Column to Pair Nested Transformation

A sophisticated data transformation tool for generating column pair combinations and creating nested data structures with advanced configuration options.

c2p_nest(data, cols2bind, by = NULL, pairs_n = 2, sep = "-", nest_type = "dt")

Arguments

data

Input data frame or data table

• Must contain valid columns for transformation

• Supports multiple data types

cols2bind

Column specification for pair generation

• Can be a character vector of column names

• Can be a numeric vector of column indices

• Must reference existing columns in the dataset

by

Optional grouping specification

• Can be a character vector of column names

• Can be a numeric vector of column indices

• Enables hierarchical nested transformations

• Supports multi-level aggregation

• Default is NULL

pairs_n

numeric indicating combination size

• Minimum value: 2

• Maximum value: Length of cols2bind

• Controls column pair complexity

• Default is 2

sep

character separator for pair naming

• Used in generating combination identifiers

• Must be a single character

• Default is "-"

nest_type

Output nesting format

• "dt": Returns nested data table (default)

• "df": Returns nested data frame

Value

data table containing nested transformation results

• Includes pairs column identifying column combinations

• Contains data column storing nested data structures

• Supports optional grouping variables

Details

Advanced Transformation Mechanism:

1. Input validation and preprocessing

2. Dynamic column combination generation

3. Flexible pair transformation

4. Nested data structure creation

Transformation Process:

• Validate input parameters and column specifications

• Convert numeric indices to column names if necessary

• Generate column combinations

• Create subset data tables

• Merge and nest transformed data

Column Specification:

• Supports both column names and numeric indices

• Numeric indices must be within valid range (1 to ncol)

• Column names must exist in the dataset

• Flexible specification for both cols2bind and by parameters

Note

Key Operation Constraints:

• Requires non-empty input data

• Column specifications must be valid (either names or indices)

• Supports flexible combination strategies

• Computational complexity increases with combination size

See also

• utils::combn() Combination generation

Examples

# 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
  cols2bind = 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
  cols2bind = 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 Species