Enhance gg_partial function to normalize factor levels and handle empty categorical lists

Author: ehrlinger

R/gg_partial.R

@@ -75,8 +75,15 @@ gg_partial <- function(part_dta,
       ## ---- Categorical variable: few unique x values -------------------
       ## VarPro works with logical or continuous only; factors are
       ## one-hot encoded internally in the varPro call.
+      ## Normalize factors so ordered/regular factors bind cleanly later.
+      x_factor <- if (is.factor(x_vals)) {
+        factor(as.character(x_vals), levels = levels(x_vals))
+      } else {
+        factor(x_vals)
+      }
+
       plt.df <- dplyr::bind_cols(
-        x    = factor(x_vals),
+        x    = x_factor,
         yhat = part_dta$plotthis[[feature]]$yhat
       )
       plt.df$name <- names(part_dta$plotthis)[[feature]]
@@ -87,8 +94,11 @@ gg_partial <- function(part_dta,
 
   # Combine per-variable lists into single data frames (NULL entries dropped)
   continuous  <- dplyr::bind_rows(cont_list)
-  categorical <- dplyr::bind_rows(cat_list)
-
+  if(length(cat_list) == 0) {
+    categorical <- NA
+  } else {
+    categorical <- dplyr::bind_rows(cat_list)
+  }
   ## Optionally attach a model label (useful when overlaying multiple forests)
   if (!is.null(model)) {
     continuous$model <- categorical$model <- model