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Edit and run



In [1]:

    
ls









    



dma.pickle  generate_new_sample_saved_state.py  run_algo.py*  Untitled0.ipynb



In [2]:

    
import pandas as pd
perf = pd.read_pickle('dma.pickle') # read in perf DataFrame
perf.head()









    Out[2]:






  
    
      
      capital_used
      ending_cash
      ending_value
      orders
      period_close
      period_open
      pnl
      portfolio_value
      positions
      returns
      starting_cash
      starting_value
      transactions
    
  
  
    
      2011-01-03 21:00:00
      0
      10000000
      0
      []
      2011-01-03 21:00:00+00:00
      2011-01-03 14:31:00+00:00
      0
      10000000
      []
      0
      10000000
      0
      []
    
    
      2011-01-04 21:00:00
      0
      10000000
      0
      []
      2011-01-04 21:00:00+00:00
      2011-01-04 14:31:00+00:00
      0
      10000000
      []
      0
      10000000
      0
      []
    
    
      2011-01-05 21:00:00
      0
      10000000
      0
      []
      2011-01-05 21:00:00+00:00
      2011-01-05 14:31:00+00:00
      0
      10000000
      []
      0
      10000000
      0
      []
    
    
      2011-01-06 21:00:00
      0
      10000000
      0
      []
      2011-01-06 21:00:00+00:00
      2011-01-06 14:31:00+00:00
      0
      10000000
      []
      0
      10000000
      0
      []
    
    
      2011-01-07 21:00:00
      0
      10000000
      0
      []
      2011-01-07 21:00:00+00:00
      2011-01-07 14:31:00+00:00
      0
      10000000
      []
      0
      10000000
      0
      []



In [3]:

    
%pylab inline
figsize(12, 12)
import matplotlib.pyplot as plt

ax1 = plt.subplot(211)
perf.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('portfolio value')
ax2 = plt.subplot(212, sharex=ax1)
perf.AAPL.plot(ax=ax2)
ax2.set_ylabel('AAPL stock price')









    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-3-d6151efac463> in <module>()
      7 ax1.set_ylabel('portfolio value')
      8 ax2 = plt.subplot(212, sharex=ax1)
----> 9 perf.AAPL.plot(ax=ax2)
     10 ax2.set_ylabel('AAPL stock price')

/usr/local/lib/python2.7/dist-packages/pandas/core/generic.pyc in __getattr__(self, name)
   2148                 return self[name]
   2149             raise AttributeError("'%s' object has no attribute '%s'" %
-> 2150                                  (type(self).__name__, name))
   2151 
   2152     def __setattr__(self, name, value):

AttributeError: 'DataFrame' object has no attribute 'AAPL'





    



Populating the interactive namespace from numpy and matplotlib



In [1]:

    
import pandas as pd
perf = pd.read_pickle('dma.pickle') # read in perf DataFrame
perf.head()









    Out[1]:






  
    
      
      AAPL
      capital_used
      ending_cash
      ending_value
      long_mavg
      orders
      period_close
      period_open
      pnl
      portfolio_value
      positions
      returns
      short_mavg
      starting_cash
      starting_value
      transactions
    
  
  
    
      2009-01-02 21:00:00
      NaN
      0
      10000000
      0
      NaN
      []
      2009-01-02 21:00:00+00:00
      2009-01-02 14:31:00+00:00
      0
      10000000
      []
      0
      NaN
      10000000
      0
      []
    
    
      2009-01-05 21:00:00
      NaN
      0
      10000000
      0
      NaN
      []
      2009-01-05 21:00:00+00:00
      2009-01-05 14:31:00+00:00
      0
      10000000
      []
      0
      NaN
      10000000
      0
      []
    
    
      2009-01-06 21:00:00
      NaN
      0
      10000000
      0
      NaN
      []
      2009-01-06 21:00:00+00:00
      2009-01-06 14:31:00+00:00
      0
      10000000
      []
      0
      NaN
      10000000
      0
      []
    
    
      2009-01-07 21:00:00
      NaN
      0
      10000000
      0
      NaN
      []
      2009-01-07 21:00:00+00:00
      2009-01-07 14:31:00+00:00
      0
      10000000
      []
      0
      NaN
      10000000
      0
      []
    
    
      2009-01-08 21:00:00
      NaN
      0
      10000000
      0
      NaN
      []
      2009-01-08 21:00:00+00:00
      2009-01-08 14:31:00+00:00
      0
      10000000
      []
      0
      NaN
      10000000
      0
      []



In [2]:

    
%pylab inline
figsize(12, 12)
import matplotlib.pyplot as plt

ax1 = plt.subplot(211)
perf.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('portfolio value')
ax2 = plt.subplot(212, sharex=ax1)
perf.AAPL.plot(ax=ax2)
ax2.set_ylabel('AAPL stock price')









    



Populating the interactive namespace from numpy and matplotlib






    Out[2]:





<matplotlib.text.Text at 0x7fd6c50b3310>



In [ ]:

	ending_cash	orders	period_close	period_open	portfolio_value	positions	starting_cash	transactions
2011-01-03 21:00:00	10000000	[]	2011-01-03 21:00:00+00:00	2011-01-03 14:31:00+00:00	10000000	[]	10000000	[]
2011-01-04 21:00:00	10000000	[]	2011-01-04 21:00:00+00:00	2011-01-04 14:31:00+00:00	10000000	[]	10000000	[]
2011-01-05 21:00:00	10000000	[]	2011-01-05 21:00:00+00:00	2011-01-05 14:31:00+00:00	10000000	[]	10000000	[]
2011-01-06 21:00:00	10000000	[]	2011-01-06 21:00:00+00:00	2011-01-06 14:31:00+00:00	10000000	[]	10000000	[]
2011-01-07 21:00:00	10000000	[]	2011-01-07 21:00:00+00:00	2011-01-07 14:31:00+00:00	10000000	[]	10000000	[]

	AAPL	ending_cash	long_mavg	orders	period_close	period_open	portfolio_value	positions	short_mavg	starting_cash	transactions
2009-01-02 21:00:00	NaN	10000000	NaN	[]	2009-01-02 21:00:00+00:00	2009-01-02 14:31:00+00:00	10000000	[]	NaN	10000000	[]
2009-01-05 21:00:00	NaN	10000000	NaN	[]	2009-01-05 21:00:00+00:00	2009-01-05 14:31:00+00:00	10000000	[]	NaN	10000000	[]
2009-01-06 21:00:00	NaN	10000000	NaN	[]	2009-01-06 21:00:00+00:00	2009-01-06 14:31:00+00:00	10000000	[]	NaN	10000000	[]
2009-01-07 21:00:00	NaN	10000000	NaN	[]	2009-01-07 21:00:00+00:00	2009-01-07 14:31:00+00:00	10000000	[]	NaN	10000000	[]
2009-01-08 21:00:00	NaN	10000000	NaN	[]	2009-01-08 21:00:00+00:00	2009-01-08 14:31:00+00:00	10000000	[]	NaN	10000000	[]