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naniar: Data Structures, Summaries, and Visualisations for Missing Data (original) (raw)

Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2023) <doi:10.18637/jss.v105.i07>.

Version: 1.1.0
Depends: R (≥ 3.1.2)
Imports: dplyr, ggplot2, purrr, tidyr, tibble (≥ 2.0.0), norm, magrittr, stats, visdat, rlang (≥ 1.1.0), forcats, viridis, glue, UpSetR, cli, vctrs, lifecycle
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), rpart, rpart.plot, covr, gridExtra, wakefield, vdiffr, here, simputation, imputeTS, Hmisc, spelling
Published: 2024-03-05
DOI: 10.32614/CRAN.package.naniar
Author: Nicholas Tierney ORCID iD [aut, cre], Di Cook ORCID iD [aut], Miles McBain ORCID iD [aut], Colin Fay ORCID iD [aut], Mitchell O'Hara-Wild [ctb], Jim Hester [ctb], Luke Smith [ctb], Andrew Heiss ORCID iD [ctb]
Maintainer: Nicholas Tierney <nicholas.tierney at gmail.com>
BugReports: https://github.com/njtierney/naniar/issues
License: MIT + file
URL: https://github.com/njtierney/naniar, http://naniar.njtierney.com/
NeedsCompilation: no
Language: en-US
Citation: naniar citation info
Materials: README, NEWS
In views: MissingData
CRAN checks: naniar results

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