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.
pivot_to_matrix(df_long)
pivot_to_df(matrix_wide, value_colname = "values")data.frame in long format with exactly 3 columns
matrix in wide format
name for the new value column in the resulting data.frame
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).
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.
# 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