Pivot long data.frame to wide matrix and vice versa

Create a matrix in 'wide' format from a data.frame with 3 columns with pivot_to_matrix or create a data.frame in long format from a matrix with pivot_to_df.

Usage

pivot_to_matrix(df_long)

pivot_to_df(matrix_wide, value_colname = "values")

Arguments

df_long

data.frame in long format with exactly 3 columns

matrix_wide

matrix in wide format

value_colname

name for the new value column in the resulting data.frame

Value

A data.frame with 3 columns or a matrix. Note that the results are sorted by the first and second column (data.frame) or row/column names (matrix).

Details

These pivot functions are used to prepare data for biproporz() in pukelsheim(). They are not supposed to cover general use cases or provide customization. They mainly exist because reshape is hard to handle and the package should have no dependencies.

Examples

# From data.frame to matrix
df = data.frame(party = c("A", "A", "A", "B", "B", "B"),
                region = c("III", "II", "I", "I", "II", "III"),
                seats = c(5L, 3L, 1L, 2L, 4L, 6L))
pivot_to_matrix(df)
#>      region
#> party I II III
#>     A 1  3   5
#>     B 2  4   6

# from matrix to data.frame
mtrx = matrix(1:6, nrow = 2)
pivot_to_df(mtrx)
#>   row col values
#> 1   1   1      1
#> 2   1   2      3
#> 3   1   3      5
#> 4   2   1      2
#> 5   2   2      4
#> 6   2   3      6

# from matrix to data.frame using dimnames
dimnames(mtrx) <- list(party = c("A", "B"), region = c("I", "II", "III"))
pivot_to_df(mtrx, "seats")
#>   party region seats
#> 1     A      I     1
#> 2     A     II     3
#> 3     A    III     5
#> 4     B      I     2
#> 5     B     II     4
#> 6     B    III     6

# Note that pivot results are sorted
pivot_to_df(pivot_to_matrix(df)) == df[order(df[[1]], df[[2]]),]
#>      party region values
#> [1,]  TRUE   TRUE   TRUE
#> [2,]  TRUE   TRUE   TRUE
#> [3,]  TRUE   TRUE   TRUE
#> [4,]  TRUE   TRUE   TRUE
#> [5,]  TRUE   TRUE   TRUE
#> [6,]  TRUE   TRUE   TRUE