data_processing_VIAB.py
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	#data_processing_VIAB.py
	# data processing for VIABILITY dataset
	import numpy as np
	import pandas as pd
	from scipy import stats


	def extract_features_VIAB(docs):
	# Initialize a list to hold the processed feature dictionaries
	processed_docs = []

	# Iterate over each document in the list
	for data in docs:
	features = {}

	# Extract features from the 'classification' list in each document
	for state in data.get('classification', []):
	state_type = state['type']
	features[f'mean_{state_type}'] = state['mu']
	features[f'std_{state_type}'] = state['std']
	features[f'q25_{state_type}'] = state['q25']
	features[f'q75_{state_type}'] = state['q75']
	features[f'median_{state_type}'] = state['median']
	features[f'skew_{state_type}'] = state['skew']
	features[f'max_{state_type}'] = state['max']
	features[f'min_{state_type}'] = state['min']

	# Handle 'death' target variable
	features['dead'] = 1 if 'dead' in data else 0

	# Append the processed features to the list
	processed_docs.append(features)

	return pd.DataFrame(processed_docs)