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.
|Author||Nicholas Tierney [aut, cre], Di Cook [aut], Miles McBain [aut], Colin Fay [aut]|
|Date of publication||2017-08-09 04:06:29 UTC|
|Maintainer||Nicholas Tierney <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.