plot.imputation: Visualize Information for an "imputation" Object

In bit2r/kodlookr: Korean Help Resources for the dlookr Package

Description

Visualize two kinds of plot by attribute of imputation class. The imputation of a numerical variable is a density plot, and the imputation of a categorical variable is a bar plot.

Usage

plot.imputation(x, typographic = TRUE, ...)

Arguments

x	an object of class "imputation", usually, a result of a call to imputate_na() or imputate_outlier().
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.
...	arguments to be passed to methods, such as graphical parameters (see par). only applies when the model argument is TRUE, and is used for ... of the plot.lm() function.

See Also

imputate_na, imputate_outlier, summary.imputation.

Examples

# Generate data for the example
heartfailure2 <- heartfailure
heartfailure2[sample(seq(NROW(heartfailure2)), 20), "platelets"] <- NA
heartfailure2[sample(seq(NROW(heartfailure2)), 5), "smoking"] <- NA

# Impute missing values -----------------------------
# If the variable of interest is a numerical variables
platelets <- imputate_na(heartfailure2, platelets, death_event, method = "rpart")
platelets
summary(platelets)

plot(platelets)

# If the variable of interest is a categorical variables
smoking <- imputate_na(heartfailure2, smoking, death_event, method = "mice")
smoking
summary(smoking)

plot(smoking)

# Impute outliers ----------------------------------
# If the variable of interest is a numerical variable
platelets <- imputate_outlier(heartfailure2, platelets, method = "capping")
platelets
summary(platelets)

plot(platelets)

bit2r/kodlookr documentation built on Dec. 19, 2021, 9:49 a.m.