def thin_data(data, variable_to_consider, percentage_cutoff=10, verbose=True):
	"""
	Takes in a dataframe and removes rows where the contribution of categorical variables in a specified column make up 
	less than a defined percentage of the total 

	data=pandas dataframe
	variable_to_consider=name of column
	percentage_cutoff=where entries in the variable_to_consider column make up less than this percentage, they will be dropped

	RETURNS dataframe 
	"""

	if verbose:
		print("*****")
		print("Trimming dataframe")
		print("Column: %s " %variable_to_consider)
		print("Dropping rows where %s variables make up less than %i %% of the total column composition." %(variable_to_consider,percentage_cutoff))
		print(" ")
		print("%s : %% of total" %variable_to_consider)
		print("----------------")
		print((data[variable_to_consider].value_counts()/data[variable_to_consider].count())*100)
	
	class_percents=(data[variable_to_consider].value_counts()/data[variable_to_consider].count())*100
	class_percents_lessThan_CUTOFF=class_percents[class_percents<percentage_cutoff]
	class_percents_greaterThan_CUTOFF=class_percents.drop(class_percents_lessThan_CUTOFF.index)

	# drop rows where CLASS is > specified percentage 
	#help: https://stackoverflow.com/questions/12065885/filter-dataframe-rows-if-value-in-column-is-in-a-set-list-of-values
	
	mask_gtCUTOFF=data[variable_to_consider].isin(list(class_percents_greaterThan_CUTOFF.index))
	data_trimmed=data[mask_gtCUTOFF]

	return(data_trimmed)