python - Creating a line graph with ggplot library which plots two lines (the high and low of stock prices) on the same graph -

i can plot closing prices using below syntax:

gg = ggplot(stock_prices.ix['2013-01-01': '2013-12-31'], aes('date', 'close')) + geom_line()  

however, don't know how plot "high" , "low" prices on same plot, ideas?

the standard practice of plotting "high" , "lows" (together "open" , "close) in finance candlestick plotting. following code should started in charting candlesticks:

step 1. imports.

import datetime dt import matplotlib.pyplot plt import matplotlib.dates mdates matplotlib.finance import candlestick_ohlc import pandas pd pandas_datareader import data 

step 2. downloads.

start = dt.datetime(2015,1,1) spy = data.datareader('^gspc', 'yahoo', start) 

you can skip step if have data in ohlc format.

step 3. prepare data.

at point have data in form:

spy.head()                    open       high         low        close    volume   adj close date                         2015-01-02  2058.899902 2072.360107 2046.040039 2058.199951 2708700000  2058.199951 2015-01-05  2054.439941 2054.439941 2017.339966 2020.579956 3799120000  2020.579956 2015-01-06  2022.150024 2030.250000 1992.439941 2002.609985 4460110000  2002.609985 2015-01-07  2005.550049 2029.609985 2005.550049 2025.900024 3805480000  2025.900024 2015-01-08  2030.609985 2064.080078 2030.609985 2062.139893 3934010000  2062.139893 

to move further, need have index in separate column number of dates, rather timestamp, achieved by:

spy['date2'] = spy.index.map(lambda x: mdates.date2num(x)) 

step 4. candlestick plotting.

now have data in place can plot:

fig, ax = plt.subplots() ax.xaxis_date() ax.xaxis.set_major_formatter(mdates.dateformatter("%y-%m-%d")) plt.xlabel("date") plt.ylabel("price") plt.title("sp500") candlestick_ohlc(ax, spy[['date2', 'open', 'high', 'low','close']].values, width=.6, colorup='g', alpha =.4); 

edit

should still wish have 2 separate lines high , low following line of code that:

spy[['high','low']].plot();