plotNA {analyzer}

Missing value visualization using ggplot2

Description

plotNA returns a grob visualizing the missing values in data

Usage

plotNA(tb, order = T, limit = T, add_percent = T, row.level = F)

Arguments

tb

a data.frame

order

(logical) Whether to order the variables based on missing values in plot

limit

(logical) Whether to limit the plot to maximum missing value. FALSE means the limit of axis will be [0, nrow(tb)]

add_percent

(logical) Whether to add percent as data labels on bar plot

row.level

(logical) Whether to create plot at rows and variables level

Details

This is a function which helps in visualizing the missing values in data using plots. By default a bar plot is generated which shows the count of missing values in each variable.

If order is set as TRUE then the bars are arranged in order of missing values. If limit is set as TRUE then limit of axis is set to [0, nrow(tb)]. If add_percent is set as TRUE then percent is added as text to the bars. If row.level is set to TRUE then an additional plot is generated which shows which rows have missing values and in which variable (reshape2 (https://CRAN.R-project.org/package=reshape2) library is required for this).

Value

This function returns a grob of class 'analyzePlot' which has a bar plot showing the count of missing value for each variable. order, limit, add_percent can be used to modify the bar plot. An additional plot will be created and added to the grob if row.level is set as TRUE

Examples

p <- plotNA(airquality)
# function to show the 'analyzerPlot' class plot
plot(p)
p1 <- plotNA(airquality, order = FALSE)
plot(p1)