def init_table(ticker, table, timespan): print "--" funcname = sys._getframe().f_code.co_name print ",".join(["--", funcname, ticker, table.name, timespan]) # timespan = '1y' #'6m' #'1d', '1y' if table.name != "daily": columns, data = quotes.get_quote_intraday(ticker, timespan) table.fill(data) else: # data = quotes.get_quote_daily_matplotlib(ticker) data = quotes.get_quote_daily_pandas(ticker) # # data from matplotlib: a numpy record array with fields: date, open, high, low, close, volume, adj_close # schema = 'Timestamp FLOAT PRIMARY KEY,close FLOAT,high FLOAT,low FLOAT,open FLOAT,volume FLOAT' # DCHLOV = zip(mdates.date2num(data.date), # data.close, data.high, data.low, data.open, data.volume) # print DCHLOV[:5] # data from pandas: index:pandas.DatetimeIndex, # columns: "Open", "High", "Low", "Close", "Volume", "Adj Close" # convert from pandas.DatetimeIndex to numpy.datetime64, to datetime # http://stackoverflow.com/questions/13703720/converting-between-datetime-timestamp-and-datetime64 DCHLOV = zip( mdates.date2num(data.index.to_pydatetime()), data.Close, data.High, data.Low, data.Open, data.Volume ) table.fill(DCHLOV) print "first and last timestamp of table:" print table.get_first_ts() print table.get_last_ts()
def init_table(ticker, table, timespan): print '--' funcname = sys._getframe().f_code.co_name print ','.join(['--', funcname, ticker, table.name, timespan]) #timespan = '1y' #'6m' #'1d', '1y' if table.name != 'daily': columns, data = quotes.get_quote_intraday(ticker, timespan) table.fill(data) else: #data = quotes.get_quote_daily_matplotlib(ticker) data = quotes.get_quote_daily_pandas(ticker) # # data from matplotlib: a numpy record array with fields: date, open, high, low, close, volume, adj_close # schema = 'Timestamp FLOAT PRIMARY KEY,close FLOAT,high FLOAT,low FLOAT,open FLOAT,volume FLOAT' #DCHLOV = zip(mdates.date2num(data.date), # data.close, data.high, data.low, data.open, data.volume) #print DCHLOV[:5] # data from pandas: index:pandas.DatetimeIndex, # columns: "Open", "High", "Low", "Close", "Volume", "Adj Close" # convert from pandas.DatetimeIndex to numpy.datetime64, to datetime # http://stackoverflow.com/questions/13703720/converting-between-datetime-timestamp-and-datetime64 DCHLOV = zip(mdates.date2num(data.index.to_pydatetime()), data.Close, data.High, data.Low, data.Open, data.Volume) table.fill(DCHLOV) print 'first and last timestamp of table:' print table.get_first_ts() print table.get_last_ts()
def init_data(self): print '--' print 'graph.init_data()' self.alldata = quotes.get_quote_daily_pandas(self.info['symbol'], self.info['timerange']) #for local testing #self.alldata = quotes.get_quote_csv(self.info['symbol'], self.info['timerange']) stock_graph.pre_compute_indicators(self.alldata)