c2p_nest: Column to Pair Nested Transformation

In mintyr: Streamlined Data Processing Tools for Genomic Selection

Column to Pair Nested Transformation

Description

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

Usage

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

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

Value

⁠data table⁠ containing nested transformation results

• Includes pairs column identifying column combinations

• Contains data column storing nested data structures

• Supports optional grouping variables

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
)
# 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)
)
# Returns a nested data.table where:
# - pairs: combined column names
# - Species: grouping variable
# - data: list column containing data.tables grouped by Species

mintyr documentation built on April 4, 2025, 2:56 a.m.