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Data cleaning

Source: R/data_clean.R
data_clean.Rd

Check some common errors of a raw dataset and return a suitable dataset to be fed into the imputer. Note that this function is just a preliminary check. It will not guarantee the output dataset is fully cleaned.

Usage

data_clean(rawdata, levels.tol = 0.2)

Arguments

rawdata

A data frame.

levels.tol

Tolerant proportion of the number of levels to the number of observations in a multiclass variable. Default: 0.2

Value

A preliminary cleaned dataset

Examples

data(nhanes3)
rawdata <- nhanes3

rawdata[4, 4] <- NaN
rawdata[5, 5] <- Inf
rawdata[6, 6] <- -Inf

cleandata <- data_clean(rawdata = rawdata)
#> Warning: There exists at least one entry coded as NaN in the following numeric variable(s): head_circumference_cm.
#> It is now coverted to NA instead.
#> Warning: There exists at least one entry coded as Inf or -Inf in the following variable(s): recumbent_length_cm;weight_kg.
#> It is now coverted to NA instead.