the unnest_ family; both are still maintained. For new code, the tidyr team recommends unnest_longer for consistency.



unchop() vs unnest_longer() vs unnest()







Function
Input
Output
Status






unchop(col)
Vector list-col
Rows
Active, older




unnest_longer(col)
Vector list-col
Rows
Active, newer (preferred)




unnest(col)
Tibble list-col
Rows
Active







For vector list-cols, prefer unnest_longer for consistency with the rest of the family.



A practical workflow



Use unchop for round-tripping with chop().




  

    
RInteractive R

    
df |>
  chop(v) |>
  mutate(processed = purrr::map(v, scale)) |>
  unchop(processed)

    

      
      
    

    

  

  





Process each group's vectors; unchop back to long form.



Common pitfalls



Pitfall 1: empty cells dropped. Default keep_empty = FALSE. Pass TRUE to preserve as NA rows.



Pitfall 2: parallel list-cols must align. unchop(c(v, w)) requires v and w to have same length per cell.



Warning
unchop() is older than unnest_longer(); for new code, prefer unnest_longer. Both work; consistency favors unnest_longer.



Try it yourself





Try it: Unchop a vector list-col and count rows. Save to ex_long.



  

    
RYour turn: unchop

    
df <- tibble(g = c("a","b"), v = list(c(1,2,3), c(4,5)))

ex_long <- df |>
  # your code here

nrow(ex_long)
#> Expected: 5

    

      
      
    

    

  

  





Click to reveal solution



  

    
RSolution

    
ex_long <- df |> unchop(v)

nrow(ex_long)
#> [1] 5

    

      
      
    

    

  

  





Explanation: unchop expands the vectors; total = 3 + 2 = 5 rows.










After mastering unchop, look at:



    


  • chop(): opposite (rows to vector list-col)
    • 


  • unnest_longer(): equivalent for vector list-cols
    • 


  • unnest(): for tibble list-cols
    • 


  • nest() / unnest(): tibble versions
    • 





FAQ



What does unchop do in tidyr?



unchop(data, col) expands a vector list-column into multiple rows. Each element becomes a row.



What is the difference between unchop and unnest_longer?



Functionally similar for vector list-cols. unchop is older; unnest_longer is part of the unified unnest family. Prefer unnest_longer for new code.



How do I keep empty cells with unchop?



Pass keep_empty = TRUE. Empty list cells become NA rows.



Is unchop deprecated?



No. It is still active. unnest_longer is preferred for consistency but both work.



How do I unchop multiple list-cols at once?



unchop(c(col1, col2)). Both must have the same vector length per cell.



          

        


        
      


      

        

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

        

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