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: 0.1.0
Depends: R (≥ 3.1.2)
Imports: dplyr, ggplot2, purrr, tidyr, tibble, magrittr, stats, visdat, purrrlyr, rlang, forcats, viridis
Suggests: knitr, rmarkdown, testthat, rpart, rpart.plot, covr, gridExtra, wakefield, vdiffr, here, simputation, imputeTS
Published: 2017-08-09
Author: Nicholas Tierney [aut, cre], Di Cook [aut], Miles McBain [aut], Colin Fay [aut]
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
Package source: naniar_0.1.0.tar.gz
Windows binaries: r-devel: naniar_0.1.0.zip, r-release: naniar_0.1.0.zip, r-oldrel: naniar_0.1.0.zip
OS X El Capitan binaries: r-release: naniar_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: naniar_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=naniar to link to this page.