Every epidist data object also carries the epidist_data class. The
methods documented here re-check an object after it has been modified and
drop any epidist class whose requirements the modified object no longer
meets, warning about what was dropped and why. An object that still carries
an epidist class is therefore a valid object of that class, so functions
which accept one do not need to re-check it.
Usage
# S3 method for class 'epidist_data'
x[...]
# S3 method for class 'epidist_data'
x[...] <- value
# S3 method for class 'epidist_data'
x[[...]] <- value
# S3 method for class 'epidist_data'
x$... <- value
# S3 method for class 'epidist_data'
names(x) <- value
# S3 method for class 'epidist_data'
rbind(..., deparse.level = 1)
# S3 method for class 'epidist_data'
dplyr_reconstruct(data, template)
# S3 method for class 'epidist_data'
dplyr_row_slice(data, i, ...)
# S3 method for class 'epidist_data'
dplyr_col_modify(data, cols)
# S3 method for class 'epidist_data'
group_by(.data, ..., .add = FALSE, .drop = dplyr::group_by_drop_default(.data))
# S3 method for class 'epidist_data'
ungroup(x, ...)Arguments
- x, .data
An object with the
epidist_dataclass.- ...
Passed to the underlying method.
- value
A replacement value.
- deparse.level
Passed to
base::rbind().- data, template
Passed to
dplyr::dplyr_reconstruct().- i, cols
Passed to
dplyr::dplyr_row_slice()anddplyr::dplyr_col_modify().- .add, .drop
Passed to
dplyr::group_by().
Details
Methods are provided for base subsetting and replacement, and for
dplyr::dplyr_reconstruct(), which dplyr verbs such as dplyr::mutate(),
dplyr::filter() and dplyr::select() use to restore the class of their
input. dplyr::group_by() and dplyr::ungroup() build a new tibble rather
than restoring the class of their input, as do the grouped_df methods for
dplyr::dplyr_row_slice() and dplyr::dplyr_col_modify(), so each has a
method of its own that puts the classes back. A grouped object keeps the
grouped_df class after the epidist classes, and the dplyr verbs keep
both. dplyr::summarise() builds a new object from the groups rather than
modifying its input, so its result does not carry the epidist classes.
A result with no columns is unclassed without a warning. Such a result is
almost always the prototype vctrs takes internally, in dplyr::bind_cols()
for example, rather than something the user asked for, and it cannot be told
apart from a deliberate empty selection.
See also
Other epidist_data:
is_epidist_data()
Examples
linelist_data <- sierra_leone_ebola_data |>
as_epidist_linelist_data(
pdate_lwr = "date_of_symptom_onset",
sdate_lwr = "date_of_sample_tested"
)
#> ℹ No primary event upper bound provided, using the primary event lower bound + 1 day as the assumed upper bound.
#> ℹ No secondary event upper bound provided, using the secondary event lower bound + 1 day as the assumed upper bound.
#> ℹ No observation time column provided, using 2015-09-14 as the observation date (the maximum of the secondary event upper bound).
# Subsetting rows keeps the class
class(linelist_data[1:10, ])
#> [1] "epidist_linelist_data" "epidist_data" "tbl_df"
#> [4] "tbl" "data.frame"
# Dropping a required column drops the class
class(dplyr::select(linelist_data, -"obs_time"))
#> Warning: ! Dropping the <epidist_linelist_data> class because the object no longer meets
#> its requirements:
#> ✖ Assertion on 'names(data)' failed: Names must include the elements
#> {'ptime_lwr','ptime_upr','stime_lwr','stime_upr','obs_time'}, but is missing
#> elements {'obs_time'}.
#> ℹ Use the matching `as_epidist_*()` function to recreate the object.
#> [1] "tbl_df" "tbl" "data.frame"
# Grouping keeps the class alongside the grouped_df class
class(dplyr::group_by(linelist_data, obs_time))
#> [1] "epidist_linelist_data" "epidist_data" "grouped_df"
#> [4] "tbl_df" "tbl" "data.frame"