def add_trendline(self,date0,date1,on='close',text=None,**kwargs):
		"""
		Adds a trendline to the QuantFigure. 
		Given 2 dates, the trendline is connected on the data points
		that correspond to those dates. 

		Parameters:
			date0 : string
				Trendline starting date
			date1 :  string
				Trendline end date
			on : string
				Indicate the data series in which the 
				trendline should be based.
					'close'
					'high'
					'low'
					'open'
			text : string
				If passed, then an annotation will be added 
				to the trendline (at mid point)

		kwargs:
			from_strfmt : string
				Defines the date formating in which 
				date0 and date1 are stated. 
				default: '%d%b%y'					
			to_strfmt : string
				Defines the date formatting 
				to which it should be converted. 
				This should match the same format as the timeseries index. 
				default : '%Y-%m-%d'		
		"""
		d={'kind':'trend','date0':date0,'date1':date1,'on':on,'text':text}
		d.update(**kwargs)
		self.trendlines.append(d)
def add_trendline ( self , date0 , date1 , on = 'close' , text = None , ** kwargs ) : d = { 'kind' : 'trend' , 'date0' : date0 , 'date1' : date1 , 'on' : on , 'text' : text } d . update ( ** kwargs ) self . trendlines . append ( d )
Adds a trendline to the QuantFigure. 
		Given 2 dates, the trendline is connected on the data points
		that correspond to those dates. 

		Parameters:
			date0 : string
				Trendline starting date
			date1 :  string
				Trendline end date
			on : string
				Indicate the data series in which the 
				trendline should be based.
					'close'
					'high'
					'low'
					'open'
			text : string
				If passed, then an annotation will be added 
				to the trendline (at mid point)

		kwargs:
			from_strfmt : string
				Defines the date formating in which 
				date0 and date1 are stated. 
				default: '%d%b%y'					
			to_strfmt : string
				Defines the date formatting 
				to which it should be converted. 
				This should match the same format as the timeseries index. 
				default : '%Y-%m-%d'