Replace all 0 values to NA

Question

I have a dataframe with some numeric columns. Some row has a 0 value which should be considered as null in statistical analysis. What is the fastest way to replace all the 0

Answer 1

You can replace 0 with NA only in numeric fields (i.e. excluding things like factors), but it works on a column-by-column basis:

col[col == 0 & is.numeric(col)] <- NA

With a function, you can apply this to your whole data frame:

changetoNA <- function(colnum,df) {
    col <- df[,colnum]
    if (is.numeric(col)) {  #edit: verifying column is numeric
        col[col == -1 & is.numeric(col)] <- NA
    }
    return(col)
}
df <- data.frame(sapply(1:5, changetoNA, df))

Although you could replace the 1:5 with the number of columns in your data frame, or with 1:ncol(df).