import pandas as pd
import numpy as np
%matplotlib inline

data = pd.read_csv('data/normalized/metadata.csv')

# data count

len(data.index)

1196

# top 20 composers
data.groupby(by='composer')['composer'].count().sort_values(ascending=False)[:20]

composer
bach           223
chopin         116
mozart         114
beethoven       96
traditional     57
schumann        52
schubert        38
haydn           37
diabelli        36
joplin          25
grieg           22
handel          21
clementi        21
liszt           20
czerny          19
tchaikovsky     19
burgmuller      19
verdi           19
debussy         17
scriabin        17
Name: composer, dtype: int64

# original musical keys
data.groupby(by='key')['key'].count()

key
A major      50
A- major     37
B major      17
B- major     69
C major     116
C# major     35
D major      78
E major      35
E- major     52
F major      87
F# major     24
G major      98
a minor      75
b minor      25
b- minor     16
c minor      52
c# minor     33
d minor      73
e minor      44
e- minor     16
f minor      33
f# minor     18
g minor      60
g# minor     15
Name: key, dtype: int64

data['year'].hist(bins=30, )

<matplotlib.axes._subplots.AxesSubplot at 0x7f127c165358>

data.groupby(by='period')['period'].count()

period
baroque        249
classicism     253
folk            58
jazz            26
modern          54
romanticism    412
Name: period, dtype: int64

data.groupby(by='musical_form')['musical_form'].count()

musical_form
ballad         5
canon          5
etude         50
fantasia      16
fugue         57
march         13
mazurka       25
nocturne       7
polonaise      5
prelude      139
rag           17
rhapsod        6
rondo          6
sonata       243
sonatina      20
song          27
suite         27
technique     20
valse          5
Name: musical_form, dtype: int64