dplyr-verbs: dplyr and tidyr verbs
In incidence2: Compute, Handle and Plot Incidence of Dated Events

dplyr-verbs

R Documentation

dplyr and tidyr verbs

Description

dplyr and tidyr methods that implicitly account 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
)

## S3 method for class 'incidence2'
nest(.data, ..., .by, .key, .names_sep)

## S3 method for class 'incidence2'
summarise(.data, ..., .by, .groups)

Arguments

`.data`	An incidence2 object.
`...`	Only used by `mutate()` and `summarise()` and, in which case, passed to underlying dplyr function.
`.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.
`.key`	The name of the resulting nested column. Only applicable when `...` isn't specified, i.e. in the case of `df %>% nest(.by = x)`. If `NULL`, then `"data"` will be used by default.
`.names_sep`	Not used.
`.groups`	Not used.

Value

For mutate() a modified incidence2 object if the necessary invariants are preserved, otherwise a tibble.
For nest() a nested tibble with rows corresponding to the count variable and (optionally) group columns of the input object.
For summarise a tibble with rows corresponding to the underlying groupings. The columns are a combination of the grouping keys and the summary expressions provided.

Examples


if (requireNamespace("outbreaks", quietly = TRUE) && requireNamespace("ggplot2", quietly = TRUE)) {
    data(ebola_sim_clean, package = "outbreaks")
    x <- subset(ebola_sim_clean$linelist, !is.na(hospital))
    dat <- incidence_(x, date_of_onset, hospital, interval = "isoweek")

    mutate(dat, 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))

    nest(dat)

    summarise(dat, model = list(glm(count ~ date_index, family = "poisson")))
}

incidence2 documentation built on April 15, 2025, 1:10 a.m.