def get_historical_data(fsym, tsym, freq, info='full', e='all', 
                        try_conversion=True, aggregate=1, limit=1440, 
                        to_ts=False):
	"""Get minute-by-minute historical price and volume information for 
	the requested currency pair. Available data is limited to the last 7 days.
	
	Args:
		fsym: FROM symbol.
		tsym: TO symbol.
		freq: Frequency of the data. Can be set to 'minute', 'hour' or 'day'.
		info: Select price or volume information to return. Default of 'full'
			returns all of them. Can be set to 'high', 'low', 'open', 'close', 
			'volumefrom', and 'volumeto' or a list containing several of those
			values.
		e: Default returns average price across all exchanges. Can be set to the
		   name of a single exchange.
		try_conversion: If the crypto does not trade directly into the toSymbol 
			requested, BTC will be used for conversion. If set to false, it will 
			try to get values without using any conversion at all.
		aggregate: Aggregates the minute prices into bins of the specified size.
		limit: Number of minute prices. The limit settings depend on the freq
			selected:
				minute: default = 1440, min = 1, max = 2000
				hour: default = 168, min = 1, max 2000
				day: default = 30, min = 1, max 2000
			
			Using aggregate reduces the maximum number of points that can be 
			returned by a factor equal to the chosen bin size.
		
		# add 'toTs' parameter
		######################
		######################
		######################
		######################
		######################
		######################
	
	Returns:
		List of dictionairies containing the price and volume information for
		each requested tick.

		[{'time': ..., 'close': ..., 'high': ..., 'low': ..., 'open': ...,
		  'volumefrom': ..., 'volumeto': ...},
		  {...},
		 ...]
	"""

	# load data
	url = build_url(freq, fsym=fsym, tsym=tsym, freq=freq, e=e, 
	                try_conversion=try_conversion, aggregate=aggregate, 
	                limit=limit, to_ts=to_ts)
	data = load_data(url)
	data = data['Data']

	# convert timestamps to nice date format
	for d in data:
		d['time'] = timestamp_to_date(d['time'])

	# convert single input info to single element list
	if not isinstance(info, list):
		info = [info]

	# select information to return
	if info[0] == 'full':
		return data
	else:
		for d in data:
			for k, v in list(d.items()):
				if k not in info and k != 'time':
					del d[k]
				
		return data