Complete dropped albums list with all 89 truly dropped albums from 2020

- Added all 89 albums that were genuinely dropped from 2020 to 2023
- Fixed incorrect status markings (many albums marked "New in 2023" were not new)
- Removed duplicates and albums incorrectly marked as dropped
- Final count: 589 total (500 main list + 89 dropped)
- Updated JavaScript validation for extended range
- Created comprehensive analysis scripts to verify data

Math now adds up correctly: 89 albums dropped to make room for new additions

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

scripts/remove_duplicate_dropped.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+"""
+Remove duplicate dropped albums that have slightly different names.
+"""
+
+import csv
+
+def normalize_for_comparison(text):
+    """Normalize album names for duplicate detection"""
+    text = text.lower().strip()
+    # Remove "The" from album names in parentheses
+    text = text.replace('(the black album)', '(black album)')
+    text = text.replace('(the blue album)', '(blue album)')
+    return text
+
+def main():
+    # Read current CSV
+    albums = []
+    with open('top_500_albums_2023.csv', 'r', encoding='utf-8') as file:
+        reader = csv.DictReader(file)
+        for row in reader:
+            albums.append(row)
+    
+    print(f"📊 Total albums before cleanup: {len(albums)}")
+    
+    # Find duplicates among dropped albums
+    seen_dropped = {}
+    duplicates = []
+    
+    for i, album in enumerate(albums):
+        if 'Dropped' in album['Status']:
+            key = (normalize_for_comparison(album['Artist']), 
+                   normalize_for_comparison(album['Album']))
+            
+            if key in seen_dropped:
+                print(f"❌ Duplicate found:")
+                print(f"   First:  Rank {seen_dropped[key]['Rank']} - {seen_dropped[key]['Artist']} - {seen_dropped[key]['Album']}")
+                print(f"   Second: Rank {album['Rank']} - {album['Artist']} - {album['Album']}")
+                duplicates.append(i)
+            else:
+                seen_dropped[key] = album
+    
+    # Remove duplicates
+    if duplicates:
+        print(f"\n🗑️  Removing {len(duplicates)} duplicate entries...")
+        # Remove in reverse order to maintain indices
+        for i in reversed(duplicates):
+            del albums[i]
+        
+        # Renumber albums after 500
+        current_rank = 501
+        for album in albums:
+            if int(album['Rank']) > 500:
+                album['Rank'] = str(current_rank)
+                current_rank += 1
+    
+    # Write cleaned CSV
+    with open('top_500_albums_2023.csv', 'w', newline='', encoding='utf-8') as file:
+        fieldnames = ['Rank', 'Artist', 'Album', 'Status', 'Info', 'Description']
+        writer = csv.DictWriter(file, fieldnames=fieldnames)
+        writer.writeheader()
+        writer.writerows(albums)
+    
+    print(f"\n✅ Cleanup complete!")
+    print(f"📊 Total albums now: {len(albums)}")
+    print(f"📊 Total dropped albums: {len([a for a in albums if 'Dropped' in a['Status']])}")
+
+if __name__ == "__main__":
+    main()