A Table is a sequence of chunked arrays. They have a similar interface to record batches, but they can be composed from multiple record batches or chunked arrays.
arrow_table(..., schema = NULL)
a Schema, or
Tables are data-frame-like, and many methods you expect to work on
data.frame are implemented for
Table. This includes
tail. You can also pull
the data from an Arrow table into R with
as.data.frame(). See the
A caveat about the
$ method: because
Table is an
$ is also used to access the object's methods (see below). Methods take
precedence over the table's columns. So,
tab$Slice would return the
"Slice" method function even if there were a column in the table called
In addition to the more R-friendly S3 methods, a
Table object has
the following R6 methods that map onto the underlying C++ methods:
$column(i): Extract a
ChunkedArray by integer position from the table
$ColumnNames(): Get all column names (called by
$nbytes(): Total number of bytes consumed by the elements of the table
$RenameColumns(value): Set all column names (called by
names(tab) <- value)
$GetColumnByName(name): Extract a
ChunkedArray by string name
$field(i): Extract a
Field from the table schema by integer position
$SelectColumns(indices): Return new
Table with specified columns, expressed as 0-based integers.
$Slice(offset, length = NULL): Create a zero-copy view starting at the
indicated integer offset and going for the given length, or to the end
of the table if
NULL, the default.
$Take(i): return an
Table with rows at positions given by
i is an Arrow
ChunkedArray, it will be
coerced to an R vector before taking.
$Filter(i, keep_na = TRUE): return an
Table with rows at positions where logical
vector or Arrow boolean-type
$SortIndices(names, descending = FALSE): return an
Array of integer row
positions that can be used to rearrange the
Table in ascending or descending
order by the first named column, breaking ties with further named columns.
descending can be a logical vector of length one or of the same length as
$serialize(output_stream, ...): Write the table to the given
$cast(target_schema, safe = TRUE, options = cast_options(safe)): Alter
the schema of the record batch.
There are also some active bindings:
$metadata: Returns the key-value metadata of the
Schema as a named list.
Modify or replace by assigning in (
tab$metadata <- new_metadata).
All list elements are coerced to string. See
schema() for more information.
$columns: Returns a list of
tbl <- arrow_table(name = rownames(mtcars), mtcars) dim(tbl) dim(head(tbl)) names(tbl) tbl$mpg tbl[["cyl"]] as.data.frame(tbl[4:8, c("gear", "hp", "wt")])
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