Examine if one value in a column matches values in a list

General
1

I'm trying to compare a column of a dataframe and see if the number in that dataframe matches one of a set of values in a list:

df$column is a range of numerical values, about 4000 rows.
comparisonlist = list of 100 or so values

I want to create a check variable that flips to 1 for a row if the value of column in that specific row matches one of the 100 numbers in comparisonlist, but I need to be able to compare column to comparisonlist for it to work properly.

I've tried various iterations of column %in% comparisonlist, but it always returns a value of FALSE, even when it should be matching. I've tried coding both as characters and it still returns FALSE every time.

Any guidance to what I'm doing wrong?

Thanks!

2

Is this what you want (other than the problem dimensions)?

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
df <- data.frame(vals = 1:10)
comparisonlist <- c(3, 5, 7)
df <- df |> rowwise() |> mutate(vals %in% comparisonlist)

Created on 2025-11-04 with reprex v2.1.1

3

Such tasks are often approached with a join, using dplyr::starwars as an example and comparing comparisonlist against sw$mass:

library(dplyr, warn.conflicts = FALSE)
( sw <- 
  starwars |> 
  select(name, height, mass)
)
#> # A tibble: 87 × 3
#>    name               height  mass
#>    <chr>               <int> <dbl>
#>  1 Luke Skywalker        172    77
#>  2 C-3PO                 167    75
#>  3 R2-D2                  96    32
#>  4 Darth Vader           202   136
#>  5 Leia Organa           150    49
#>  6 Owen Lars             178   120
#>  7 Beru Whitesun Lars    165    75
#>  8 R5-D4                  97    32
#>  9 Biggs Darklighter     183    84
#> 10 Obi-Wan Kenobi        182    77
#> # ℹ 77 more rows

comparisonlist <- c(32, 49)

( cl <- tibble(comparisonlist, in_comp_list = TRUE) )
#> # A tibble: 2 × 2
#>   comparisonlist in_comp_list
#>            <dbl> <lgl>       
#> 1             32 TRUE        
#> 2             49 TRUE

left_join(sw, cl, by = join_by(mass == comparisonlist )) |> 
  # missing matches result with NAs, turn those to FALSE with coalesce()
  mutate(in_comp_list = coalesce(in_comp_list, FALSE))
#> # A tibble: 87 × 4
#>    name               height  mass in_comp_list
#>    <chr>               <int> <dbl> <lgl>       
#>  1 Luke Skywalker        172    77 FALSE       
#>  2 C-3PO                 167    75 FALSE       
#>  3 R2-D2                  96    32 TRUE        
#>  4 Darth Vader           202   136 FALSE       
#>  5 Leia Organa           150    49 TRUE        
#>  6 Owen Lars             178   120 FALSE       
#>  7 Beru Whitesun Lars    165    75 FALSE       
#>  8 R5-D4                  97    32 TRUE        
#>  9 Biggs Darklighter     183    84 FALSE       
#> 10 Obi-Wan Kenobi        182    77 FALSE       
#> # ℹ 77 more rows

Or you could loop through all values of df$column (sw$mass in this example) with sapply() or purrr::map_lgl() to use %in% and get a logical vector as a result:

sw$in_list <- sapply(sw$mass, \(x) x %in% cl$comparisonlist)
sw
#> # A tibble: 87 × 4
#>    name               height  mass in_list
#>    <chr>               <int> <dbl> <lgl>  
#>  1 Luke Skywalker        172    77 FALSE  
#>  2 C-3PO                 167    75 FALSE  
#>  3 R2-D2                  96    32 TRUE   
#>  4 Darth Vader           202   136 FALSE  
#>  5 Leia Organa           150    49 TRUE   
#>  6 Owen Lars             178   120 FALSE  
#>  7 Beru Whitesun Lars    165    75 FALSE  
#>  8 R5-D4                  97    32 TRUE   
#>  9 Biggs Darklighter     183    84 FALSE  
#> 10 Obi-Wan Kenobi        182    77 FALSE  
#> # ℹ 77 more rows

By any chance, do you happen to work with floating-point numbers? Just in case, you do know that printed value may not match the object value? E.g. when a and b are both printed as 1, equality is not granted:

a <- 1 
b <- 1 + 1e-7 
print(c(a, b))
#> [1] 1 1
a == b
#> [1] FALSE
dput(b)
#> 1.0000001

And you should not expect something like 0.3 / 3 == 0.1 to yield TRUE, e.g.:

( a <- 0.3 / 3 )
#> [1] 0.1
( b <- 0.1 ) 
#> [1] 0.1
a == b
#> [1] FALSE
a - b
#> [1] -1.387779e-17

The same applies for %in% and equality joins ( join_by(a == b )), so you may need to use rounding, comparison with tolerance (e.g. dplyr::near() instead of %in%) or rolling / overlap join instead of equality join ( you can check ?dplyr::join_by for examples).