added model training
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@ -29,8 +29,8 @@ def check_datasets_presence():
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raise FileNotFoundError(dataset_2 + " not found")
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def datasets_preparation():
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df_1 = pd.read_csv("datasets/spotify_songs.csv")
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df_2 = pd.read_csv("datasets/Spotify_Dataset.csv", sep=";")
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df_1 = pd.read_csv("artifacts/spotify_songs.csv")
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df_2 = pd.read_csv("artifacts/Spotify_Dataset.csv", sep=";")
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df_1 = df_1.dropna()
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df_2 = df_2.dropna()
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@ -60,8 +60,8 @@ def datasets_preparation():
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#df_1 = df_1.iloc[20:]
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if "docker_test_dataset.csv" not in os.listdir("datasets"):
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diff_df.to_csv("datasets/docker_test_dataset.csv", index=False)
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if "docker_test_dataset.csv" not in os.listdir("artifacts"):
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diff_df.to_csv("artifacts/docker_test_dataset.csv", index=False)
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result_df = pd.merge(df_1, df_2, on='track_name', how='inner')
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result_df = result_df.drop_duplicates(subset=['track_name'])
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