dlookr (version 0.6.3)

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

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

# S3 method for imputation
plot(x, typographic = TRUE, base_family = NULL, ...)

Value

A ggplot2 object.

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.

base_family

character. The name of the base font family to use for the visualization. If not specified, the font defined in dlookr is applied. (See details)

...

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.

Details

The base_family is selected from "Roboto Condensed", "Liberation Sans Narrow", "NanumSquare", "Noto Sans Korean". If you want to use a different font, use it after loading the Google font with import_google_font().

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, yvar = death_event, method = "rpart")
plot(platelets)

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

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