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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_to_wide.R
\name{data_to_wide}
\alias{data_to_wide}
\alias{reshape_wider}
\title{Reshape (pivot) data from long to wide}
\usage{
data_to_wide(
data,
id_cols = NULL,
values_from = "Value",
names_from = "Name",
names_sep = "_",
names_prefix = "",
names_glue = NULL,
values_fill = NULL,
verbose = TRUE,
...,
colnames_from,
rows_from,
sep
)
reshape_wider(
data,
id_cols = NULL,
values_from = "Value",
names_from = "Name",
names_sep = "_",
names_prefix = "",
names_glue = NULL,
values_fill = NULL,
verbose = TRUE,
...,
colnames_from,
rows_from,
sep
)
}
\arguments{
\item{data}{A data frame to pivot.}
\item{id_cols}{The name of the column that identifies the rows. If \code{NULL},
it will use all the unique rows.}
\item{values_from}{The name of the column that contains the values to be used
as future variable values.}
\item{names_from}{The name of the column that contains the levels to be
used as future column names.}
\item{names_sep}{If \code{names_from} or \code{values_from} contains multiple variables,
this will be used to join their values together into a single string to use
as a column name.}
\item{names_prefix}{String added to the start of every variable name. This is
particularly useful if \code{names_from} is a numeric vector and you want to create
syntactic variable names.}
\item{names_glue}{Instead of \code{names_sep} and \code{names_prefix}, you can supply a
\href{https://glue.tidyverse.org/index.html}{glue specification} that uses the
\code{names_from} columns to create custom column names. Note that the only
delimiters supported by \code{names_glue} are curly brackets, \verb{\{} and \verb{\}}.}
\item{values_fill}{Optionally, a (scalar) value that will be used to replace
missing values in the new columns created.}
\item{verbose}{Toggle warnings.}
\item{...}{Not used for now.}
\item{colnames_from}{Deprecated. Use \code{names_from} instead.}
\item{rows_from}{Deprecated. Use \code{id_cols} instead.}
\item{sep}{Deprecated. Use \code{names_sep} instead.}
}
\value{
If a tibble was provided as input, \code{reshape_wider()} also returns a
tibble. Otherwise, it returns a data frame.
}
\description{
This function "widens" data, increasing the number of columns and decreasing
the number of rows. This is a dependency-free base-R equivalent of
\code{tidyr::pivot_wider()}.
}
\examples{
data_long <- read.table(header = TRUE, text = "
subject sex condition measurement
1 M control 7.9
1 M cond1 12.3
1 M cond2 10.7
2 F control 6.3
2 F cond1 10.6
2 F cond2 11.1
3 F control 9.5
3 F cond1 13.1
3 F cond2 13.8
4 M control 11.5
4 M cond1 13.4
4 M cond2 12.9")
reshape_wider(
data_long,
id_cols = "subject",
names_from = "condition",
values_from = "measurement"
)
reshape_wider(
data_long,
id_cols = "subject",
names_from = "condition",
values_from = "measurement",
names_prefix = "Var.",
names_sep = "."
)
production <- expand.grid(
product = c("A", "B"),
country = c("AI", "EI"),
year = 2000:2014
)
production <- data_filter(production, (product == "A" & country == "AI") | product == "B")
production$production <- rnorm(nrow(production))
reshape_wider(
production,
names_from = c("product", "country"),
values_from = "production",
names_glue = "prod_{product}_{country}"
)
}
\seealso{
\itemize{
\item Functions to rename stuff: \code{\link[=data_rename]{data_rename()}}, \code{\link[=data_rename_rows]{data_rename_rows()}}, \code{\link[=data_addprefix]{data_addprefix()}}, \code{\link[=data_addsuffix]{data_addsuffix()}}
\item Functions to reorder or remove columns: \code{\link[=data_reorder]{data_reorder()}}, \code{\link[=data_relocate]{data_relocate()}}, \code{\link[=data_remove]{data_remove()}}
\item Functions to reshape, pivot or rotate data frames: \code{\link[=data_to_long]{data_to_long()}}, \code{\link[=data_to_wide]{data_to_wide()}}, \code{\link[=data_rotate]{data_rotate()}}
\item Functions to recode data: \code{\link[=rescale]{rescale()}}, \code{\link[=reverse]{reverse()}}, \code{\link[=categorize]{categorize()}}, \code{\link[=recode_values]{recode_values()}}, \code{\link[=slide]{slide()}}
\item Functions to standardize, normalize, rank-transform: \code{\link[=center]{center()}}, \code{\link[=standardize]{standardize()}}, \code{\link[=normalize]{normalize()}}, \code{\link[=ranktransform]{ranktransform()}}, \code{\link[=winsorize]{winsorize()}}
\item Split and merge data frames: \code{\link[=data_partition]{data_partition()}}, \code{\link[=data_merge]{data_merge()}}
\item Functions to find or select columns: \code{\link[=data_select]{data_select()}}, \code{\link[=data_find]{data_find()}}
\item Functions to filter rows: \code{\link[=data_match]{data_match()}}, \code{\link[=data_filter]{data_filter()}}
}
}
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