uci-ml-to-r/data-collection/bank-marketing/preprocess.R

preprocess.dataset = function()
{
    temp.dir = tempdir()
    
    zip.file         = "bank.zip"
    zip.dataset.path = "bank-full.csv"
    
    flog.debug(paste("Unzipping", zip.file))
    
    unzip(zipfile = file.path(orig.dir, zip.file),
          files   = zip.dataset.path,
          exdir   = temp.dir)
    
    flog.debug(paste("Loading", zip.dataset.path))
    
    dataset = read.csv(file.path(temp.dir, zip.dataset.path), sep = ";")
    
    flog.debug("Preprocessing loaded dataset")
    
    dataset = dataset %>% 
        select(-c(duration, default)) %>%
        filter(job != "unknown" & marital != "unknown" & education != "unknown" & 
               education != "unknown" & housing != "unknown" & 
               loan != "unknown") %>%
        droplevels()
    
    dataset = dataset %>% 
        mutate(
            education = factor(education, 
                               levels  = c("primary", "secondary", "tertiary"),
                               ordered = TRUE),
            month = factor(month, 
                           levels  = c("jan", "feb", "mar", "apr", "may", "jun", 
                                       "jul", "aug", "sep", "oct", "nov", "dec"), 
                           ordered = TRUE),
            pdays.bin = revalue(factor(pdays == -1), 
                                c("TRUE" = "never", "FALSE" = "successful")), 
            pdays = as.integer(replace(pdays, pdays == -1, 999))) %>%
        select(age:pdays, pdays.bin, previous:y)
    
    unlink("temp.dir", recursive = TRUE)
    
    return(dataset)
}