Missing pattern analysis for missing data

Source: R/missingPattern.R

This function is used to summarise the missing variable, missing pattern identification and classifying the columns based on the pattern of missing values.

misspattern(data, mfeature, drop = 0.99, print = FALSE)

Arguments

data

[data.frame | Required] data set with missing values
mfeature

[character | Required] only missing variable name
drop

[numeric | optional] drop variable percentage. Example, if drop = 0.9, function will automatically drop 90per missing columns from the data set
print

[character | optional] defualt print is FALSE

Value

final variable list, summary of missing data analysis

Examples

## Sample iris data
mdata <- iris
mobject <- misspattern(mdata, mfeature = c("Sepal.Length", "Petal.Length"), drop = 0.99, print = F)