https://github.com/clewerenz/ilabelled

R package ilabelled
https://github.com/clewerenz/ilabelled

r

Last synced: 4 months ago
JSON representation

R package ilabelled

• Host: GitHub
• URL: https://github.com/clewerenz/ilabelled
• Owner: clewerenz
• License: other
• Created: 2023-09-18T09:24:18.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-21T15:18:30.000Z (8 months ago)
• Last Synced: 2024-11-28T22:41:35.012Z (5 months ago)
• Topics: r
• Language: R
• Homepage:
• Size: 353 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• jimsghstars - clewerenz/ilabelled - R package ilabelled (R)

README

        
This is the development repository for the R package ilabelled.

# ilabelled

A function library for working with labelled data in R. This package introduces the data class 'i_labelled' for atomic vector objects which can be used within data.frames.

## Installation

Install from CRAN install.packages('ilabelled') or the development version from this github repository remotes::install_github('https://github.com/clewerenz/ilabelled')

At this state of development the package version on github is ahead of CRAN's version, since the package is still under development in order to take specific use cases into account.

## Context

R is a great software for working with data. However, there is a non-negligible disadvantage when it comes to handling categorical data and meta-information, such as variable labels or scale levels, and the like, as known from other statistical software, especially SPSS.

The aim of this package is to introduce a data class in which meta information (variable-label, value-labels, missing-values, scale-level) can and should be directly included. In addition, one of the biggest disadvantages of the base R factor class is to be addressed: Numerical values are not changed if they are provided with value labels. Negative and non-sequential consecutive values are not changed. In other words: the underlying database is not changed by labeling. Nevertheless, the option of using value labels for indexing is offered. 

An intuitive syntax enables easy access to package-specific functions. All functions available for data manipulation can be controlled by an “i_*”.

### Motivation

  - Data consistency 

    - Allow labeling of values <= 0 without altering them

    - Allow labeling of non-sequential values without altering them

      - Do not change numeric data when data is labelled (as factors do) 

    - Do not loose attributes when recoding or subsetting data

  - Easy access 

    - Intuitive functions for handling labels and missing values 

    - Transparency: Show meta-information (e.g. value-labels, missing-values, etc.) when data is printed

  - Metadata management:

    - Metadata in form of attributes can easily be set and altered by dedicated functions.

  - Easy validation 

    - Missing and incorrect meta-information

  - Reduce dependencies 

    - The most possible minimum of third party dependencies. Right now the package depends on no third party libraries besides packages which come with the installation of R.

### Inspiration

The inspiration for this package was drawn from the [lfactors](https://github.com/pdbailey0/lfactors) package, the [labelled](https://github.com/larmarange/labelled) package and the [sticky](https://github.com/cran/sticky) package with the aim to bring dependencies on bloated third party libraries to zero. The self-understanding of this package is not to be better than comparable libraries, but be a lightweight and slightly more intuitive alternative.