Description Usage Arguments Details Examples
Visualize distribution of missing value by combination of variables.
1 2 3 4 5 6 7 | plot_na_hclust(
x,
main = NULL,
col.left = "#009E73",
col.right = "#56B4E9",
typographic = TRUE
)
|
x |
data frames, or objects to be coerced to one. |
main |
character. Main title. |
col.left |
character. The color of left legend that is frequency of NA. default is "#009E73". |
col.right |
character. The color of right legend that is percentage of NA. default is "#56B4E9". |
typographic |
logical. Whether to apply focuses on typographic elements to ggplot2 visualization. The default is TRUE. if TRUE provides a base theme that focuses on typographic elements using hrbrthemes package. |
Rows are variables containing missing values, and columns are observations. These data structures were grouped into similar groups by applying hclust. So, it was made possible to visually examine how the missing values are distributed for each combination of variables.
1 2 3 4 5 6 7 8 9 10 11 12 | # Generate data for the example
set.seed(123L)
jobchange2 <- jobchange[sample(nrow(jobchange), size = 1000), ]
# Visualize hcluster chart for variables with missing value.
plot_na_hclust(jobchange2)
# Change the main title.
plot_na_hclust(jobchange2, main = "Distribution of missing value")
# Not support typographic elements
plot_na_hclust(jobchange2, typographic = FALSE)
|
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