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Row-Wise Value Classifier

dot-dr_row_classifier.Rd

This function classifies the values in a set of input vectors row-wise based on specific rules. It supports numeric, logical, and categorical (non-numeric) vectors, applying type-specific classifications and producing a combined classification for each row as a delimited string.

Usage

.dr_row_classifier(...)

Arguments

...

A series of numeric, logical, or categorical vectors to classify. All vectors must be of the same length.

Value

A character vector, with one element per row of input, containing the concatenated classifications for each row.

Details

Classification Rules:

  • Numeric or Logical Variables:

    • NA: Missing values are classified as "NA".

    • 0: Values equal to 0 (or FALSE for logicals) are classified as "0".

    • >0: Positive values (or TRUE for logicals) are classified as ">0".

    • <=0: Negative values are classified as "<=0".

  • Categorical (Non-Numeric) Variables:

    • "a": Non-missing values are classified generically as "a".

    • "NA": Missing values are classified as "NA".

Output:

The function outputs a combined classification for each row, concatenated using "_" to separate the classifications for all input vectors.

Examples

var1 <- c(NA, 0, 1, 2)           # Numeric
var2 <- c(0, 1, NA, 3)           # Numeric
var3 <- c(NA, NA, 2, 0)          # Numeric
var4 <- c("a", "b", NA, "c")     # Categorical
var5 <- c(TRUE, FALSE, NA, TRUE) # Logical

classifications <- .dr_row_classifier(var1, var2, var3, var4, var5)
print(classifications)
#> [1] "NA_0_NA_a_>0"   "0_>0_NA_a_0"    ">0_NA_>0_NA_NA" ">0_>0_0_a_>0"  

## Output:
# [1] "NA_0_NA_a_>0" "0_>0_NA_a_0" ">0_NA_>0_NA_NA" ">0_>0_0_a_>0"