In [1]:

    

import pandas as pd
import numpy as np
import matplotlib.pylab as plt
from statsmodels.tsa.seasonal import seasonal_decompose
%matplotlib inline
 
plt.rcParams['figure.figsize']=(20,10)
plt.style.use('ggplot')


    

In [3]:

    

data = pd.read_csv('DEOK_hourly.csv')
data['Datetime']=pd.to_datetime(data['Datetime'])
data.set_index('Datetime', inplace=True)


    

In [4]:

    

data.head()


    

    
Out[4]:







  

    

      

      
DEOK_MW
    
    

      
Datetime
      

    
  
  

    

      
2012-12-31 01:00:00
      
2945.0
    
    

      
2012-12-31 02:00:00
      
2868.0
    
    

      
2012-12-31 03:00:00
      
2812.0
    
    

      
2012-12-31 04:00:00
      
2812.0
    
    

      
2012-12-31 05:00:00
      
2860.0
    
  

In [5]:

    

data.plot()


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x7efbc832db50>






    

In [7]:

    

decomposed = seasonal_decompose(data['DEOK_MW'], model='additive', freq=1)
x =decomposed.plot() #See note below about this


    

In [14]:

    

data['stationary']=data['AEP_MW'].diff()


    

In [15]:

    

data.head()


    

    
Out[15]:







  

    

      

      
AEP_MW
      
stationary
    
    

      
Datetime
      

      

    
  
  

    

      
2004-12-31 01:00:00
      
13478.0
      
NaN
    
    

      
2004-12-31 02:00:00
      
12865.0
      
-613.0
    
    

      
2004-12-31 03:00:00
      
12577.0
      
-288.0
    
    

      
2004-12-31 04:00:00
      
12517.0
      
-60.0
    
    

      
2004-12-31 05:00:00
      
12670.0
      
153.0
    
  

In [16]:

    

data['stationary'].plot()


    

    
Out[16]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f2d84eda810>






    

In [17]:

    

decomposed = seasonal_decompose(data['stationary'].dropna(), model='additive', freq=1)
x =decomposed.plot() #See note below about this


    

In [18]:

    

pd.tools.plotting.lag_plot(data['AEP_MW'])


    

    




/vagrant/pythondata/env/lib/python2.7/site-packages/ipykernel_launcher.py:1: FutureWarning: 'pandas.tools.plotting.lag_plot' is deprecated, import 'pandas.plotting.lag_plot' instead.
  """Entry point for launching an IPython kernel.






    
Out[18]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f2d7f394b90>






    

In [19]:

    

pd.tools.plotting.lag_plot(data['stationary'])


    

    




/vagrant/pythondata/env/lib/python2.7/site-packages/ipykernel_launcher.py:1: FutureWarning: 'pandas.tools.plotting.lag_plot' is deprecated, import 'pandas.plotting.lag_plot' instead.
  """Entry point for launching an IPython kernel.






    
Out[19]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f2d8c67c890>






    

In [ ]: