add_miss_cluster: Add a column that tells us which "missingness cluster" a row...

In njtierney/naniar: Data Structures, Summaries, and Visualisations for Missing Data

Add a column that tells us which "missingness cluster" a row belongs to

Description

A way to extract the cluster of missingness that a group belongs to. For example, if you use vis_miss(airquality, cluster = TRUE), you can see some clustering in the data, but you do not have a way to identify the cluster. Future work will incorporate the seriation package to allow for better control over the clustering from the user.

Usage

add_miss_cluster(data, cluster_method = "mcquitty", n_clusters = 2)

Arguments

data	a dataframe
cluster_method	character vector of the agglomeration method to use, the default is "mcquitty". Options are taken from stats::hclust helpfile, and options include: "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).
n_clusters	numeric the number of clusters you expect. Defaults to 2.

See Also

bind_shadow() add_any_miss() add_label_missings() add_label_shadow() add_miss_cluster() add_n_miss() add_prop_miss() add_shadow_shift() cast_shadow()

Examples

add_miss_cluster(airquality)
add_miss_cluster(airquality, n_clusters = 3)
add_miss_cluster(airquality, cluster_method = "ward.D", n_clusters = 3)

njtierney/naniar documentation built on March 19, 2024, 9:48 p.m.