Last chance! 50% off unlimited learning
Sale ends in
Fast merge of two data.tables. The data.table method behaves
very similarly to that of data.frames except that, by default, it attempts to merge
at first based on the shared key columns, and if there are none,
then based on key columns of the first argument x, and if there
are none,
then based on the common columns between the two data.tables.
Set the by, or by.x and by.y arguments explicitly to override this default.
# S3 method for data.table
merge(x, y, by = NULL, by.x = NULL, by.y = NULL, all = FALSE,
all.x = all, all.y = all, sort = TRUE, suffixes = c(".x", ".y"), no.dups = TRUE,
allow.cartesian=getOption("datatable.allow.cartesian"), # default FALSE
…)data tables. y is coerced to a data.table if
it isn't one already.
A vector of shared column names in x and y to merge on.
This defaults to the shared key columns between the two tables.
If y has no key columns, this defaults to the key of x.
Vectors of column names in x and y to merge on.
logical; all = TRUE is shorthand to save setting both
all.x = TRUE and all.y = TRUE.
logical; if TRUE, then extra rows will be added to the
output, one for each row in x that has no matching row in y.
These rows will have 'NA's in those columns that are usually filled with values
from y. The default is FALSE, so that only rows with data from both
x and y are included in the output.
logical; analogous to all.x above.
logical. If TRUE (default), the merged data.table is
sorted by setting the key to the by / by.x columns. If FALSE, the
result is not sorted.
A character(2) specifying the suffixes to be used for
making non-by column names unique. The suffix behaviour works in a similar
fashion as the merge.data.frame method does.
logical indicating that suffixes are also appended to
non-by.y column names in y when they have the same column name
as any by.x.
See allow.cartesian in [.data.table.
Not used at this time.
A new data.table based on the merged data tables, and sorted by the
columns set (or inferred for) the by argument if argument sort is
set to TRUE.
merge is a generic function in base R. It dispatches to either the
merge.data.frame method or merge.data.table method depending on
the class of its first argument. Note that, unlike SQL, NA is
matched against NA (and NaN against NaN) while merging.
In versions <= v1.9.4, if the specified columns in by were not the
key (or head of the key) of x or y, then a copy is
first re-keyed prior to performing the merge. This was less performant as well as memory
inefficient. The concept of secondary keys (implemented in v1.9.4) was
used to overcome this limitation from v1.9.6+. No deep copies are made
any more, thereby improving performance and memory efficiency. Also, there is better
control for providing the columns to merge on with the help of the newly implemented
by.x and by.y arguments.
For a more data.table-centric way of merging two data.tables, see
[.data.table; e.g., x[y, …]. See FAQ 1.11 for a detailed
comparison of merge and x[y, …].
If any column names provided to by.x also occur in names(y) but not in by.y,
then this data.table method will add the suffixes to those column names. As of
R v3.4.3, the data.frame method will not (leading to duplicate column names in the result) but a patch has
been proposed (see r-devel thread here)
which is looking likely to be accepted for a future version of R.
# NOT RUN {
(dt1 <- data.table(A = letters[1:10], X = 1:10, key = "A"))
(dt2 <- data.table(A = letters[5:14], Y = 1:10, key = "A"))
merge(dt1, dt2)
merge(dt1, dt2, all = TRUE)
(dt1 <- data.table(A = letters[rep(1:3, 2)], X = 1:6, key = "A"))
(dt2 <- data.table(A = letters[rep(2:4, 2)], Y = 6:1, key = "A"))
merge(dt1, dt2, allow.cartesian=TRUE)
(dt1 <- data.table(A = c(rep(1L, 5), 2L), B = letters[rep(1:3, 2)], X = 1:6, key = "A,B"))
(dt2 <- data.table(A = c(rep(1L, 5), 2L), B = letters[rep(2:4, 2)], Y = 6:1, key = "A,B"))
merge(dt1, dt2)
merge(dt1, dt2, by="B", allow.cartesian=TRUE)
# test it more:
d1 <- data.table(a=rep(1:2,each=3), b=1:6, key="a,b")
d2 <- data.table(a=0:1, bb=10:11, key="a")
d3 <- data.table(a=0:1, key="a")
d4 <- data.table(a=0:1, b=0:1, key="a,b")
merge(d1, d2)
merge(d2, d1)
merge(d1, d2, all=TRUE)
merge(d2, d1, all=TRUE)
merge(d3, d1)
merge(d1, d3)
merge(d1, d3, all=TRUE)
merge(d3, d1, all=TRUE)
merge(d1, d4)
merge(d1, d4, by="a", suffixes=c(".d1", ".d4"))
merge(d4, d1)
merge(d1, d4, all=TRUE)
merge(d4, d1, all=TRUE)
# new feature, no need to set keys anymore
set.seed(1L)
d1 <- data.table(a=sample(rep(1:3,each=2)), z=1:6)
d2 <- data.table(a=2:0, z=10:12)
merge(d1, d2, by="a")
merge(d1, d2, by="a", all=TRUE)
# new feature, using by.x and by.y arguments
setnames(d2, "a", "b")
merge(d1, d2, by.x="a", by.y="b")
merge(d1, d2, by.x="a", by.y="b", all=TRUE)
merge(d2, d1, by.x="b", by.y="a")
# }
Run the code above in your browser using DataLab