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 (2018) <arXiv:1809.02264>.
Version: | 0.6.1 |
Depends: | R (≥ 3.1.2) |
Imports: | dplyr, ggplot2, purrr, tidyr, tibble (≥ 2.0.0), norm, magrittr, stats, visdat, rlang, forcats, viridis, glue, UpSetR |
Suggests: | knitr, rmarkdown, testthat (≥ 2.1.0), rpart, rpart.plot, covr, gridExtra, wakefield, vdiffr, here, simputation, imputeTS, gdtools, Hmisc, spelling |
Published: | 2021-05-14 |
Author: | Nicholas Tierney |
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 |
Language: | en-US |
Materials: | README NEWS |
In views: | MissingData |
CRAN checks: | naniar results |
Reference manual: | naniar.pdf |
Vignettes: |
Exploring Imputed Values Getting Started with naniar Gallery of Missing Data Visualisations Replacing values with NA Special Missing Values |
Package source: | naniar_0.6.1.tar.gz |
Windows binaries: | r-devel: naniar_0.6.1.zip, r-release: naniar_0.6.1.zip, r-oldrel: naniar_0.6.1.zip |
macOS binaries: | r-release (arm64): naniar_0.6.1.tgz, r-oldrel (arm64): naniar_0.6.1.tgz, r-release (x86_64): naniar_0.6.1.tgz, r-oldrel (x86_64): naniar_0.6.1.tgz |
Old sources: | naniar archive |
Reverse imports: | povcalnetR, suddengains |
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