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51c5bd8d7d
* Created a testing suite for the spotipy client.Spotify class * Delete pyvenv.cfg * Corrected error in description * Added some advanced usage examples, some of which involve utilizing basic data analysis methods using other libraries such as Pandas * Minor formatting fixes --------- Co-authored-by: Stéphane Bruckert <stephane.bruckert@gmail.com>
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import spotipy
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from spotipy.oauth2 import SpotifyClientCredentials
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# Import the extra necessary libraries for this example
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# These libraries are not included in the default packages
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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# Set up Spotify credentials
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client_credentials_manager = SpotifyClientCredentials()
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sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)
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# Fetch audio features of tracks from any playlist
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playlist_id = '37i9dQZEVXbMDoHDwVN2tF'
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results = sp.playlist_tracks(playlist_id)
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tracks = results['items']
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track_ids = [track['track']['id'] for track in tracks]
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audio_features = sp.audio_features(track_ids)
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# Create a DataFrame of audio features
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df = pd.DataFrame(audio_features)
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df = df[['danceability', 'energy', 'speechiness', 'acousticness',
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'instrumentalness', 'liveness', 'valence', 'tempo']]
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# Generate a correlation matrix
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correlation_matrix = df.corr()
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# Plot the correlation matrix using seaborn
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sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')
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# Show the plot
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plt.show()
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