Reshape a data.frame or matrix to a long data.frame

Reshape a data.frame or matrix to a wide data.frame

Usage

to_long(
  wide,
  rowname = NULL,
  colname = NULL,
  responseName = deparse(substitute(wide)),
  varNames = c("Row", "Col")
)

to_wide(long, row = 1, col = 2, response = 3)

Arguments

wide: A data.frame or matrix in wide form
rowname: Name for the row variable
colname: Name for the column variable
responseName: Name for the response variable. If wide is a matrix with an attribute that begins with "response", that value is taken as the responseName. Otherwise, the name of the wide object is used.
varNames: Default names for the row and column variables if not passed as rowname or colname
long: A data.frame in long form
row: Column index or quoted name of the row variable
col: Column index or quoted name of the column variable
response: Column index or quoted name of the response variable

Value

A data.frame in long format

Author

Michael Friendly and Richard M. Heiberger

Examples

Arizona.long <- to_long(Arizona, varNames=c("Month", "City"))
Arizona.long
#>    Month      City Temperature
#> 1    Jul Flagstaff        65.2
#> 2    Aug Flagstaff        63.4
#> 3    Sep Flagstaff        57.0
#> 4    Oct Flagstaff        46.1
#> 5    Nov Flagstaff        35.8
#> 6    Dec Flagstaff        28.4
#> 7    Jan Flagstaff        25.3
#> 8    Jul   Phoenix        90.1
#> 9    Aug   Phoenix        88.3
#> 10   Sep   Phoenix        82.7
#> 11   Oct   Phoenix        70.8
#> 12   Nov   Phoenix        58.4
#> 13   Dec   Phoenix        52.1
#> 14   Jan   Phoenix        49.7
#> 15   Jul      Yuma        94.6
#> 16   Aug      Yuma        93.7
#> 17   Sep      Yuma        88.3
#> 18   Oct      Yuma        76.4
#> 19   Nov      Yuma        64.2
#> 20   Dec      Yuma        57.1
#> 21   Jan      Yuma        55.3

Arizona.long <- to_long(Arizona, varNames=c("Month", "City"))
# back the other way
to_wide(Arizona.long)
#>      City
#> Month Flagstaff Phoenix Yuma
#>   Jul      65.2    90.1 94.6
#>   Aug      63.4    88.3 93.7
#>   Sep      57.0    82.7 88.3
#>   Oct      46.1    70.8 76.4
#>   Nov      35.8    58.4 64.2
#>   Dec      28.4    52.1 57.1
#>   Jan      25.3    49.7 55.3