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Convert a long-format data frame into matrix

Source: R/matrix2longdf.R
longdf2matrix.Rd

Input data.frame must contain at least three columns: one contains row names (specified by row.col), one contains column names (column.col), and one contains values in matrix cells (value.col). The output is a 2D matrix.

Usage

longdf2matrix(
  df,
  row.col = 1L,
  column.col = 2L,
  value.col = 3L,
  missingValue = NULL
)

Arguments

df

Long-format data frame

row.col

Character or integer, which column of the input data.frame contains row names?

column.col

Character or integer, which column contains column names?

value.col

Character or integer, which column contains matrix values?

missingValue

Values assigned in case of missing data

Value

A 2D matrix equivalent to the long-format data frame

See also

matrix2longdf

Author

Jitao David Zhang <jitao_david.zhang@roche.com>

Examples


test.df <- data.frame(H=c("HSV", "BVB", "HSV", "BVB"),
A=c("FCB", "S04", "S04", "FCB"),
score=c(3, 1, 1, 0))
longdf2matrix(test.df, row.col=1L, column.col=2L, value.col=3L)
#>     FCB S04
#> HSV   3   1
#> BVB   0   1

data(Indometh)
longdf2matrix(Indometh, row.col="time", column.col="Subject",value.col="conc")
#>         1    2    3    4    5    6
#> 0.25 1.50 2.03 2.72 1.85 2.05 2.31
#> 0.5  0.94 1.63 1.49 1.39 1.04 1.44
#> 0.75 0.78 0.71 1.16 1.02 0.81 1.03
#> 1    0.48 0.70 0.80 0.89 0.39 0.84
#> 1.25 0.37 0.64 0.80 0.59 0.30 0.64
#> 2    0.19 0.36 0.39 0.40 0.23 0.42
#> 3    0.12 0.32 0.22 0.16 0.13 0.24
#> 4    0.11 0.20 0.12 0.11 0.11 0.17
#> 5    0.08 0.25 0.11 0.10 0.08 0.13
#> 6    0.07 0.12 0.08 0.07 0.10 0.10
#> 8    0.05 0.08 0.08 0.07 0.06 0.09
longdf2matrix(Indometh, row.col="Subject", column.col="time", value.col="conc")
#>   0.25  0.5 0.75    1 1.25    2    3    4    5    6    8
#> 1 1.50 0.94 0.78 0.48 0.37 0.19 0.12 0.11 0.08 0.07 0.05
#> 2 2.03 1.63 0.71 0.70 0.64 0.36 0.32 0.20 0.25 0.12 0.08
#> 3 2.72 1.49 1.16 0.80 0.80 0.39 0.22 0.12 0.11 0.08 0.08
#> 4 1.85 1.39 1.02 0.89 0.59 0.40 0.16 0.11 0.10 0.07 0.07
#> 5 2.05 1.04 0.81 0.39 0.30 0.23 0.13 0.11 0.08 0.10 0.06
#> 6 2.31 1.44 1.03 0.84 0.64 0.42 0.24 0.17 0.13 0.10 0.09