parent
2c1551588f
commit
565aaa4615
@ -1,132 +0,0 @@
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#sae2.04
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import pandas as pd
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import getpass
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import matplotlib.pyplot as plt
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from sqlalchemy import create_engine, exc, text
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df = pd.read_csv('spotify_songs.csv', sep=',', encoding="latin-1")
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print(df)
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print(df.columns)
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'''
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renvoie ['track_id', 'track_name', 'track_artist', 'track_popularity',
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'track_album_id', 'track_album_name', 'track_album_release_date',
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'playlist_name', 'playlist_id', 'playlist_genre', 'playlist_subgenre',
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'danceability', 'energy', 'key', 'loudness', 'mode', 'speechiness',
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'acousticness', 'instrumentalness', 'liveness', 'valence', 'tempo',
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'duration_ms']
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'''
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df = df.drop(columns=['key','mode','instrumentalness'])
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# Ces colonnes sont inutiles ici
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# Au besoin, on peut drop
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df = df.dropna()
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print(df['duration_ms'])
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# df['duration_ms'] = df['duration_ms']/1000 #ms en s
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# df['duration_ms'] = df['duration_ms']/60 #s en m
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df['duration_ms'] = pd.to_timedelta(df['duration_ms'], unit='ms')
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df = df.rename(columns={"duration_ms": "duration_m"})
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print(df['duration_m'])
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df = df.drop(151)
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dfT = df[['track_id', 'track_name', 'track_popularity', 'duration_m', 'danceability', 'energy', 'loudness','speechiness', 'acousticness', 'liveness', 'valence', 'tempo', 'track_artist', 'track_album_id','playlist_id']]
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dfA = df[['track_album_id', 'track_album_name', 'track_album_release_date', 'track_artist']]
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dfP = df[['playlist_id', 'playlist_name', 'playlist_genre', 'playlist_subgenre']]
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dfArtist = df[['track_artist']]
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dfArtist = dfArtist.drop_duplicates()
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dfA = dfA.drop_duplicates()
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dfA['track_album_id'] = dfA['track_album_id'].drop_duplicates()
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dfA = dfA.dropna()
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dfP = dfP.drop_duplicates()
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dfP['playlist_id'] = dfP['playlist_id'].drop_duplicates()
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dfP = dfP.dropna()
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dfT = dfT.drop_duplicates()
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dfT['track_id'] = dfT['track_id'].drop_duplicates()
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dfT = dfT.dropna()
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co = None
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engine = create_engine("postgresql://reneveu:achanger@londres/dbreneveu")
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try :
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co = engine.connect()
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co.execute(text('''DROP TABLE IF EXISTS Artist CASCADE;'''))
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co.execute(text('''CREATE TABLE Artist(
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track_artist varchar(150),
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PRIMARY KEY (track_artist)
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);'''))
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co.execute(text('''DROP TABLE IF EXISTS Album CASCADE;'''))
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co.execute(text('''CREATE TABLE Album(
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track_album_id varchar(150),
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track_album_name varchar(500),
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track_album_release_date varchar(15),
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track_artist varchar(150) REFERENCES Artist,
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PRIMARY KEY (track_album_id)
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);'''))
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co.execute(text('''DROP TABLE IF EXISTS Playlist CASCADE;'''))
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co.execute(text('''CREATE TABLE Playlist(
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playlist_id varchar(150) PRIMARY KEY,
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playlist_name varchar(150),
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playlist_genre varchar(50),
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playlist_subgenre varchar(150)
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);'''))
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co.execute(text('''DROP TABLE IF EXISTS Track CASCADE;'''))
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co.execute(text('''CREATE TABLE Track(
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track_id varchar(150),
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track_name varchar(150),
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track_popularity numeric,
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duration_m time,
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danceability numeric,
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energy numeric,
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loudness numeric,
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speechiness numeric,
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acousticness numeric,
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liveness numeric,
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valence numeric,
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tempo numeric,
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track_artist varchar(150) REFERENCES Artist,
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track_album_id varchar(150) REFERENCES Album,
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playlist_id varchar(150) REFERENCES Playlist,
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PRIMARY KEY (track_id)
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);'''))
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for row in dfArtist.itertuples():
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co.execute(text('''INSERT INTO Artist VALUES(:1);'''),
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{'1': row.track_artist})
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co.execute(text('''SELECT * FROM Artist;'''))
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co.commit()
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for row in dfA.itertuples():
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co.execute(text('''INSERT INTO Album VALUES(:1, :2, :3, :4);'''),
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{'1': row.track_album_id, '2': row.track_album_name, '3': row.track_album_release_date, '4': row.track_artist})
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co.execute(text('''SELECT * FROM Album;'''))
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co.commit()
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for row in dfP.itertuples():
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co.execute(text('''INSERT INTO Playlist VALUES(:1, :2, :3, :4);'''),
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{'1': row.playlist_id, '2': row.playlist_name, '3': row.playlist_genre, '4': row.playlist_subgenre})
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co.execute(text('''SELECT * FROM Playlist;'''))
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co.commit()
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for row in dfT.itertuples():
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co.execute(text('''INSERT INTO Track VALUES(:1, :2, :3, :4, :5, :6, :7, :8, :9, :10, :11, :12, :13, :14, :15);'''),
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{'1': row.track_id, '2': row.track_name, '3': row.track_popularity, '4': row.duration_m, '5': row.danceability, '6': row.energy, '7': row.loudness,
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'8': row.speechiness, '9': row.acousticness, '10': row.liveness, '11': row.valence, '12': row.tempo, '13': row.track_artist, '14': row.track_album_id,
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'15': row.playlist_id})
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co.execute(text('''SELECT * FROM Track;'''))
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co.commit()
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except exc.SQLAlchemyError as e:
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print(e)
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finally :
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if co is not None:
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co.close()
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df['playlist_genre'].value_counts().plot.pie(ylabel='', autopct='%1.1f%%')
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plt.show()
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