Constructors and methods for a nonnegative continuous data type.
v_continuous_nonneg and nneg are synonyms that each create a
new v_continuous_nonneg object subclassed from v_continuous and
vctrs_vctr.
Support: \(\mathbf{R^+}\)* (plus NA_real_)
Prototype: double
* - i.e. floating-point number
v_continuous_nonneg(
x = ptypeFUN(),
internal_name = "",
context,
auto_compute_summary = auto_compute_default,
extra_descriptors = list()
)
nneg(
x = ptypeFUN(),
internal_name = "",
context,
auto_compute_summary = auto_compute_default,
extra_descriptors = list()
)
is_continuous_nonneg(x)
is_nonneg(x)
as_nonneg_continuous(x)
as_continuous_nonneg(x)
# S3 method for v_continuous_nonneg
as_canonical(x)nonnegative double
the internal name of the variable
a context
an indicator of whether the data_summary is
automatically computed whenever a vector is initialized, subset, or
concatenated. Defaults to TRUE. If this option is set to FALSE,
then get_data_summary is the only way to compute the summary.
The data_summary_l lens will return an empty data_summary.
A list of descriptors functions
appended to the default descriptors.
Other stype types:
tbl_analysis,
v_binary,
v_continuous,
v_count,
v_nominal,
v_ordered,
v_proportion,
v_rcensored
# Example data
src_dbl <- c(1, 2.5, 4, 5.5, NA_real_)
# Constructor for the `v_continuous_nonneq` class. One can also use `nneg`
# which is a synonym for the `v_continuous_nonneg` function.
v <- v_continuous_nonneg(
x = src_dbl,
internal_name = "v_example",
context = context(
short_label = "important_var",
long_label = "Very important variable"
),
extra_descriptors = list()
)
# Helper functions and methods
is_continuous_nonneg(v)
#> [1] TRUE
as_nonneg_continuous(src_dbl)
#> <continuous nonnegative[5]>
#> [1] 1 2.5 4 5.5 <NA>
#> Mean = 3.250; SD = 1.936; Missing = 1
as.character(v)
#> [1] "1" "2.5" "4" "5.5" NA
as_canonical(v)
#> [1] 1.0 2.5 4.0 5.5 NA