subset
Subsetting Vectors, Matrices and Data Frames
Return subsets of vectors, matrices or data frames which meet conditions.
 Keywords
 manip
Usage
subset(x, ...)
"subset"(x, subset, ...)
"subset"(x, subset, select, drop = FALSE, ...)
"subset"(x, subset, select, drop = FALSE, ...)
Arguments
 x
 object to be subsetted.
 subset
 logical expression indicating elements or rows to keep: missing values are taken as false.
 select
 expression, indicating columns to select from a data frame.
 drop
 passed on to
[
indexing operator.  ...
 further arguments to be passed to or from other methods.
Details
This is a generic function, with methods supplied for matrices, data frames and vectors (including lists). Packages and users can add further methods.
For ordinary vectors, the result is simply
x[subset & !is.na(subset)]
.
For data frames, the subset
argument works on the rows. Note
that subset
will be evaluated in the data frame, so columns can
be referred to (by name) as variables in the expression (see the examples).
The select
argument exists only for the methods for data frames
and matrices. It works by first replacing column names in the
selection expression with the corresponding column numbers in the data
frame and then using the resulting integer vector to index the
columns. This allows the use of the standard indexing conventions so
that for example ranges of columns can be specified easily, or single
columns can be dropped (see the examples).
The drop
argument is passed on to the indexing method for
matrices and data frames: note that the default for matrices is
different from that for indexing.
Factors may have empty levels after subsetting; unused levels are
not automatically removed. See droplevels
for a way to
drop all unused levels from a data frame.
Value

An object similar to x contain just the selected elements (for
a vector), rows and columns (for a matrix or data frame), and so on.
Warning
This is a convenience function intended for use interactively. For
programming it is better to use the standard subsetting functions like
[
, and in particular the nonstandard evaluation of
argument subset
can have unanticipated consequences.
See Also
Examples
library(base)
subset(airquality, Temp > 80, select = c(Ozone, Temp))
subset(airquality, Day == 1, select = Temp)
subset(airquality, select = Ozone:Wind)
with(airquality, subset(Ozone, Temp > 80))
## sometimes requiring a logical 'subset' argument is a nuisance
nm < rownames(state.x77)
start_with_M < nm %in% grep("^M", nm, value = TRUE)
subset(state.x77, start_with_M, Illiteracy:Murder)
# but in recent versions of R this can simply be
subset(state.x77, grepl("^M", nm), Illiteracy:Murder)
Community examples
# NOT RUN { subset(airquality, Temp > 80, select = c(Ozone, Temp)) subset(airquality, Day == 1, select = Temp) subset(airquality, select = Ozone:Wind) with(airquality, subset(Ozone, Temp > 80)) ## sometimes requiring a logical 'subset' argument is a nuisance nm < rownames(state.x77) start_with_M < nm %in% grep("^M", nm, value = TRUE) subset(state.x77, start_with_M, Illiteracy:Murder) # but in recent versions of R this can simply be subset(state.x77, grepl("^M", nm), Illiteracy:Murder) # }