Find which interval row in a data frame that each element of a vector belongs in

Question

I have a vector of numeric elements, and a dataframe with two columns that define the start and end points of intervals. Each row in the dataframe is one interval. I want to find out which interval each element in the vector belongs to.

Here's some example data:

# Find which interval that each element of the vector belongs in

    library(tidyverse)
    elements <- c(0.1, 0.2, 0.5, 0.9, 1.1, 1.9, 2.1)

    intervals <-  frame_data(~phase, ~start, ~end,
                               "a",     0,     0.5,
                               "b",     1,     1.9,
                               "c",     2,     2.5)

The same example data for those who object to the tidyverse:

elements <- c(0.1, 0.2, 0.5, 0.9, 1.1, 1.9, 2.1)

intervals <- structure(list(phase = c("a", "b", "c"), 
                            start = c(0, 1, 2), 
                            end = c(0.5, 1.9, 2.5)), 
                       .Names = c("phase", "start", "end"), 
                       row.names = c(NA, -3L), 
                       class = "data.frame")

Here's one way to do it:

    library(intrval) 
    phases_for_elements <- 
    map(elements, ~.x %[]% data.frame(intervals[, c('start', 'end')])) %>% 
      map(., ~unlist(intervals[.x, 'phase'])) 

Here's the output:

    [[1]]
    phase 
      "a" 

    [[2]]
    phase 
      "a" 

    [[3]]
    phase 
      "a" 

    [[4]]
    character(0)

    [[5]]
    phase 
      "b" 

    [[6]]
    phase 
      "b" 

    [[7]]
    phase 
      "c" 

But I'm looking for a simpler method with less typing. I've seen findInterval in related questions, but I'm not sure how I can use it in this situation.

Answer 1

David Arenburg's mention of non-equi joins was very helpful for understanding what general kind of problem this is (thanks!). I can see now that it's not implemented for dplyr. Thanks to this answer, I see that there is a fuzzyjoin package that can do it in the same idiom. But it's barely any simpler than my map solution above (though more readable, in my view), and doesn't hold a candle to thelatemail's cut answer for brevity.

For my example above, the fuzzyjoin solution would be

library(fuzzyjoin)
library(tidyverse)

fuzzy_left_join(data.frame(elements), intervals, 
                by = c("elements" = "start", "elements" = "end"), 
                match_fun = list(`>=`, `<=`)) %>% 
  distinct()

Which gives:

    elements phase start end
1      0.1     a     0   0.5
2      0.2     a     0   0.5
3      0.5     a     0   0.5
4      0.9  <NA>    NA    NA
5      1.1     b     1   1.9
6      1.9     b     1   1.9
7      2.1     c     2   2.5

Answer 2

Here is kind of a "one-liner" which (mis-)uses foverlaps from the data.table package but David's non-equi join is still more concise:

library(data.table) #v1.10.0
foverlaps(data.table(start = elements, end = elements), 
          setDT(intervals, key = c("start", "end")))
#   phase start end i.start i.end
#1:     a     0 0.5     0.1   0.1
#2:     a     0 0.5     0.2   0.2
#3:     a     0 0.5     0.5   0.5
#4:    NA    NA  NA     0.9   0.9
#5:     b     1 1.9     1.1   1.1
#6:     b     1 1.9     1.9   1.9
#7:     c     2 2.5     2.1   2.1