def split_measures_table(measures_table, frac=0.7, loud=False):
	"""
	Splits a measures table into two randomly selected groups. This is useful for machine learning methods where a train-test split is needed, and uses the Pandas library's sample method.

	
	Args:
		measures_table(Dataframe): A measures table.
		frac(Float): The fraction, represented as a decimal number, to split the measures table by, e.g. 0.7 would result in a 70-30 split.
		loud(Boolean): Whether or not to print out the size of the two resulting groups.

	"""
	measures_table.drop(['player_id'], axis=1)
	train_table = measures_table.sample(frac=frac) 
	test_table = measures_table.drop(train_table.index)

	if loud:
		print('train:test\n', len(train_table),':',len(test_table), 'ready')
	
	return train_table, test_table