✅ This vignette is dedicated to one specific feature of
joyn: displaying information through
messages.
We’ll start with a rough overview of the different kinds of messages that might be generated when merging two data tables, then discuss each of them in detail with representative examples.
Joyn messages can be of 4 different types:
Info
Timing
Warning
Error
# Checking available types of messages
msgs_types = joyn:::type_choices()
print(msgs_types)
#> [1] "info" "note" "warn" "timing" "err"Info messages are intended to inform you about various aspects of the join and the data tables involved, as you can see in the examples below.
Recall that one of the additional features of joyn is
that it returns a reporting variable with the status of the join.
Examples in this regard include info messages that tell you in which
variable it is available the joyn report, or if the
reporting variable is not returned instead.
Recall that one of the additional features of joyn is that it returns
a reporting variable with the status of the join.
Examples in this regard include info messages that tell you in which
variable it is available the joyn report, or if the
reporting variable is not returned instead. Also, an info message might
let you know that the name you want to assign to the reporting variable
is already present in the returning table, so that it will be changed to
a another one.
# Example dataframes
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(id = c(1, 4, 2, 3, NA),
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),
yd = c(1, 2, 5, 6, 3),
y = c(11L, 15L, 20L, 13L, 10L),
x = c(16:20))
x3 = 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))
y3 = data.table(id3 = c(1, 2, 5, 6, 3),
id4 = c(1, 1, 2, 3, 4),
y = c(11L, 15L, 20L, 13L, 10L),
z = c(16:20))
# ------------------- Showing which var contains joyn report -------------------
# Joining x2 and y2
joyn(x = x2,
y = y2,
by = "id",
y_vars_to_keep = FALSE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> id t x .joyn
#> <num> <int> <num> <fctr>
#> 1: 1 1 16 x & y
#> 2: 4 2 12 x
#> 3: 2 1 NA x & y
#> 4: 3 2 NA x & y
#> 5: NA NA 15 x
#> 6: 5 NA NA y
#> 7: 6 NA NA y
# Printing the info message
joyn_msg(msg_type = "info")
#> ℹ Note: Joyn's report available in variable .joyn
# ---------------- Info about change in reporting variable name ----------------
joyn(x = x2,
y = y2,
by = "id",
reportvar = "x",
y_vars_to_keep = FALSE)
#>
#> ── JOYn Report ──
#>
#> x.1 n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable x
#> ℹ Note: reportvar x is already part of the resulting table. It will be changed
#> to x.1
#> id t x x.1
#> <num> <int> <num> <fctr>
#> 1: 1 1 16 x & y
#> 2: 4 2 12 x
#> 3: 2 1 NA x & y
#> 4: 3 2 NA x & y
#> 5: NA NA 15 x
#> 6: 5 NA NA y
#> 7: 6 NA NA y
joyn_msg(msg_type = "info")
#> ℹ Note: Joyn's report available in variable x
#> ℹ Note: reportvar x is already part of the resulting table. It will be changed
#> to x.1
# ------------- Informing that reporting variable is not returned -------------
joyn(x = x2,
y = y2,
by = "id",
reportvar = FALSE,
y_vars_to_keep = FALSE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Reporting variable is NOT returned
#> id t x
#> <num> <int> <num>
#> 1: 1 1 16
#> 2: 4 2 12
#> 3: 2 1 NA
#> 4: 3 2 NA
#> 5: NA NA 15
#> 6: 5 NA NA
#> 7: 6 NA NA
joyn_msg(msg_type = "info")
#> ℹ Note: Reporting variable is NOT returnedFurthermore, info messages will help you keep track of which
variables in y will be kept after
the merging, for example notifying you if any of the y
variables you have specified to keep will be removed because they are
part of the by variables.
joyn(x = x2,
y = y2,
by = "id",
y_vars_to_keep = TRUE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id, yd, y, and x
#> id t x yd y .joyn
#> <num> <int> <num> <num> <int> <fctr>
#> 1: 1 1 16 1 11 x & y
#> 2: 4 2 12 NA NA x
#> 3: 2 1 NA 2 15 x & y
#> 4: 3 2 NA 3 10 x & y
#> 5: NA NA 15 NA NA x
#> 6: 5 NA NA 5 20 y
#> 7: 6 NA NA 6 13 y
joyn_msg(msg_type = "info")
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id, yd, y, and xTiming messages report in how many seconds the join is executed, including the time spent to perform all checks.
While performing the join, joyn keeps track of the
time spent for the execution. This is then displayed in
timing messages, which report the elapsed time measured in seconds.
Before visualizing some examples, it is important to remind a feature
of how joyn executes any join between two data tables.
Specifically, joyn always first executes a full join
between the data tables - which includes all matching and non matching
rows in the resulting table. Then, it filters the rows depending on the
specific type of join that user wants to execute. For example, if the
user sets keep = "right", joyn will filter the
table resulting from the full join and return to the user the data table
retaining all rows from the right table and only
matching rows from the left table. In addition, note that since
joyn performs a number of checks throughout the execution
(e.g., checking that the specified key for the merge is valid, or the
match type consistency), the time spent on checks will also be included
in reported time.
As a result, timing messages enable you to be aware of both:
# --------------------------- Example with full join ---------------------------
joyn(x = x1,
y = y1,
match_type = "m:1")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 33.3%
#> 2 y 1 16.7%
#> 3 x & y 3 50%
#> 4 total 6 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y
#> id t x y .joyn
#> <num> <int> <int> <num> <fctr>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & y
#> 4: 3 2 14 NA x
#> 5: NA NA 15 NA x
#> 6: 4 NA NA 16 y
joyn_msg("timing")
#> ● Timing:The full joyn is executed in 0.000254 seconds.
#> ● Timing: The entire joyn function, including checks, is executed in 0.019748
#> seconds.
# --------------------------- Example with left join ---------------------------
left_join(x = x1,
y = y1,
relationship = "many-to-one")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 40%
#> 2 y 1 20%
#> 3 x & y 2 40%
#> 4 total 5 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y
#> id t x y .joyn
#> <num> <int> <int> <num> <fctr>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & y
#> 4: 3 2 14 NA x
#> 5: NA NA 15 NA x
joyn_msg("timing")
#> ● Timing:The full joyn is executed in 0.00025 seconds.
#> ● Timing: The entire joyn function, including checks, is executed in 0.016798
#> seconds.joyn generates warning messages to alert you about
possible problematic situation which however do not warrant terminating
execution of the merge.
For example, if you provide a match type that is inconsistent with
the data, joyn will generate a warning to inform you about
the actual relationship and to alert that the join will be executed
accordingly.
In the example below, both x2 and y2 are
uniquely identified by the key id, but the user is choosing
a “one to many” relationship instead. The user will be alerted and a
“one to one” join will be executed instead.
# Warning that "id" uniquely identifies y2
joyn(x2, y2, by = "id", match_type = "1:m", verbose = TRUE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id, yd, y, and x
#> ⚠ Warning: The keys supplied uniquely identify y, therefore a 1:1 join is
#> executed
#> id t x yd y .joyn
#> <num> <int> <num> <num> <int> <fctr>
#> 1: 1 1 16 1 11 x & y
#> 2: 4 2 12 NA NA x
#> 3: 2 1 NA 2 15 x & y
#> 4: 3 2 NA 3 10 x & y
#> 5: NA NA 15 NA NA x
#> 6: 5 NA NA 5 20 y
#> 7: 6 NA NA 6 13 y
joyn_msg("warn")
#> ⚠ Warning: The keys supplied uniquely identify y, therefore a 1:1 join is
#> executedIn a similar way, warning messages are generated when choosing
match_type = "m:m" or "m:1"
# ------------ Warning that "id" uniquely identifies both x2 and y2 ------------
joyn(x2, y2, by = "id", match_type = "m:m", verbose = TRUE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id, yd, y, and x
#> ⚠ Warning: The keys supplied uniquely identify both x and y, therefore a 1:1
#> join is executed
#> id t x yd y .joyn
#> <num> <int> <num> <num> <int> <fctr>
#> 1: 1 1 16 1 11 x & y
#> 2: 4 2 12 NA NA x
#> 3: 2 1 NA 2 15 x & y
#> 4: 3 2 NA 3 10 x & y
#> 5: NA NA 15 NA NA x
#> 6: 5 NA NA 5 20 y
#> 7: 6 NA NA 6 13 y
joyn_msg("warn")
#> ⚠ Warning: The keys supplied uniquely identify both x and y, therefore a 1:1
#> join is executed
# ------------------ Warning that "id" uniquely identifies x2 ------------------
joyn(x2, y2, by = "id", match_type = "m:1", verbose = TRUE)
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 28.6%
#> 2 y 2 28.6%
#> 3 x & y 3 42.9%
#> 4 total 7 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id, yd, y, and x
#> ⚠ Warning: The keys supplied uniquely identify x, therefore a 1:1 join is
#> executed
#> id t x yd y .joyn
#> <num> <int> <num> <num> <int> <fctr>
#> 1: 1 1 16 1 11 x & y
#> 2: 4 2 12 NA NA x
#> 3: 2 1 NA 2 15 x & y
#> 4: 3 2 NA 3 10 x & y
#> 5: NA NA 15 NA NA x
#> 6: 5 NA NA 5 20 y
#> 7: 6 NA NA 6 13 y
joyn_msg("warn")
#> ⚠ Warning: The keys supplied uniquely identify x, therefore a 1:1 join is
#> executedOther examples of warnings are those that arise when you are trying
to supply certain arguments to the merging functions that are not yet
supported by the current version of joyn.
Suppose you are executing a left-join and you try to set the
na_matches argument to ‘never’. joyn will warn
you that it currently allows only na_matches = 'na'. A
similar message is displayed when keep = NULL. Given that
the current version of joyn does not support inequality
joins, joyn will warn you that keep = NULL
will make the join retain only keys in x.
joyn::left_join(x = x1,
y = y1,
relationship = "many-to-one",
keep = NULL,
na_matches = "never")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 40%
#> 2 y 1 20%
#> 3 x & y 2 40%
#> 4 total 5 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y
#> ⚠ Warning: joyn does not currently allow inequality joins, so keep = NULL will
#> retain only keys in x
#> ⚠ Warning: Currently, joyn allows only na_matches = 'na'
#> id t x y .joyn
#> <num> <int> <int> <num> <fctr>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & y
#> 4: 3 2 14 NA x
#> 5: NA NA 15 NA x
joyn_msg("warn")
#> ⚠ Warning: joyn does not currently allow inequality joins, so keep = NULL will
#> retain only keys in x
#> ⚠ Warning: Currently, joyn allows only na_matches = 'na'Error messages act as helpful notifications about the reasons why the join you are trying to perform can’t be executed. Error messages highlight where you went off course and provide clues to fix the issue so that the merging can be successfully executed.
Sometimes error messages are due to a wrong/missing provision of the
inputs, for example if you do not supply variables to be used as key for
the merge, and x and y do not have any common
variable names. Error messages will also pop up if you provide an input
data table that has no variables, or that has duplicate variable
names.
Representative messages in this regard can be visualized below:
# ----------------- Error due to input table x with no columns -----------------
x_empty = data.table()
joyn(x = x_empty,
y = y1)
#> ✖ Error: Input table x has no columns.
#> Error in `check_xy()`:
#> ! wrong input specification
joyn_msg("err")
#> ✖ Error: Input table x has no columns.
# ----------------------- Error due to duplicate names ------------------------
x_duplicates = data.table(id = c(1L, 1L, 2L, 3L, NA_integer_),
x = c(1L, 2L, 1L, 2L, NA_integer_),
x = 11:15,
check.names = FALSE)
joyn(x = x_duplicates,
y = y1)
#> ✖ Error: Table x has the following column duplicated: x. Please rename or
#> remove and try again.
#> Error in `check_xy()`:
#> ! wrong input specification
joyn_msg("err")
#> ✖ Error: Table x has the following column duplicated: x. Please rename or
#> remove and try again.Furthermore, errors messages are generated when choosing the wrong
match_type, that is not consistent with the actual
relationship between the variables being used for merging.
joyn will therefore display the following message:
joyn(x = x1, y=y1, by="id", match_type = "1:1")
#> ✖ Error: table x is not uniquely identified by id
#> Duplicate counts in x:
#> id copies percent
#> <char> <int> <char>
#> 1: 1 2 40%
#> 2: total 5 100%
#> Error in `check_match_type()`:
#> ! match type inconsistency
#> ℹ refer to the duplicate counts in the table(s) above to identify where the
#> issue occurred
joyn_msg("err")
#> ✖ Error: table x is not uniquely identified by idjoyn messages?joyn stores the messages in the joyn
environment.
In order to print them, you can use the joyn_msg()
function. The msg_type argument allows you to specify a
certain type of message you would like to visualize, or, if you want all
of them to be displayed, you can just set type = 'all'
# Execute a join
joyn(x = x1,
y = y1,
match_type = "m:1")
#>
#> ── JOYn Report ──
#>
#> .joyn n percent
#> 1 x 2 33.3%
#> 2 y 1 16.7%
#> 3 x & y 3 50%
#> 4 total 6 100%
#> ────────────────────────────────────────────────────────── End of JOYn report ──
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y
#> id t x y .joyn
#> <num> <int> <int> <num> <fctr>
#> 1: 1 1 11 11 x & y
#> 2: 1 2 12 11 x & y
#> 3: 2 1 13 15 x & y
#> 4: 3 2 14 NA x
#> 5: NA NA 15 NA x
#> 6: 4 NA NA 16 y
# Print all messages stored
joyn_msg(msg_type = "all")
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y
#> ● Timing:The full joyn is executed in 0.000182 seconds.
#> ● Timing: The entire joyn function, including checks, is executed in 0.018091
#> seconds.
# Print info messages only
joyn_msg(msg_type = "info")
#> ℹ Note: Joyn's report available in variable .joyn
#> ℹ Note: Removing key variables id from id and y