88a6434132
- Corrected dropped albums to exactly 8 albums through detailed comparison analysis - Updated dropped albums list (ranks 501-508) with proper albums that were truly removed - Fixed "New in 2023" markings to show only 8 albums (balancing the 8 dropped) - Downloaded cover art for all 8 dropped albums - Removed incorrect cover art files for albums that weren't actually dropped - Updated data files with corrected artist/album name formatting for accurate matching 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
74 lines
No EOL
2.7 KiB
Python
74 lines
No EOL
2.7 KiB
Python
#!/usr/bin/env python3
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"""
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Compare rolling_stone_top_500_albums_2020.csv and wikipedia_top_500_albums.csv to find dropped albums.
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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 Rolling Stone albums
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albums_2020 = {}
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with open('rolling_stone_2020_simplified.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 Rolling Stone list")
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# Read Wikipedia 2023 albums (note: columns are rank,album,artist)
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albums_2023_wiki = set()
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with open('wikipedia_top_500_albums.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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# Wikipedia format: rank,album,artist
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key = (normalize_text(row['artist']), normalize_text(row['album']))
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albums_2023_wiki.add(key)
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print(f"📊 Loaded {len(albums_2023_wiki)} albums from Wikipedia 2023 list")
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# Find dropped albums (in 2020 but not in Wikipedia 2023)
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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_wiki:
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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" - Albums in 2020: {len(albums_2020)}")
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print(f" - Albums in Wikipedia 2023: {len(albums_2023_wiki)}")
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print(f" - Albums dropped: {len(dropped_albums)}")
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# Save dropped albums list
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with open('dropped_albums_2020_vs_2023.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 dropped albums list to: dropped_albums_2020_vs_2023.csv")
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if __name__ == "__main__":
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main() |