datawizard (version 0.4.1)

data_relocate: Relocate (reorder) columns of a data frame

Description

data_relocate() will reorder columns to specific positions, indicated by before or after. data_reorder() will instead move selected columns to the beginning of a data frame. Finally, data_remove() removes columns from a data frame. All functions support select-helpers that allow flexible specification of a search pattern to find matching columns, which should be reordered or removed.

Usage

data_relocate(
  data,
  select,
  before = NULL,
  after = NULL,
  ignore_case = FALSE,
  verbose = TRUE,
  ...
)
data_reorder(data, select, ignore_case = FALSE, verbose = TRUE, ...)
data_remove(data, select, ignore_case = FALSE, verbose = FALSE, ...)

Value

A data frame with reordered columns.

Arguments

data

A data frame.

select

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(""),

• 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. find_columns(iris, select = c("Species", "Test")) will just return "Species".

before, after

Destination of columns. Supplying neither will move columns to the left-hand side; specifying both is an error. Can be a character vector, indicating the name of the destination column, or a numeric value, indicating the index number of the destination column. If -1, will be added before or after the last column.

ignore_case

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.

verbose

Toggle warnings.

...

Arguments passed down to other functions. Mostly not used yet.

See Also

• Functions to rename stuff: data_rename(), data_rename_rows(), data_addprefix(), data_addsuffix()

• Functions to reorder or remove columns: data_reorder(), data_relocate(), data_remove()

• Functions to reshape, pivot or rotate dataframes: data_to_long(), data_to_wide(), data_rotate()

• Functions to recode data: data_rescale(), data_reverse(), data_cut(), data_recode(), data_shift()

• Functions to standardize, normalize, rank-transform: center(), standardize(), normalize(), ranktransform(), winsorize()

• Split and merge dataframes: data_partition(), data_merge()

• Functions to find or select columns: data_select(), data_find()

• Functions to filter rows: data_match(), data_filter()

Examples

# Reorder columns
head(data_relocate(iris, select = "Species", before = "Sepal.Length"))
head(data_relocate(iris, select = "Species", before = "Sepal.Width"))
head(data_relocate(iris, select = "Sepal.Width", after = "Species"))
# same as
head(data_relocate(iris, select = "Sepal.Width", after = -1))

# reorder multiple columns
head(data_relocate(iris, select = c("Species", "Petal.Length"), after = "Sepal.Width"))
# same as
head(data_relocate(iris, select = c("Species", "Petal.Length"), after = 2))

# Reorder columns
head(data_reorder(iris, c("Species", "Sepal.Length")))
head(data_reorder(iris, c("Species", "dupa"))) # Safe for non-existing cols

# Remove columns
head(data_remove(iris, "Sepal.Length"))
head(data_remove(iris, starts_with("Sepal")))