Refactor calculate_weighted_ownership function in predict_dupes.py: remove debug print statements, adjust ownership value calculations to handle percentages, and ensure the return value is in percentage form, improving clarity and accuracy of ownership metrics.

global_func/predict_dupes.py

@@ -11,35 +11,31 @@ def calculate_weighted_ownership(row_ownerships):
     (AVERAGE of (each value's average with overall average)) * count - (max - min)
     
     Args:
-        row_ownerships: Series containing ownership values for a row
+        row_ownerships: Series containing ownership values in percentage form (e.g., 24.2213 for 24.2213%)
         
     Returns:
         float: Calculated weighted ownership value
     """
-    print("Input row:", row_ownerships)  # Debug print
-    print("Type:", type(row_ownerships))  # Debug print
+    # Drop NaN values and convert percentages to decimals
+    row_ownerships = row_ownerships.dropna() / 100
     
     # Get the mean of all ownership values
     row_mean = row_ownerships.mean()
-    print("Row mean:", row_mean)  # Debug print
     
     # Calculate average of each value with the overall mean
     value_means = [(val + row_mean) / 2 for val in row_ownerships]
-    print("Value means:", value_means)  # Debug print
     
     # Take average of all those means
-    avg_of_means = sum(value_means) / len(value_means)
-    print("Average of means:", avg_of_means)  # Debug print
+    avg_of_means = sum(value_means) / len(row_ownerships)
     
     # Multiply by count of values
     weighted = avg_of_means * len(row_ownerships)
-    print("After multiplication:", weighted)  # Debug print
     
     # Subtract (max - min)
     weighted = weighted - (row_ownerships.max() - row_ownerships.min())
-    print("Final weighted:", weighted)  # Debug print
     
-    return weighted
+    # Convert back to percentage form to match input format
+    return weighted * 100
 
 def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, strength_var, sport_var):
     if strength_var == 'Weak':