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construct-final-dataset.py
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construct-final-dataset.py
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import pandas as pd
from preprocessing import removesquarebr, processgenres, fix_wrong_unicode, tokenize, lemmatize, remove_repetitions
darklyrics = pd.read_csv('darklyrics-lang.csv')
if __name__ == '__main__':
# Rimuovo le canzoni senza liriche
darklyrics = darklyrics.dropna()
# Rimuovo le annotazioni nelle quadre
darklyrics['lyrics'] = darklyrics.apply(lambda x: removesquarebr(x['lyrics']), axis=1)
# Rimuovo possibili strumentali
darklyrics = darklyrics[darklyrics['lyrics'] != '']
# print(darklyrics['lang'].value_counts())
# Rimuovo le canzoni non in inglese
darklyrics = darklyrics[darklyrics['lang'] == 'en']
darklyrics = darklyrics.drop('lang', axis=1)
# Parso i generi, vedere funzione
darklyrics['genre'] = darklyrics.apply(lambda x: processgenres(x['genre']), axis=1)
# Rimuovo le canzoni con genere mancante
darklyrics = darklyrics[darklyrics.apply(lambda x: 'MISSING' not in x['genre'], axis=1)]
# generi = [lista for lista in darklyrics['genre'] if len(lista)>1]
# Trasformo da multi-label a singola label, da valutare
# darklyrics['genre'] = darklyrics.apply(lambda x: singularizegenre(x['genre']), axis=1)
# Magia
print("fix unicode")
darklyrics['lyrics'] = darklyrics.apply(lambda x: fix_wrong_unicode(x['lyrics']), axis=1)
# Pulizia dei token
print("tokenize")
darklyrics['tokens'] = darklyrics.apply(lambda x: tokenize(x['lyrics']), axis=1)
print("remove repetitions")
# Rimuove i token con lettere multiple tipo aaaarggghhh -> argh
darklyrics['tokens'] = darklyrics.apply(lambda x: remove_repetitions(x['tokens']), axis=1)
print("lemmatize")
darklyrics['tokens'] = darklyrics.apply(lambda x: lemmatize(x['tokens']), axis=1)
darklyrics = darklyrics.drop('lyrics', axis=1)
darklyrics.to_csv('darklyrics-tokens.csv', index=False)