mutate.incidence2 {incidence2} | R Documentation |
Create, modify, and delete incidence2 columns
Description
Method for dplyr::mutate that implicitly accounts for the inherent
grouping structure of incidence2 objects.
Usage
## S3 method for class 'incidence2'
mutate(
.data,
...,
.by,
.keep = c("all", "used", "unused", "none"),
.before = NULL,
.after = NULL
)
Arguments
.data |
An incidence2 object.
|
... |
<data-masking > Name-value pairs.
The name gives the name of the column in the output.
The value can be:
A vector of length 1, which will be recycled to the correct length.
A vector the same length as the current group (or the whole data frame
if ungrouped).
-
NULL , to remove the column.
A data frame or tibble, to create multiple columns in the output.
|
.by |
Not used as grouping structure implicit.
|
.keep |
Control which columns from .data are retained in the output. Grouping
columns and columns created by ... are always kept.
-
"all" retains all columns from .data . This is the default.
-
"used" retains only the columns used in ... to create new
columns. This is useful for checking your work, as it displays inputs
and outputs side-by-side.
-
"unused" retains only the columns not used in ... to create new
columns. This is useful if you generate new columns, but no longer need
the columns used to generate them.
-
"none" doesn't retain any extra columns from .data . Only the grouping
variables and columns created by ... are kept.
|
.before , .after |
<tidy-select > Optionally, control where new columns
should appear (the default is to add to the right hand side). See
relocate() for more details.
|
Value
A modified incidence2 object if the necessary
invariants are preserved, otherwise a tibble.
See Also
dplyr::mutate for the underlying generic.
Examples
if (requireNamespace("outbreaks", quietly = TRUE) && requireNamespace("ggplot2", quietly = TRUE)) {
data(ebola_sim_clean, package = "outbreaks")
ebola_sim_clean$linelist |>
subset(!is.na(hospital)) |>
incidence_(date_of_onset, hospital, interval = "isoweek") |>
mutate(ave = data.table::frollmean(count, n = 3L, align = "right")) |>
plot(border_colour = "white", angle = 45) +
ggplot2::geom_line(ggplot2::aes(x = date_index, y = ave))
}
[Package
incidence2 version 2.4.0
Index]