duplicate_count {scrutiny} | R Documentation |
duplicate_count()
returns a frequency table. When searching a
data frame, it includes values from all columns for each frequency count.
This function is a blunt tool designed for initial data checking. It is not too informative if many values have few characters each.
For summary statistics, call audit()
on the results.
duplicate_count(
x,
ignore = NULL,
locations_type = c("character", "list"),
numeric_only = deprecated()
)
x |
Vector or data frame. |
ignore |
Optionally, a vector of values that should not be counted. |
locations_type |
String. One of |
numeric_only |
[Deprecated] No longer used: All values are coerced to character. |
Don't use numeric_only
. It no longer has any effect and will be
removed in the future. The only reason for this argument was the risk of
errors introduced by coercing values to numeric. This is no longer an issue
because all values are now coerced to character, which is more appropriate
for checking reported statistics.
If x
is a data frame or another named vector, a tibble with four
columns. If x
isn't named, only the first two columns appear:
value
: All the values from x
.
frequency
: Absolute frequency of each value in x
, in descending order.
locations
: Names of all columns from x
in which value
appears.
locations_n
: Number of columns named in locations
.
The tibble has the scr_dup_count
class, which is recognized by the
audit()
generic.
audit()
There is an S3 method for the
audit()
generic, so you can call audit()
following
duplicate_count()
. It returns a tibble with summary statistics for the
two numeric columns, frequency
and locations_n
(or, if x
isn't named,
only for frequency
).
duplicate_count_colpair()
to check each combination of columns for
duplicates.
duplicate_tally()
to show instances of a value next to each instance.
janitor::get_dupes()
to search for duplicate rows.
# Count duplicate values...
iris %>%
duplicate_count()
# ...and compute summaries:
iris %>%
duplicate_count() %>%
audit()
# Any values can be ignored:
iris %>%
duplicate_count(ignore = c("setosa", "versicolor", "virginica"))