These functions turn a wide table (one column per trait) into pieces
that can be analysed one at a time: by trait and group
(w2l_nest(), w2l_split()), by pairs of traits
(c2p_nest()), or with the levels of one column side by side
(r2p_nest()).
w2l_nest()
# Example: Wide to long format nesting demonstrations
# Example 1: Basic nesting by group
w2l_nest(
data = iris, # Input dataset
by = "Species" # Group by Species column
)
#> Species data
#> <fctr> <list>
#> 1: setosa <data.table[50x4]>
#> 2: versicolor <data.table[50x4]>
#> 3: virginica <data.table[50x4]>
# Example 2: Nest specific columns with numeric indices
w2l_nest(
data = iris, # Input dataset
cols = 1:4, # Select first 4 columns to nest
by = "Species" # Group by Species column
)
#> name Species data
#> <char> <fctr> <list>
#> 1: Sepal.Length setosa <data.table[50x1]>
#> 2: Sepal.Length versicolor <data.table[50x1]>
#> 3: Sepal.Length virginica <data.table[50x1]>
#> 4: Sepal.Width setosa <data.table[50x1]>
#> 5: Sepal.Width versicolor <data.table[50x1]>
#> 6: Sepal.Width virginica <data.table[50x1]>
#> 7: Petal.Length setosa <data.table[50x1]>
#> 8: Petal.Length versicolor <data.table[50x1]>
#> 9: Petal.Length virginica <data.table[50x1]>
#> 10: Petal.Width setosa <data.table[50x1]>
#> 11: Petal.Width versicolor <data.table[50x1]>
#> 12: Petal.Width virginica <data.table[50x1]>
# Example 3: Nest specific columns with column names
w2l_nest(
data = iris, # Input dataset
cols = c("Sepal.Length", # Select columns by name
"Sepal.Width",
"Petal.Length"),
by = 5 # Group by column index 5 (Species)
)
#> name Species data
#> <char> <fctr> <list>
#> 1: Sepal.Length setosa <data.table[50x2]>
#> 2: Sepal.Length versicolor <data.table[50x2]>
#> 3: Sepal.Length virginica <data.table[50x2]>
#> 4: Sepal.Width setosa <data.table[50x2]>
#> 5: Sepal.Width versicolor <data.table[50x2]>
#> 6: Sepal.Width virginica <data.table[50x2]>
#> 7: Petal.Length setosa <data.table[50x2]>
#> 8: Petal.Length versicolor <data.table[50x2]>
#> 9: Petal.Length virginica <data.table[50x2]>
# Returns similar structure to Example 2w2l_split()
# Example: Wide to long format splitting demonstrations
# Example 1: Basic splitting by Species
w2l_split(
data = iris, # Input dataset
by = "Species" # Split by Species column
) |>
lapply(head) # Show first 6 rows of each split
#> $setosa
#> Sepal.Length Sepal.Width Petal.Length Petal.Width
#> <num> <num> <num> <num>
#> 1: 5.1 3.5 1.4 0.2
#> 2: 4.9 3.0 1.4 0.2
#> 3: 4.7 3.2 1.3 0.2
#> 4: 4.6 3.1 1.5 0.2
#> 5: 5.0 3.6 1.4 0.2
#> 6: 5.4 3.9 1.7 0.4
#>
#> $versicolor
#> Sepal.Length Sepal.Width Petal.Length Petal.Width
#> <num> <num> <num> <num>
#> 1: 7.0 3.2 4.7 1.4
#> 2: 6.4 3.2 4.5 1.5
#> 3: 6.9 3.1 4.9 1.5
#> 4: 5.5 2.3 4.0 1.3
#> 5: 6.5 2.8 4.6 1.5
#> 6: 5.7 2.8 4.5 1.3
#>
#> $virginica
#> Sepal.Length Sepal.Width Petal.Length Petal.Width
#> <num> <num> <num> <num>
#> 1: 6.3 3.3 6.0 2.5
#> 2: 5.8 2.7 5.1 1.9
#> 3: 7.1 3.0 5.9 2.1
#> 4: 6.3 2.9 5.6 1.8
#> 5: 6.5 3.0 5.8 2.2
#> 6: 7.6 3.0 6.6 2.1
# Example 2: Split specific columns using numeric indices
w2l_split(
data = iris, # Input dataset
cols = 1:3, # Select first 3 columns to split
by = 5 # Split by column index 5 (Species)
) |>
lapply(head) # Show first 6 rows of each split
#> $Sepal.Length_setosa
#> Petal.Width value
#> <num> <num>
#> 1: 0.2 5.1
#> 2: 0.2 4.9
#> 3: 0.2 4.7
#> 4: 0.2 4.6
#> 5: 0.2 5.0
#> 6: 0.4 5.4
#>
#> $Sepal.Length_versicolor
#> Petal.Width value
#> <num> <num>
#> 1: 1.4 7.0
#> 2: 1.5 6.4
#> 3: 1.5 6.9
#> 4: 1.3 5.5
#> 5: 1.5 6.5
#> 6: 1.3 5.7
#>
#> $Sepal.Length_virginica
#> Petal.Width value
#> <num> <num>
#> 1: 2.5 6.3
#> 2: 1.9 5.8
#> 3: 2.1 7.1
#> 4: 1.8 6.3
#> 5: 2.2 6.5
#> 6: 2.1 7.6
#>
#> $Sepal.Width_setosa
#> Petal.Width value
#> <num> <num>
#> 1: 0.2 3.5
#> 2: 0.2 3.0
#> 3: 0.2 3.2
#> 4: 0.2 3.1
#> 5: 0.2 3.6
#> 6: 0.4 3.9
#>
#> $Sepal.Width_versicolor
#> Petal.Width value
#> <num> <num>
#> 1: 1.4 3.2
#> 2: 1.5 3.2
#> 3: 1.5 3.1
#> 4: 1.3 2.3
#> 5: 1.5 2.8
#> 6: 1.3 2.8
#>
#> $Sepal.Width_virginica
#> Petal.Width value
#> <num> <num>
#> 1: 2.5 3.3
#> 2: 1.9 2.7
#> 3: 2.1 3.0
#> 4: 1.8 2.9
#> 5: 2.2 3.0
#> 6: 2.1 3.0
#>
#> $Petal.Length_setosa
#> Petal.Width value
#> <num> <num>
#> 1: 0.2 1.4
#> 2: 0.2 1.4
#> 3: 0.2 1.3
#> 4: 0.2 1.5
#> 5: 0.2 1.4
#> 6: 0.4 1.7
#>
#> $Petal.Length_versicolor
#> Petal.Width value
#> <num> <num>
#> 1: 1.4 4.7
#> 2: 1.5 4.5
#> 3: 1.5 4.9
#> 4: 1.3 4.0
#> 5: 1.5 4.6
#> 6: 1.3 4.5
#>
#> $Petal.Length_virginica
#> Petal.Width value
#> <num> <num>
#> 1: 2.5 6.0
#> 2: 1.9 5.1
#> 3: 2.1 5.9
#> 4: 1.8 5.6
#> 5: 2.2 5.8
#> 6: 2.1 6.6
# Example 3: Split specific columns using column names
list_res <- w2l_split(
data = iris, # Input dataset
cols = c("Sepal.Length", # Select columns by name
"Sepal.Width"),
by = "Species" # Split by Species column
)
lapply(list_res, head) # Show first 6 rows of each split
#> $Sepal.Length_setosa
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 1.4 0.2 5.1
#> 2: 1.4 0.2 4.9
#> 3: 1.3 0.2 4.7
#> 4: 1.5 0.2 4.6
#> 5: 1.4 0.2 5.0
#> 6: 1.7 0.4 5.4
#>
#> $Sepal.Length_versicolor
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 4.7 1.4 7.0
#> 2: 4.5 1.5 6.4
#> 3: 4.9 1.5 6.9
#> 4: 4.0 1.3 5.5
#> 5: 4.6 1.5 6.5
#> 6: 4.5 1.3 5.7
#>
#> $Sepal.Length_virginica
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 6.0 2.5 6.3
#> 2: 5.1 1.9 5.8
#> 3: 5.9 2.1 7.1
#> 4: 5.6 1.8 6.3
#> 5: 5.8 2.2 6.5
#> 6: 6.6 2.1 7.6
#>
#> $Sepal.Width_setosa
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 1.4 0.2 3.5
#> 2: 1.4 0.2 3.0
#> 3: 1.3 0.2 3.2
#> 4: 1.5 0.2 3.1
#> 5: 1.4 0.2 3.6
#> 6: 1.7 0.4 3.9
#>
#> $Sepal.Width_versicolor
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 4.7 1.4 3.2
#> 2: 4.5 1.5 3.2
#> 3: 4.9 1.5 3.1
#> 4: 4.0 1.3 2.3
#> 5: 4.6 1.5 2.8
#> 6: 4.5 1.3 2.8
#>
#> $Sepal.Width_virginica
#> Petal.Length Petal.Width value
#> <num> <num> <num>
#> 1: 6.0 2.5 3.3
#> 2: 5.1 1.9 2.7
#> 3: 5.9 2.1 3.0
#> 4: 5.6 1.8 2.9
#> 5: 5.8 2.2 3.0
#> 6: 6.6 2.1 3.0
# Returns similar structure to Example 2c2p_nest()
# Example data preparation: Define column names for combination
col_names <- c("Sepal.Length", "Sepal.Width", "Petal.Length")
# Example 1: Basic column-to-pairs nesting with custom separator
c2p_nest(
iris, # Input iris dataset
cols = col_names, # Columns to be combined as pairs
pairs_n = 2, # Create pairs of 2 columns
sep = "&" # Custom separator for pair names
)
#> pairs data
#> <char> <list>
#> 1: Sepal.Length&Sepal.Width <data.table[150x4]>
#> 2: Sepal.Length&Petal.Length <data.table[150x4]>
#> 3: Sepal.Width&Petal.Length <data.table[150x4]>
# Returns a nested data.table where:
# - pairs: combined column names (e.g., "Sepal.Length&Sepal.Width")
# - data: list column containing data.tables with value1, value2 columns
# Example 2: Column-to-pairs nesting with numeric indices and grouping
c2p_nest(
iris, # Input iris dataset
cols = 1:3, # First 3 columns to be combined
pairs_n = 2, # Create pairs of 2 columns
by = 5 # Group by 5th column (Species)
)
#> pairs Species data
#> <char> <fctr> <list>
#> 1: Sepal.Length-Sepal.Width setosa <data.table[50x3]>
#> 2: Sepal.Length-Sepal.Width versicolor <data.table[50x3]>
#> 3: Sepal.Length-Sepal.Width virginica <data.table[50x3]>
#> 4: Sepal.Length-Petal.Length setosa <data.table[50x3]>
#> 5: Sepal.Length-Petal.Length versicolor <data.table[50x3]>
#> 6: Sepal.Length-Petal.Length virginica <data.table[50x3]>
#> 7: Sepal.Width-Petal.Length setosa <data.table[50x3]>
#> 8: Sepal.Width-Petal.Length versicolor <data.table[50x3]>
#> 9: Sepal.Width-Petal.Length virginica <data.table[50x3]>
# Returns a nested data.table where:
# - pairs: combined column names
# - Species: grouping variable
# - data: list column containing data.tables grouped by Speciesr2p_nest()
# Example: the same traits recorded on the same animals in two farms
set.seed(1)
growth <- data.frame(
animal = rep(sprintf("A%02d", 1:6), each = 2),
farm = rep(c("farm1", "farm2"), times = 6),
adg = round(rnorm(12, 900, 50)), # average daily gain
bf = round(rnorm(12, 11, 1.5), 1) # backfat
)
# Example 1: column names
r2p_nest(
growth,
names_from = "farm", # levels become columns: farm1, farm2
cols = c("adg", "bf"), # traits to pivot
id = "animal" # aligns records of the same animal
)
#> name data
#> <char> <list>
#> 1: adg <data.table[6x3]>
#> 2: bf <data.table[6x3]>
# Returns a nested data.table where:
# - name: trait names (adg, bf)
# - data: one row per animal with columns animal, farm1, farm2
# Example 2: numeric indices
r2p_nest(growth, names_from = 2, cols = 3:4, id = 1)
#> name data
#> <char> <list>
#> 1: adg <data.table[6x3]>
#> 2: bf <data.table[6x3]>