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.

Version: 0.2.0
Depends: R (≥ 3.1.2)
Imports: dplyr, ggplot2, purrr, tidyr, tibble, magrittr, stats, visdat, purrrlyr, rlang, forcats, viridis, glue
Suggests: knitr, rmarkdown, testthat, rpart, rpart.plot, covr, gridExtra, wakefield, vdiffr, here, simputation, imputeTS
Published: 2018-02-09
Author: Nicholas Tierney ORCID iD [aut, cre], Di Cook ORCID iD [aut], Miles McBain ORCID iD [aut], Colin Fay ORCID iD [aut], Jim Hester [ctb]
Maintainer: Nicholas Tierney <nicholas.tierney at gmail.com>
BugReports: https://github.com/njtierney/naniar/issues
License: MIT + file LICENSE
URL: https://github.com/njtierney/naniar
NeedsCompilation: no
Materials: README NEWS
CRAN checks: naniar results

Downloads:

Reference manual: naniar.pdf
Vignettes: Getting Started with naniar
Gallery of Missing Data Visualisations
Replacing values with NA
Package source: naniar_0.2.0.tar.gz
Windows binaries: r-devel: naniar_0.2.0.zip, r-release: naniar_0.2.0.zip, r-oldrel: naniar_0.2.0.zip
OS X binaries: r-release: naniar_0.2.0.tgz, r-oldrel: naniar_0.2.0.tgz
Old sources: naniar archive

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