between.Rd
Intended for use in i
in [.data.table
.
between
is equivalent to lower<=x & x<=upper
when
incbounds=TRUE
, or lower<x & y<upper
when FALSE
. With a caveat that
NA
in lower
or upper
are taken as unlimited bounds not NA
.
This can be changed by setting NAbounds
to NA
.
inrange
checks whether each value in x
is in between any of
the intervals provided in lower,upper
.
between(x, lower, upper, incbounds=TRUE, NAbounds=TRUE, check=FALSE)
x %between% y
inrange(x, lower, upper, incbounds=TRUE)
x %inrange% y
Any orderable vector, i.e., those with relevant methods for
`<=`
, such as numeric
, character
, Date
, etc. in
case of between
and a numeric vector in case of inrange
.
Lower range bound. Either length 1 or same length as x
.
Upper range bound. Either length 1 or same length as x
.
A length-2 vector
or list
, with y[[1]]
interpreted as lower
and y[[2]]
as upper
.
TRUE
means inclusive bounds, i.e., [lower,upper].
FALSE
means exclusive bounds, i.e., (lower,upper).
It is set to TRUE
by default for infix notations.
If lower
(upper
) contains an NA
what should lower<=x
(x<=upper
) return? By default TRUE
so that a missing bound is interpreted as unlimited.
Produce error if any(lower>upper)
? FALSE
by default for efficiency, in particular type character
.
non-equi joins were implemented in v1.9.8
. They extend
binary search based joins in data.table
to other binary operators
including >=, <=, >, <
. inrange
makes use of this new
functionality and performs a range join.
Logical vector the same length as x
with value TRUE
for those
that lie within the specified range.
Current implementation does not make use of ordered keys for
%between%
.
X = data.table(a=1:5, b=6:10, c=c(5:1))
X[b %between% c(7,9)]
#> a b c
#> <int> <int> <int>
#> 1: 2 7 4
#> 2: 3 8 3
#> 3: 4 9 2
X[between(b, 7, 9)] # same as above
#> a b c
#> <int> <int> <int>
#> 1: 2 7 4
#> 2: 3 8 3
#> 3: 4 9 2
# NEW feature in v1.9.8, vectorised between
X[c %between% list(a,b)]
#> a b c
#> <int> <int> <int>
#> 1: 1 6 5
#> 2: 2 7 4
#> 3: 3 8 3
X[between(c, a, b)] # same as above
#> a b c
#> <int> <int> <int>
#> 1: 1 6 5
#> 2: 2 7 4
#> 3: 3 8 3
X[between(c, a, b, incbounds=FALSE)] # open interval
#> a b c
#> <int> <int> <int>
#> 1: 1 6 5
#> 2: 2 7 4
# inrange()
Y = data.table(a=c(8,3,10,7,-10), val=runif(5))
range = data.table(start = 1:5, end = 6:10)
Y[a %inrange% range]
#> a val
#> <num> <num>
#> 1: 8 0.6830724
#> 2: 3 0.3182244
#> 3: 10 0.1347508
#> 4: 7 0.9432908
Y[inrange(a, range$start, range$end)] # same as above
#> a val
#> <num> <num>
#> 1: 8 0.6830724
#> 2: 3 0.3182244
#> 3: 10 0.1347508
#> 4: 7 0.9432908
Y[inrange(a, range$start, range$end, incbounds=FALSE)] # open interval
#> a val
#> <num> <num>
#> 1: 8 0.6830724
#> 2: 3 0.3182244
#> 3: 7 0.9432908