R: Reshape Wide Data Into a Semi-long Form

Reshape {splitstackshape}

R Documentation

Reshape Wide Data Into a Semi-long Form

Description

The reshape function in base R is very handy when you want a semi-long (or semi-wide) data.frame. However, base R's reshape has problems is with "unbalanced" panel data, for instance data where one variable was measured at three points in time, and another only twice.

Usage

Reshape(data, id.vars = NULL, var.stubs, sep = ".", rm.rownames = TRUE,
  ...)

Arguments

`data`	The source `data.frame`.
`id.vars`	The variables that serve as unique identifiers. Defaults to `NULL`, at which point, all names which are not identified as variable groups are used as the identifiers.
`var.stubs`	The prefixes of the variable groups.
`sep`	The character that separates the "variable name" from the "times" in the wide `data.frame`.
`rm.rownames`	Logical. `reshape` creates some long distracting `rownames` that do not seem to serve much purpose. This argument is set to `TRUE` to remove the `rownames` by default.
`...`	Further arguments to `NoSep` in case the separator is of a different form.

Details

This function was written to overcome that limitation of dealing with unbalanced data, but is also appropriate for basic wide-to-long reshaping tasks.

Related functions like stack in base R and melt in "reshape2" are also very handy when you want a "long" reshaping of data, but they result in a very long structuring of your data, not the "semi-wide" format that reshape produces.

Value

A "long" data.frame of the reshaped data that retains the attributes added by base R's reshape function.

Author(s)

Ananda Mahto

Examples

set.seed(1)
mydf <- data.frame(id_1 = 1:6, id_2 = c("A", "B"), varA.1 = sample(letters, 6),
                 varA.2 = sample(letters, 6), varA.3 = sample(letters, 6),
                 varB.2 = sample(10, 6), varB.3 = sample(10, 6),
                 varC.3 = rnorm(6))
mydf

## Note that these data are unbalanced
## reshape() will not work
## Not run: 
reshape(mydf, direction = "long", idvar=1:2, varying=3:ncol(mydf))

## End(Not run)

## The Reshape() function can handle such scenarios

Reshape(mydf, id.vars = c("id_1", "id_2"),
       var.stubs = c("varA", "varB", "varC"))

[Package splitstackshape version 1.4.2 Index]