subsetting | R Documentation |
Accessing columns, rows, or cells via $
, [[
, or [
is mostly similar to
regular data frames. However, the
behavior is different for tibbles and data frames in some cases:
[
always returns a tibble by default, even if
only one column is accessed.
Partial matching of column names with $
and [[
is not supported, and
NULL
is returned.
For $
, a warning is given.
Only scalars (vectors of length one) or vectors with the same length as the number of rows can be used for assignment.
Rows outside of the tibble's boundaries cannot be accessed.
When updating with [[<-
and [<-
, type changes of entire columns are
supported, but updating a part of a column requires that the new value is
coercible to the existing type.
See vec_slice()
for the underlying implementation.
Unstable return type and implicit partial matching can lead to surprises and
bugs that are hard to catch. If you rely on code that requires the original
data frame behavior, coerce to a data frame via as.data.frame()
.
## S3 method for class 'tbl_df'
x$name
## S3 method for class 'tbl_df'
x[[i, j, ..., exact = TRUE]]
## S3 method for class 'tbl_df'
x[i, j, drop = FALSE, ...]
## S3 replacement method for class 'tbl_df'
x$name <- value
## S3 replacement method for class 'tbl_df'
x[[i, j, ...]] <- value
## S3 replacement method for class 'tbl_df'
x[i, j, ...] <- value
x |
A tibble. |
name |
A name or a string. |
i, j |
Row and column indices. If |
... |
Ignored. |
exact |
Ignored, with a warning. |
drop |
Coerce to a vector if fetching one column via |
value |
A value to store in a row, column, range or cell. Tibbles are stricter than data frames in what is accepted here. |
For better compatibility with older code written for regular data frames,
[
supports a drop
argument which defaults to FALSE
.
New code should use [[
to turn a column into a vector.
df <- data.frame(a = 1:3, bc = 4:6)
tbl <- tibble(a = 1:3, bc = 4:6)
# Subsetting single columns:
df[, "a"]
tbl[, "a"]
tbl[, "a", drop = TRUE]
as.data.frame(tbl)[, "a"]
# Subsetting single rows with the drop argument:
df[1, , drop = TRUE]
tbl[1, , drop = TRUE]
as.list(tbl[1, ])
# Accessing non-existent columns:
df$b
tbl$b
df[["b", exact = FALSE]]
tbl[["b", exact = FALSE]]
df$bd <- c("n", "e", "w")
tbl$bd <- c("n", "e", "w")
df$b
tbl$b
df$b <- 7:9
tbl$b <- 7:9
df$b
tbl$b
# Identical behavior:
tbl[1, ]
tbl[1, c("bc", "a")]
tbl[, c("bc", "a")]
tbl[c("bc", "a")]
tbl["a"]
tbl$a
tbl[["a"]]
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