codecountR: Counting Codes in a Text and Preparing Data for Analysis

Data analysis frequently requires coding, in particular when data are collected by interviews, by observations or even by questionnaires. Therefore, code counting and data preparation are necessary phases to carry out the analysis. Thus, the analysts will wish to count the codes inserted in a text (tokenization and counting of a list of pre-established codes) and to carry out the preparation of the data (feature scaling min-max normalization, Zscore, Box and Cox transformation, non parametric bootstrap). For Box and Cox (1964) <https://www.jstor.org/stable/2984418> transformation, optimal Lambda is calculated by log-likelihood. Non parametric bootstrap is based on randomly sampling data with replacement. Package for educational purposes.

Version: 0.0.4.0
Imports: stats
Suggests: knitr, rmarkdown
Published: 2023-12-07
Author: Philippe Cohard [aut, cre]
Maintainer: Philippe Cohard <p.cohard at laposte.net>
License: GPL-3
NeedsCompilation: no
CRAN checks: codecountR results

Documentation:

Reference manual: codecountR.pdf
Vignettes: How_to_use_codeCountR

Downloads:

Package source: codecountR_0.0.4.0.tar.gz
Windows binaries: r-devel: codecountR_0.0.4.0.zip, r-release: codecountR_0.0.4.0.zip, r-oldrel: codecountR_0.0.4.0.zip
macOS binaries: r-release (arm64): codecountR_0.0.4.0.tgz, r-oldrel (arm64): codecountR_0.0.4.0.tgz, r-release (x86_64): codecountR_0.0.4.0.tgz, r-oldrel (x86_64): codecountR_0.0.4.0.tgz
Old sources: codecountR archive

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