densify: An R package to reduce empty cells in dataframes of typological linguistic data

The R package densify provides a procedure to prune input data frames containing empty cells (or cells with values {?} or {NA}) to denser sub-matrices with fewer empty cells.The pruning process trades off a series of variably weighted concerns, including data retention, coding density (proportion of non-empty cells) and taxonomic diversity of rows (representing for example phylogenetic relations).Users can adapt the relative weights given to these concerns through various parameters so that the densification process best fits their needs.As such, the software is useful for several purposes, including the densification of sparse input matrices and the subsampling of large input matrices according to a procedure that is sensitive to taxonomic structure.

Authors

Publication Details

Journal
The Journal of Open Source Software
Published
2024-09-06
DOI
https://doi.org/10.21105/joss.07024
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.69
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article

densify: An R package to reduce empty cells in dataframes of typological linguistic data

Reinhard Furrer, Anna Graff, Balthasar Bickel, Taras Zakharko et al.
2 citations
The Journal of Open Source Software
Natural Language Processing Techniques
0.69
article

densify: An R package to reduce empty cells in dataframes of typological linguistic data

Reinhard Furrer, Anna Graff, Balthasar Bickel, Taras Zakharko, Marc Lischka
article en
2 citations

Abstract

The R package densify provides a procedure to prune input data frames containing empty cells (or cells with values {?} or {NA}) to denser sub-matrices with fewer empty cells.The pruning process trades off a series of variably weighted concerns, including data retention, coding density (proportion of non-empty cells) and taxonomic diversity of rows (representing for example phylogenetic relations).Users can adapt the relative weights given to these concerns through various parameters so that the densification process best fits their needs.As such, the software is useful for several purposes, including the densification of sparse input matrices and the subsampling of large input matrices according to a procedure that is sensitive to taxonomic structure.

The Journal of Open Source SoftwareVol. 9(101)
Openalex Percentile: Top 25%
Natural Language Processing Techniques
0.69
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