Expand a data frame by replicating rows based on another variable that contains the counts of replications per row.
data_replicate(
data,
expand = NULL,
select = NULL,
exclude = NULL,
remove_na = FALSE,
ignore_case = FALSE,
verbose = TRUE,
regex = FALSE,
...
)
A dataframe with each row replicated as many times as defined in expand
.
A data frame.
The name of the column that contains the counts of replications
for each row. Can also be a numeric value, indicating the position of that
column. Note that the variable indicated by expand
must be an integer vector.
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"
), or a character
vector of variable names (e.g., c("col1", "col2", "col3")
),
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")
.
or 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"
.
See select
, however, column names matched by the pattern
from exclude
will be excluded instead of selected. If NULL
(the default),
excludes no columns.
Logical. If TRUE
, missing values in the column
provided in expand
are removed from the data frame. If FALSE
and expand
contains missing values, the function will throw an error.
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.
Toggle warnings.
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.
Currently not used.
data(mtcars)
data_replicate(head(mtcars), "carb")
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