character refine

plots.py

@@ -40,8 +40,9 @@ def plot_average_scores_with_counts(
         Plotly figure object.
     """
     # Calculate average and count of non-null values for each column
+    # Exclude _recordId column
     stats = []
-    for col in df.columns:
+    for col in [c for c in df.columns if c != '_recordId']:
         avg_score = df[col].mean()
         non_null_count = df[col].drop_nulls().len()
         stats.append({
@@ -126,8 +127,9 @@ def plot_top3_ranking_distribution(
     go.Figure
         Plotly figure object.
     """
+    # Exclude _recordId column
     stats = []
-    for col in df.columns:
+    for col in [c for c in df.columns if c != '_recordId']:
         # Count occurrences of each rank (1, 2, 3)
         # We ensure we're just counting the specific integer values
         rank1 = df.filter(pl.col(col) == 1).height