def min_max(PE_data):
	"""
	Will normalize all the data to within the interval 0 to 1. The input 
	should be a Dataframe with the trials as columns and a timeline as index.
	If a different interval is required, simply multiply the data by the width 
	of that interval and add the floor.
	
	Examples:

		>>> PE_norm = min_max_norm(PE_data)

		>>> # If the interval should be -1 to 1
		>>> PE_norm = (PE_norm * 2) - 1

	"""

	new_data = PE_data.copy()
	new_data = new_data - new_data.min(axis=0)
	new_data = new_data/new_data.max(axis=0)
	new_data.signal_type = 'Signal (Normalized)'

	return new_data