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📦 bedrock

Title: Base Functions for the DescToolsX Ecosystem
License: GPL (≥ 2)

🧩 Overview

bedrock is the foundation layer of the DescToolsX ecosystem. It provides low-level, generic utilities and basic routines — data manipulation, inspection, vector operations, string handling, math and combinatorics — that serve as building blocks for the higher-level statistical, graphics, and modelling packages of the suite.

The package is self-contained. It has no dependency on any other package of the suite and is equally useful on its own.

It follows the DescToolsX design rules: a consistent lowerCamelCase API, generic functions with S3 methods, predictable argument names and ordering, and performance-critical routines implemented in Rcpp.

📖 Documentation: https://andrisignorell.github.io/bedrock/

⚙️ Installation

Install the released version from CRAN:

install.packages("bedrock")

Or the development version from GitHub:

remotes::install_github("AndriSignorell/bedrock")

📚 Core Features

🔹 Data Manipulation

Appending, recoding, renaming, sorting, and reshaping of vectors, factors, matrices, and data frames.

• appendX(), appendRowNames(), appendEnum()
• recodeX(), revCode(), combLevels(), dummy()
• sortX(), revX(), renameX(), setNamesX()
• splitX(), splitAt(), toLong() / toWide()
• recycle(), columnWrap(), compareDataFrames()
• toBaseR(), stringsAsFactors()
• Type coercion shortcuts: num(), int(), chr(), nchr(), bin()

🔹 Data Inspection & Validation

Predicates and checks for data quality and structure.

• isNumeric(), isDichotomous(), isLowCardinality(), isWholeLike(), isZero(), isNA()
• allDuplicated(), allIdentical(), completeColumns(), countCompCases(), flags()
• Between operators: %[]%, %()%, %[)%, %(]%
• isFilePath(), isURL(), isEuclid()

🔹 Vector Operations

• coalesceX(), closest(), locf()
• naIf(), naReplace(), nz()
• trim(), winsorize(), setLength()
• moveAvg(), midx(), vRot(), vShift(), pairApply()

🔹 String Utilities

• mGsub(), mReplace()
• strSplitToCol(), strSplitToDummy()
• charToAscii() / asciiToChar(), asCDateFmt()

🔹 Mathematical Functions

• roundTo(), linScale(), logit()
• nDec(), prec(), frac(), maxDigits()
• rankX(), percentRank(), nUnique()
• dotProd(), crossProd(), crossProdN()
• unirootAll(), untable()

🔹 Number Theory & Combinatorics

• primes(), isPrime(), factorize(), divisors()
• GCD() / LCM(), fibonacci(), digitSum(), isOdd()
• Base conversions: decToBin(), decToHex(), decToOct(), baseToBase(), romanToInt()
• combN(), combSet(), combPairs(), permn()
• sampleX(), randGroupSplit(), unwhich()

🔹 Tables & Merging

• collapseTable(), multMerge(), printCharMatrix()

🔹 Labels & Metadata

• label() — get or set variable labels
• setAttr(), removeAttr(), keepAttr()
• openDataObject(), dataDescription() — Excel data with codes and labels

🔹 File Utilities

• buildPath(), splitPath()
• findDownload(), readDownload(), peekFile()
• fileExistURL(), pdfManual()
• parseSASDatalines() — parse SAS DATALINES blocks into a data.frame

🔹 Programming & Introspection

• callIf(), mergeArgs(), extractArgs(), getDotsArg(), quot()
• resolveFormula(), resolveGroups(), resolveContingency()
• funArgs(), funCalls(), funList(), funKeywords()
• rdTitle(), rdLabels(), strX()

🔹 Datasets

Teaching and example datasets: Cards, Pizza, Roulette, Tarot, plus courseData() for loading course material.

🚀 Design Principles

• Consistent — lowerCamelCase API and uniform argument conventions across the whole DescToolsX suite
• Fast — performance-critical routines implemented in Rcpp
• Generic — S3 generics with methods for vectors, factors, matrices, tables, and data frames
• Robust — validated inputs, informative errors, extensive testthat coverage

🧪 Example

library(bedrock)

# range operators
x <- 1:10
x %[]% c(3, 6)

# first non-missing value
coalesceX(c(NA, NA, 5, 3))

# round to arbitrary multiples
roundTo(c(1.23, 4.56), 0.25)

# all 2-element subsets
combSet(letters[1:4], 2)

# parse a SAS data step
sas <- "
  data mydata;
    input name $ age score;
  datalines;
  Alice 30 95.5
  Bob   25 88.0
  ;
"
parseSASDatalines(sas)

🙏 Acknowledgements

Parts of the code and documentation were reviewed with the help of large language models (OpenAI Codex, Anthropic Claude). Every suggestion was assessed, edited and verified by the maintainer, who remains solely responsible for the content of this package.

📜 License

GPL (≥ 2)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.