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data.table::merge()
wrapper
library(joyn)
library(data.table)
x1 = data.table(id = c(1L, 1L, 2L, 3L, NA_integer_),
t = c(1L, 2L, 1L, 2L, NA_integer_),
x = 11:15)
y1 = data.table(id = c(1,2, 4),
y = c(11L, 15L, 16))
x2 = data.table(id1 = c(1, 1, 2, 3, 3),
id2 = c(1, 1, 2, 3, 4),
t = c(1L, 2L, 1L, 2L, NA_integer_),
x = c(16, 12, NA, NA, 15))
y2 = data.table(id = c(1, 2, 5, 6, 3),
id2 = c(1, 1, 2, 3, 4),
y = c(11L, 15L, 20L, 13L, 10L),
x = c(16:20))
This vignette describes the use of the joyn
merge() function.
🔀 joyn::merge resembles the usability of
base::merge and data.table::merge, while also
incorporating the additional features that characterize
joyn. In fact, joyn::merge masks the other
two.
Suppose you want to merge x1 and y1. First
notice that while base::merge is principally for data
frames, joyn::merge coerces x and
y to data tables if they are not already.
By default, merge will join by the shared column name(s)
in x and y.
# Example not specifying the key
merge(x = x1,
y = y1)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> <char> <int> <char>
#> 1: x & y 3 100%
#> 2: total 3 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ ❯ Joyn's report available in variable .joyn
#> ℹ ❯ Removing key variables id from id and y
#> ⚠ Warning: The keys supplied uniquely identify y therefore a m:1 join is
#> executed.
#> Key: <id>
#> id t x y .joyn
#> <num> <int> <int> <num> <char>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & y
# Example specifying the key
merge(x = x1,
y = y1,
by = "id")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> <char> <int> <char>
#> 1: x & y 3 100%
#> 2: total 3 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ ❯ Joyn's report available in variable .joyn
#> ℹ ❯ Removing key variables id from id and y
#> ⚠ Warning: The keys supplied uniquely identify y therefore a m:1 join is
#> executed.
#> Key: <id>
#> id t x y .joyn
#> <num> <int> <int> <num> <char>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & yAs usual, if the columns you want to join by don’t have the same
name, you need to tell merge which columns you want to join
by: by.x for the x data frame column name,
and by.y for the y one. For example,
df1 <- data.frame(id = c(1L, 1L, 2L, 3L, NA_integer_, NA_integer_),
t = c(1L, 2L, 1L, 2L, NA_integer_, 4L),
x = 11:16)
df2 <- data.frame(id = c(1,2, 4, NA_integer_, 8),
y = c(11L, 15L, 16, 17L, 18L),
t = c(13:17))
merge(x = df1,
y = df2,
by.x = "x",
by.y = "y")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> <char> <int> <char>
#> 1: x & y 3 100%
#> 2: total 3 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ ❯ Joyn's report available in variable .joyn
#> ℹ ❯ Removing key variables keyby1 from id, keyby1, and t
#> ⚠ Warning: The keys supplied uniquely identify both x and y therefore a 1:1
#> join is executed.
#> x id.x t.x id.y t.y .joyn
#> 1 11 1 1 1 13 x & y
#> 2 15 NA NA 2 14 x & y
#> 3 16 NA 4 4 15 x & yBy default, sort is TRUE, so that the
merged table will be sorted by the by.x column. Notice that
the output table distinguishes non-by column t coming from
x from the one coming from y by adding the
.x and .y suffixes -which occurs because the
no.dups argument is set to TRUE by
default.
In a similar fashion as the joyn() primary function
does, merge() offers a number of arguments to
verify/control the merge1.
For example, joyn::joyn allows to execute one-to-one,
one-to-many, many-to-one and many-to-many joins. Similarly,
merge accepts the match_type argument:
# Example with many to many merge
joyn::merge(x = x2,
y = y2,
by.x = "id1",
by.y = "id2",
match_type = "m:m")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> <char> <int> <char>
#> 1: x & y 7 100%
#> 2: total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ ❯ Joyn's report available in variable .joyn
#> ℹ ❯ Removing key variables keyby1 from id, keyby1, y, and x
#> ⚠ Warning: Supplied both by and by.x/by.y. by argument will be ignored.
#> Key: <id1>
#> id1 id2 t x.x id y x.y .joyn
#> <num> <num> <int> <num> <num> <int> <int> <char>
#> 1: 1 1 1 16 1 11 16 x & y
#> 2: 1 1 1 16 2 15 17 x & y
#> 3: 1 1 2 12 1 11 16 x & y
#> 4: 1 1 2 12 2 15 17 x & y
#> 5: 2 2 1 NA 5 20 18 x & y
#> 6: 3 3 2 NA 6 13 19 x & y
#> 7: 3 4 NA 15 6 13 19 x & y
# Example with many to many merge
joyn::merge(x = x1,
y = y1,
by = "id",
match_type = "m:1")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> <char> <int> <char>
#> 1: x & y 3 100%
#> 2: total 3 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ ❯ Joyn's report available in variable .joyn
#> ℹ ❯ Removing key variables id from id and y
#> ⚠ Warning: Supplied both by and by.x/by.y. by argument will be ignored.
#> Key: <id>
#> id t x y .joyn
#> <num> <int> <int> <num> <char>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & yIn a similar way, you can exploit all the other additional options
available in joyn(), e.g., for keeping common variables,
updating NAs and values, displaying messages etc…, which you can explore
in the “Advanced functionalities” article.
See the “Advanced functionalities” article for more details↩︎
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.