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/find_all_dropped.py

@@ -0,0 +1,79 @@
+#!/usr/bin/env python3
+"""
+Find ALL albums that were dropped from 2020 to 2023 by comparing the lists.
+"""
+
+import csv
+
+def normalize_text(text):
+    """Normalize text for comparison"""
+    return text.lower().strip().replace('&', 'and').replace('  ', ' ')
+
+def main():
+    # Read 2020 albums (simplified)
+    albums_2020 = {}
+    with open('rolling_stone_2020_simple.csv', 'r', encoding='utf-8') as file:
+        reader = csv.DictReader(file)
+        for row in reader:
+            key = (normalize_text(row['Artist']), normalize_text(row['Album']))
+            albums_2020[key] = {
+                'rank': row['Rank'],
+                'artist': row['Artist'],
+                'album': row['Album']
+            }
+    
+    print(f"📊 Loaded {len(albums_2020)} albums from 2020 list")
+    
+    # Read 2023 albums (only first 500)
+    albums_2023 = set()
+    new_count = 0
+    with open('top_500_albums_2023.csv', 'r', encoding='utf-8') as file:
+        reader = csv.DictReader(file)
+        for row in reader:
+            rank = int(row['Rank'])
+            if rank <= 500:
+                key = (normalize_text(row['Artist']), normalize_text(row['Album']))
+                albums_2023.add(key)
+                if row['Status'] == 'New in 2023':
+                    new_count += 1
+    
+    print(f"📊 Loaded {len(albums_2023)} albums from 2023 list")
+    print(f"🆕 Found {new_count} albums marked as 'New in 2023'")
+    
+    # Find dropped albums
+    dropped_albums = []
+    for key, album_info in albums_2020.items():
+        if key not in albums_2023:
+            dropped_albums.append(album_info)
+    
+    # Sort by original 2020 rank
+    dropped_albums.sort(key=lambda x: int(x['rank']))
+    
+    print(f"\n❌ Found {len(dropped_albums)} albums dropped from 2020 to 2023:")
+    print("=" * 80)
+    
+    for album in dropped_albums:
+        print(f"#{album['rank']:3s} - {album['artist']} - {album['album']}")
+    
+    print("=" * 80)
+    print(f"\n📊 Summary:")
+    print(f"   - New albums in 2023: {new_count}")
+    print(f"   - Dropped albums: {len(dropped_albums)}")
+    print(f"   - Match: {'✅ Yes' if new_count == len(dropped_albums) else '❌ No'}")
+    
+    # Save dropped albums list
+    with open('truly_dropped_albums.csv', 'w', newline='', encoding='utf-8') as file:
+        fieldnames = ['Original_Rank_2020', 'Artist', 'Album']
+        writer = csv.DictWriter(file, fieldnames=fieldnames)
+        writer.writeheader()
+        for album in dropped_albums:
+            writer.writerow({
+                'Original_Rank_2020': album['rank'],
+                'Artist': album['artist'],
+                'Album': album['album']
+            })
+    
+    print(f"\n💾 Saved complete list to: truly_dropped_albums.csv")
+
+if __name__ == "__main__":
+    main()