Prepare numeric data safely for analysis

Safely coerces selected variables in a data frame to numeric format while preserving column names and replacing non-finite values (Inf, -Inf, NaN) with NA.

Usage

PrepNumericData(df, variables = names(df))

Arguments

df

A data frame.

variables

Character vector of variable names to process. Defaults to all columns.

Value

A data frame with selected variables converted to numeric and non-finite values replaced with NA.

Details

This function is useful for preparing real-world biomedical, omics, and survey datasets for downstream statistical analyses such as correlations, PCA, clustering, regression, and factor analysis.

Character and factor variables are converted using as.numeric(as.character(x)) to avoid incorrect factor level coercion.

Examples

df <- data.frame(
  x = c("1", "2", "3"),
  y = c(1, 2, Inf),
  z = factor(c("4", "5", "6"))
)

PrepNumericData(df)
#>   x  y z
#> 1 1  1 4
#> 2 2  2 5
#> 3 3 NA 6