Prepare tracks for model endpoint

Build the ModelPrep class.

Use the class to prepare a list of tracks and their associated features for use in model prediction.

 ModelPrep ()

A class for preparing data for a Spotify recommendation model.

 ModelPrep.load_scaler ()

Loads the scaler object from S3.

 ModelPrep.load_svd ()

Loads the SVD object from S3.

 ModelPrep.load_tracks_data ()

Loads the Spotify and Last.fm tracks data and merges them.

 ModelPrep.load_genre_series ()

Loads the genre series data from S3.

 ModelPrep.load_key_series ()

Loads the key series data from S3.

 ModelPrep.load_time_signature_series ()

Loads the time signature series data from S3.

 ModelPrep.load_s3 ()

Loads all necessary data from S3.

 ModelPrep.transform_features (constant)

Transforms the features of the prepped DataFrame.

	Type	Details
constant	float	The constant to add to ‘speechiness’, ‘acousticness’, and ‘instrumentalness’ before log-transforming.
Returns	None

 ModelPrep.update_dataframe_with_prefix (current_dataframe, series,
                                         prefix)

Updates the DataFrame with a one-hot encoded series.

	Type	Details
current_dataframe	pandas.DataFrame	The DataFrame to update.
series	pandas.Series	The series to one-hot encode.
prefix	str	The prefix to add to the column names.
Returns	pandas.DataFrame	The updated DataFrame.

 ModelPrep.prepare_final_frame ()

Prepares the final DataFrame for prediction.

 ModelPrep.save_prepared_frame ()

Saves the prepared DataFrame to S3.