Some code playing with the Echonest API python wrapper

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Resources for the Spotify web API:
Python wrapper
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In [69]:

    
from pyechonest import config, artist, song
import pandas as pd
config.ECHO_NEST_API_KEY = 'XXXXXXXX' #retrieved from https://developer.echonest.com/account/profile
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

Query a single song, get its audio features and make a dataframe



In [4]:

    
songs = song.search(title='Elastic Heart',artist='Sia',buckets='id:spotify',limit=True,results=1)
elasticHeart = songs[0]



In [5]:

    
elasticHeartFeatures = pd.DataFrame.from_dict(elasticHeart.audio_summary,orient='index')



In [10]:

    
pd.DataFrame.from_dict([elasticHeart.audio_summary])









    Out[10]:






  
    
      
      acousticness
      analysis_url
      audio_md5
      danceability
      duration
      energy
      instrumentalness
      key
      liveness
      loudness
      mode
      speechiness
      tempo
      time_signature
      valence
    
  
  
    
      0
      0.021916
      http://echonest-analysis.s3.amazonaws.com/TR/j...
      
      0.670395
      224.45333
      0.743102
      0.000014
      9
      0.180429
      -6.031
      1
      0.03682
      130.044
      4
      0.512652

Grab and compare the hottest tracks, available in Spotify, for 2 artists on a number of audio features



In [50]:

    
floHottest = song.search(artist = 'Flo Rida' ,sort = 'song_hotttnesss-desc', buckets = 'id:spotify', limit = True, results = 20)
fsongFeatures = []
for song in floHottest:
    fsongFeatures.append(song.audio_summary)



In [53]:

    
S= pd.DataFrame.from_dict(songFeatures)
S.index = [song.title for song in siaHottest]
S['hotness'] = [song.song_hotttnesss for song in siaHottest]



In [64]:

    
F= pd.DataFrame.from_dict(fsongFeatures)
F.index = [song.title for song in floHottest]
F['hotness'] = [song.song_hotttnesss for song in floHottest]



In [65]:

    
u,idx = np.unique(S.index,return_index=True)
S = S.ix[idx,:]
u,idx = np.unique(F.index,return_index=True)
F = F.ix[idx,:]



In [133]:

    
ax = pd.DataFrame({'Flo Rida':F.mean(), 'Sia': S.mean()}).plot(kind='bar',figsize=(18,6),rot=0, color = ['lightblue','salmon']);
ax.set_title("Average Song Features for Artist's Hottest 20 tracks",fontsize=14);
ax.tick_params(axis='x', labelsize=12)



In [145]:

    
Elastic_Heart = siaHottest[5].get_tracks('spotify')



In [152]:

    
Elastic_Heart[1]









    Out[152]:





{u'catalog': u'spotify',
 u'foreign_id': u'spotify:track:3yFdQkEQNzDwpPB1iIFtaM',
 u'foreign_release_id': u'spotify:album:2uLFriAEtIBfZvjTb1nru3',
 u'id': u'TRVJDIL14EA1351E7F'}



In [157]:

    
%%html
<iframe src="https://embed.spotify.com/?uri=spotify:track:3yFdQkEQNzDwpPB1iIFtaM" width="300" height="380" frameborder="0" allowtransparency="true"></iframe>



In [ ]: