| Extract.data.frame {base} | R Documentation |
Extract or replace subsets of data frames.
x[i] x[i] <- value x[i, j, drop] x[i, j] <- value x[[i]] x[[i]] <- value x[[i, j]] x[[i, j]] <- value x$name x$name <- value
x |
data frame. |
i, j |
elements to extract or replace. i, j are
numeric or character or, for [ only, empty.
Numeric values are coerced to integer as if by as.integer.
For replacement by [, a logical matrix is allowed.
|
drop |
logical. If TRUE the result is coerced to the
lowest possible dimension. The default is to drop if only one
column is left, but not to drop if only one row is left. |
value |
A suitable replacement value: it will be repeated a whole
number of times if necessary and it may be coerced: see the
Coercion section. If NULL, deletes the column if a single
column is selected. |
name |
name or literal character string. |
Data frames can be indexed in several modes. When [ and
[[ are used with a single index, they index the data frame
as if it were a list. In this usage a drop argument is
ignored, with a warning. Using $ is equivalent to using
[[ with a single index.
When [ and [[ are used with two indices they act
like indexing a matrix: [[ can only be used to select one element.
If [ returns a data frame it will have unique (and non-missing)
row names, if necessary transforming the row names using
make.unique. Similarly, column names
will be transformed (if columns are selected more than once).
When drop =TRUE, this is applied to the subsetting of any
matrices contained in the data frame as well as to the data frame itself.
The replacement methods can be used to add whole column(s) by specifying non-existent column(s), in which case the column(s) are added at the right-hand edge of the data frame and numerical indices must be contiguous to existing indices. On the other hand, rows can be added at any row after the current last row, and the columns will be in-filled with missing values. Missing values in the indices are not allowed for replacement.
For [ the replacement value can be a list: each element of the
list is used to replace (part of) one column, recycling the list as
necessary. If columns specified by number are created, the names
(if any) of the corresponding list elements are used to name the
columns. If the replacement is not selecting rows, list values can
contain NULL elements which will cause the corresponding
columns to be deleted. (See the Examples.)
Matrixing indexing using [ is not recommended, and barely
supported. For extraction, x is first coerced to a matrix.
For replacement a logical matrix (only) can be used to select the
elements to be replaced in the same way as for a matrix.
For [ a data frame, list or a single column (the latter two
only when dimensions have been dropped). If matrix indexing is used for
extraction a matrix results.
For [[ a column of the data frame (extraction with one index)
or a length-one vector (extraction with two indices).
For [<-, [[<- and $<-, a data frame.
The story over when replacement values are coerced is a complicated one, and one that has changed during R's development. This section is a guide only.
When [ and [[ are used to add or replace a whole column,
no coercion takes place but value will be
replicated (by calling the generic function rep) to the
right length if an exact number of repeats can be used.
When [ is used with a logical matrix, each value is coerced to
the type of the column in which it is to be placed.
When [ and [[ are used with two indices, the
column will be coerced as necessary to accommodate the value.
Note that when the replacement value is an array (including a matrix)
it is not treated as a series of columns (as
data.frame and as.data.frame do) but
inserted as a single column.
The default behaviour when only one row is left is equivalent to
specifying drop = FALSE. To drop from a data frame to a list,
drop = TRUE has to be specified explicitly.
subset which is often easier for extraction,
data.frame, Extract.
sw <- swiss[1:5, 1:4] # select a manageable subset sw[1:3] # select columns sw[, 1:3] # same sw[4:5, 1:3] # select rows and columns sw[1] # a one-column data frame sw[, 1, drop = FALSE] # the same sw[, 1] # a (unnamed) vector sw[[1]] # the same sw[1,] # a one-row data frame sw[1,, drop=TRUE] # a list swiss[ c(1, 1:2), ] # duplicate row, unique row names are created sw[sw <= 6] <- 6 # logical matrix indexing sw ## adding a column sw["new1"] <- LETTERS[1:5] # adds a character column sw[["new2"]] <- letters[1:5] # ditto sw[, "new3"] <- LETTERS[1:5] # ditto sw$new4 <- 1:5 sapply(sw, class) sw$new4 <- NULL # delete the column sw sw[6:8] <- list(letters[10:14], NULL, aa=1:5) # delete col7, update 6, append sw ## matrices in a data frame A <- data.frame(x=1:3, y=I(matrix(4:6)), z=I(matrix(letters[1:9],3,3))) A[1:3, "y"] # a matrix A[1:3, "z"] # a matrix A[, "y"] # a matrix