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>
69 lines
No EOL
2.4 KiB
Python
69 lines
No EOL
2.4 KiB
Python
#!/usr/bin/env python3
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"""
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Remove duplicate dropped albums that have slightly different names.
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"""
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import csv
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def normalize_for_comparison(text):
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"""Normalize album names for duplicate detection"""
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text = text.lower().strip()
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# Remove "The" from album names in parentheses
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text = text.replace('(the black album)', '(black album)')
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text = text.replace('(the blue album)', '(blue album)')
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return text
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def main():
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# Read current CSV
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albums = []
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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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albums.append(row)
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print(f"📊 Total albums before cleanup: {len(albums)}")
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# Find duplicates among dropped albums
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seen_dropped = {}
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duplicates = []
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for i, album in enumerate(albums):
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if 'Dropped' in album['Status']:
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key = (normalize_for_comparison(album['Artist']),
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normalize_for_comparison(album['Album']))
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if key in seen_dropped:
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print(f"❌ Duplicate found:")
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print(f" First: Rank {seen_dropped[key]['Rank']} - {seen_dropped[key]['Artist']} - {seen_dropped[key]['Album']}")
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print(f" Second: Rank {album['Rank']} - {album['Artist']} - {album['Album']}")
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duplicates.append(i)
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else:
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seen_dropped[key] = album
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# Remove duplicates
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if duplicates:
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print(f"\n🗑️ Removing {len(duplicates)} duplicate entries...")
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# Remove in reverse order to maintain indices
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for i in reversed(duplicates):
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del albums[i]
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# Renumber albums after 500
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current_rank = 501
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for album in albums:
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if int(album['Rank']) > 500:
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album['Rank'] = str(current_rank)
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current_rank += 1
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# Write cleaned CSV
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with open('top_500_albums_2023.csv', 'w', newline='', encoding='utf-8') as file:
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fieldnames = ['Rank', 'Artist', 'Album', 'Status', 'Info', 'Description']
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writer = csv.DictWriter(file, fieldnames=fieldnames)
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writer.writeheader()
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writer.writerows(albums)
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print(f"\n✅ Cleanup complete!")
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print(f"📊 Total albums now: {len(albums)}")
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print(f"📊 Total dropped albums: {len([a for a in albums if 'Dropped' in a['Status']])}")
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if __name__ == "__main__":
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main() |