A colleague came to my office the other day with an interesting question:

Is there a way in R to find the closest number to X in a list?

I knowing full well the power the power of R, I naturally said that surely there is such a function, but I have never used it. So I set out to find it because I am curious. It turns out there is not an of the shelf closest function. There are however a few solution out there which I have collected and are bellow. To top it off there is a comparison of how fast each solution is.

solution 1

Source

x=c(1:10^6)
your.number=90000.43
which(abs(x-your.number)==min(abs(x-your.number)))

## [1] 90000

solution 2

Same source as before.

which.min(abs(x-your.number))

## [1] 90000

solution 3

From here. It requires data.table

install.packages("data.table")

## Installing package into '/home/adomingu/R/x86_64-pc-linux-gnu-library/3.2'
## (as 'lib' is unspecified)

## Error in contrib.url(repos, type): trying to use CRAN without setting a mirror

library(data.table)
dt = data.table(x, val = x) # you'll see why val is needed in a sec
setattr(dt, "sorted", "x")  # let data.table know that w is sorted
setkey(dt, x) # sorts the data

# binary search and "roll" to the nearest neighbour
# In the final expression the val column will have the you're looking for.
dt[J(your.number), roll = "nearest"]

##        x   val
## 1: 90000 90000

Speed comparison

## time:
# solution1
system.time(which(abs(x-your.number)==min(abs(x-your.number))))

##    user  system elapsed 
##   0.024   0.020   0.043

# solution2
system.time(which.min(abs(x-your.number)))

##    user  system elapsed 
##   0.008   0.004   0.012

# solution3
system.time(dt[J(your.number), roll = "nearest"])

##    user  system elapsed 
##   0.000   0.000   0.001

To my surprise the base R functions perform pretty well, though in really large datasets data.table is worth a punt.