row_count {datawizard} | R Documentation |
Count specific values row-wise
Description
row_count()
mimics base R's rowSums()
, with sums for a
specific value indicated by count
. Hence, it is similar to
rowSums(x == count, na.rm = TRUE)
, but offers some more options, including
strict comparisons. Comparisons using ==
coerce values to atomic vectors,
thus both 2 == 2
and "2" == 2
are TRUE
. In row_count()
, it is also
possible to make "type safe" comparisons using the allow_coercion
argument,
where "2" == 2
is not true.
Usage
row_count(
data,
select = NULL,
exclude = NULL,
count = NULL,
allow_coercion = TRUE,
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE
)
Arguments
data |
A data frame with at least two columns, where number of specific
values are counted row-wise.
|
select |
Variables that will be included when performing the required
tasks. Can be either
a variable specified as a literal variable name (e.g., column_name ),
a string with the variable name (e.g., "column_name" ), a character
vector of variable names (e.g., c("col1", "col2", "col3") ), or a
character vector of variable names including ranges specified via :
(e.g., c("col1:col3", "col5") ),
for some functions, like data_select() or data_rename() , select can
be a named character vector. In this case, the names are used to rename
the columns in the output data frame. See 'Details' in the related
functions to see where this option applies.
a formula with variable names (e.g., ~column_1 + column_2 ),
a vector of positive integers, giving the positions counting from the left
(e.g. 1 or c(1, 3, 5) ),
a vector of negative integers, giving the positions counting from the
right (e.g., -1 or -1:-3 ),
one of the following select-helpers: starts_with() , ends_with() ,
contains() , a range using : , or regex() . starts_with() ,
ends_with() , and contains() accept several patterns, e.g
starts_with("Sep", "Petal") . regex() can be used to define regular
expression patterns.
a function testing for logical conditions, e.g. is.numeric() (or
is.numeric ), or any user-defined function that selects the variables
for which the function returns TRUE (like: foo <- function(x) mean(x) > 3 ),
ranges specified via literal variable names, select-helpers (except
regex() ) and (user-defined) functions can be negated, i.e. return
non-matching elements, when prefixed with a - , e.g. -ends_with() ,
-is.numeric or -(Sepal.Width:Petal.Length) . Note: Negation means
that matches are excluded, and thus, the exclude argument can be
used alternatively. For instance, select=-ends_with("Length") (with
- ) is equivalent to exclude=ends_with("Length") (no - ). In case
negation should not work as expected, use the exclude argument instead.
If NULL , selects all columns. Patterns that found no matches are silently
ignored, e.g. extract_column_names(iris, select = c("Species", "Test"))
will just return "Species" .
|
exclude |
See select , however, column names matched by the pattern
from exclude will be excluded instead of selected. If NULL (the default),
excludes no columns.
|
count |
The value for which the row sum should be computed. May be a
numeric value, a character string (for factors or character vectors), NA or
Inf .
|
allow_coercion |
Logical. If FALSE , count matches only values of same
class (i.e. when count = 2 , the value "2" is not counted and vice versa).
By default, when allow_coercion = TRUE , count = 2 also matches "2" . In
order to count factor levels in the data, use count = factor("level") . See
'Examples'.
|
ignore_case |
Logical, if TRUE and when one of the select-helpers or
a regular expression is used in select , ignores lower/upper case in the
search pattern when matching against variable names.
|
regex |
Logical, if TRUE , the search pattern from select will be
treated as regular expression. When regex = TRUE , select must be a
character string (or a variable containing a character string) and is not
allowed to be one of the supported select-helpers or a character vector
of length > 1. regex = TRUE is comparable to using one of the two
select-helpers, select = contains() or select = regex() , however,
since the select-helpers may not work when called from inside other
functions (see 'Details'), this argument may be used as workaround.
|
verbose |
Toggle warnings.
|
Value
A vector with row-wise counts of values specified in count
.
Examples
dat <- data.frame(
c1 = c(1, 2, NA, 4),
c2 = c(NA, 2, NA, 5),
c3 = c(NA, 4, NA, NA),
c4 = c(2, 3, 7, 8)
)
# count all 4s per row
row_count(dat, count = 4)
# count all missing values per row
row_count(dat, count = NA)
dat <- data.frame(
c1 = c("1", "2", NA, "3"),
c2 = c(NA, "2", NA, "3"),
c3 = c(NA, 4, NA, NA),
c4 = c(2, 3, 7, Inf)
)
# count all 2s and "2"s per row
row_count(dat, count = 2)
# only count 2s, but not "2"s
row_count(dat, count = 2, allow_coercion = FALSE)
dat <- data.frame(
c1 = factor(c("1", "2", NA, "3")),
c2 = c("2", "1", NA, "3"),
c3 = c(NA, 4, NA, NA),
c4 = c(2, 3, 7, Inf)
)
# find only character "2"s
row_count(dat, count = "2", allow_coercion = FALSE)
# find only factor level "2"s
row_count(dat, count = factor("2"), allow_coercion = FALSE)
[Package
datawizard version 1.1.0
Index]