c3a24799c8
- 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>
79 lines
No EOL
2.7 KiB
Python
79 lines
No EOL
2.7 KiB
Python
#!/usr/bin/env python3
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"""
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Find ALL albums that were dropped from 2020 to 2023 by comparing the lists.
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"""
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import csv
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def normalize_text(text):
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"""Normalize text for comparison"""
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return text.lower().strip().replace('&', 'and').replace(' ', ' ')
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def main():
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# Read 2020 albums (simplified)
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albums_2020 = {}
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with open('rolling_stone_2020_simple.csv', 'r', encoding='utf-8') as file:
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reader = csv.DictReader(file)
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for row in reader:
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key = (normalize_text(row['Artist']), normalize_text(row['Album']))
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albums_2020[key] = {
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'rank': row['Rank'],
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'artist': row['Artist'],
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'album': row['Album']
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}
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print(f"📊 Loaded {len(albums_2020)} albums from 2020 list")
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# Read 2023 albums (only first 500)
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albums_2023 = set()
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new_count = 0
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with open('top_500_albums_2023.csv', 'r', encoding='utf-8') as file:
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reader = csv.DictReader(file)
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for row in reader:
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rank = int(row['Rank'])
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if rank <= 500:
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key = (normalize_text(row['Artist']), normalize_text(row['Album']))
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albums_2023.add(key)
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if row['Status'] == 'New in 2023':
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new_count += 1
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print(f"📊 Loaded {len(albums_2023)} albums from 2023 list")
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print(f"🆕 Found {new_count} albums marked as 'New in 2023'")
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# Find dropped albums
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dropped_albums = []
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for key, album_info in albums_2020.items():
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if key not in albums_2023:
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dropped_albums.append(album_info)
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# Sort by original 2020 rank
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dropped_albums.sort(key=lambda x: int(x['rank']))
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print(f"\n❌ Found {len(dropped_albums)} albums dropped from 2020 to 2023:")
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print("=" * 80)
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for album in dropped_albums:
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print(f"#{album['rank']:3s} - {album['artist']} - {album['album']}")
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print("=" * 80)
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print(f"\n📊 Summary:")
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print(f" - New albums in 2023: {new_count}")
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print(f" - Dropped albums: {len(dropped_albums)}")
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print(f" - Match: {'✅ Yes' if new_count == len(dropped_albums) else '❌ No'}")
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# Save dropped albums list
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with open('truly_dropped_albums.csv', 'w', newline='', encoding='utf-8') as file:
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fieldnames = ['Original_Rank_2020', 'Artist', 'Album']
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writer = csv.DictWriter(file, fieldnames=fieldnames)
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writer.writeheader()
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for album in dropped_albums:
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writer.writerow({
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'Original_Rank_2020': album['rank'],
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'Artist': album['artist'],
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'Album': album['album']
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})
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print(f"\n💾 Saved complete list to: truly_dropped_albums.csv")
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if __name__ == "__main__":
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main() |