naniar: Data Structures, Summaries, and Visualisations for Missing Data

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>.

Package details

AuthorNicholas Tierney [aut, cre] (<https://orcid.org/0000-0003-1460-8722>), Di Cook [aut] (<https://orcid.org/0000-0002-3813-7155>), Miles McBain [aut] (<https://orcid.org/0000-0003-2865-2548>), Colin Fay [aut] (<https://orcid.org/0000-0001-7343-1846>), Mitchell O'Hara-Wild [ctb], Jim Hester [ctb], Luke Smith [ctb], Andrew Heiss [ctb] (<https://orcid.org/0000-0002-3948-3914>)
MaintainerNicholas Tierney <nicholas.tierney@gmail.com>
LicenseMIT + file LICENSE
Version1.1.0
URL https://github.com/njtierney/naniar http://naniar.njtierney.com/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("naniar")

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naniar documentation built on May 29, 2024, 1:43 a.m.