I'm working on a chord dictionary and for that I need to group the different types of chords into smaller groups.

However, I'm having trouble working with some variations that contain characters like # (e.g. C#, C#m) and variations like D7/F# and A/B, which I would like to insert into others.

I believe it's some regex parameter, which I confess I'm not so familiar with.

Here is the developed code:

triadeMaior = pd.DataFrame({'triadeMaior': ['C','C#','Db','D','D#','Eb','E','F','F#','Gb','G','G#','Ab','A','A#','Bb','B']
})

triadeMenor = pd.DataFrame({'triadeMenor': ['Cm','C#m','Dbm','Dm','D#m','Ebm','Em','Fm','F#m','Gbm','Gm','G#m','Abm','Am','A#m','Bbm','Bm']
})

triadeDiminuta = pd.DataFrame({'triadeDiminuta':['Cdim','C#dim','Dbdim', 'Ddim', 'D#dim', 'Ebdim', 'Edim', 'Fdim', 'F#dim', 'Gbdim','Gdim', 
'G#dim', 'Abdim', 'Adim', 'A#dim', 'Bbdim', 'Bdim']
})

triadeAumentada = pd.DataFrame({'triadeAumentada':['Caug','C#aug','Dbaug','Daug','D#aug','Ebaug','Eaug','Faug','F#aug','Gbaug','Gaug','G#aug','Abaug','Aaug','A#aug','Bbaug','Baug' ]
})

setima = pd.DataFrame({'setima':['C7','C#7','Db7','D7','D#7','Eb7','E7','F7','F#7','Gb7','G7','G#7','Ab7','A7','A#7','Bb7','B7']
})

setimaMenor = pd.DataFrame({'setimaMenor':['Cm7','C#m7','Dbm7','Dm7','D#m7','Ebm7','Em7','Fm7','F#m7','Gbm7','Gm7','G#m7','Abm7','Am7','A#m7','Bbm7','Bm7']
})

setimaMaior = pd.DataFrame({'setimaMaior':['Cmaj7', 'C#maj7', 'Dbmaj7', 'Dmaj7', 'D#maj7', 'Ebmaj7', 'Emaj7', 'Fmaj7', 'F#maj7','Gbmaj7','Gmaj7', 'G#maj7','Abmaj7','Amaj7','A#maj7','Bbmaj7','Bmaj7']
})

setimaMenorQuinta = ({'setimaMenorQuinta':['Cm7b5','C#m7b5', 'Dbm7b5', 'Dm7b5', 'D#m7b5', 'Ebm7b5','Em7b5', 'Fm7b5', 'F#m7b5', 'Gbm7b5', 'Gm7b5', 'G#m7b5', 'Abm7b5', 'Am7b5', 'A#m7b5', 'Bbm7b5', 'Bm7b5']
})

sexta= pd.DataFrame({'sexta':['C6','C#6','Db6','D6','D#6','Eb6','E6','F6','F#6','Gb6','G6','G#6','Ab6','A6','A#6','Bb6','B6']
})

sextaMenor = pd.DataFrame({'sextaMenor': ['Cm6','C#m6','Dbm6','Dm6','D#m6','Ebm6','Em6','Fm6','F#m6','Gbm6','Gm6','G#m6','Abm6','Am6','A#m6' 
'Bbm6','Bm6']
})

triadeMaior_pat = fr"\b({'|'.join(triadeMaior['triadeMaior'])})\b"
triadeMenor_pat = fr"\b({'|'.join(triadeMenor['triadeMenor'])})\b"
triadeDiminuta_pat = fr"\b({'|'.join(triadeDiminuta['triadeDiminuta'])})\b"
triadeAumentada_pat = fr"\b({'|'.join(triadeAumentada['triadeAumentada'])})\b"
setima_pat = fr"\b({'|'.join(setima['setima'])})\b"
setimaMenor_pat = fr"\b({'|'.join(setimaMenor['setimaMenor'])})\b"
setimaMaior_pat = fr"\b({'|'.join(setimaMaior['setimaMaior'])})\b"
setimaMenorQuinta_pat = fr"\b({'|'.join(setimaMenorQuinta['setimaMenorQuinta'])})\b"
sexta_pat = fr"\b({'|'.join(sexta['sexta'])})\b"
sextaMenor_pat = fr"\b({'|'.join(sextaMenor['sextaMenor'])})\b"

df['chordType'] = df['chords'].replace({triadeMaior_pat: 'triadeMaj',
                                   triadeMenor_pat: 'triadeMen',
                                   triadeDiminuta_pat: 'triadeDim',
                                   triadeAumentada_pat: 'triadeAug',
                                   setima_pat: 'setima',
                                   setimaMenor_pat: 'setimaMen', 
                                   setimaMaior_pat: 'setimaMaj',
                                   setimaMenorQuinta_pat : 'setimaMenQui',
                                   sexta_pat:'sexta',
                                   sextaMenor_pat: 'sextaMen',                               
                                   r'\b(?!triadeMaj|triadeMen|triadeDim|triadeAug|setima|setimaMen|setimaMen|setimaMaj|sexta|sextaMen\b)\w ': 'outros'}, 
                                  regex=True)

Here is an example of some results:

As you can see, in the case of chords with # and /, the current code understands it as two parts and not one.

Does anyone know how to fix? Also, as I mentioned, I don't have a lot of regex skills, so I don't know if it would be possible to shorten and make the code more robust and clean.

CodePudding user response：

This might be more cleanly done without regex, actually.

This example just uses a small subset of your data, but you can just fill out the chord_types dict with all your mappings.

import pandas as pd

chord_types = {'C': 'triadeMaj', 'C#': 'triadeMaj', 'C7': 'setima'} # Add as required
df = pd.DataFrame(['C, C7', 'C, C#'], columns=('chords',)) # Toy example

map_fn = lambda cs: ', '.join((chord_types.get(c, 'outros') for c in cs))
df['chordType'] = df['chords'].str.replace(' ', '').str.split(',').apply(map_fn)

print(df)

giving:

  chords             chordType
0  C, C7     triadeMaj, setima
1  C, C#  triadeMaj, triadeMaj