In [37]:

    

from __future__ import division
import datetime
import pandas
import numpy
import matplotlib.pyplot as plt
import seaborn
seaborn.set_style("whitegrid")
seaborn.despine()
%matplotlib inline
%config InlineBackend.figure_formats = {'svg',}


    

In [38]:

    

df = pandas.read_csv('../data/pv_10kw.csv', skiprows=1)
df['                P # [W]'] *= 0.2
df['Date'] = df['Date'].apply(lambda x: datetime.datetime.strptime(x, '%Y-%m-%d %H:%M:%S'))
df.set_index('Date', inplace=True)


    

In [39]:

    

plt.figure(figsize=(11, 5))
plt.plot(df['2014-06-17 00:00:00':'2014-06-18 00:00:00'])
plt.show()

plt.figure(figsize=(11, 5))
plt.plot(df['2014-06-17 00:00:00':'2014-06-18 00:00:00'].rolling(15).mean())
plt.show()


    

In [40]:

    

df.rolling(15).mean().to_csv('../data/pv_2kw_rolling15.csv')


    

In [41]:

    

# df.to_csv('../data/pv_2kw.csv')


    

In [42]:

    

df.head()


    

    
Out[42]:






  

    

      

      
P # [W]
    
    

      
Date
      

    
  
  

    

      
2014-01-01 00:00:00
      
0.0
    
    

      
2014-01-01 00:01:00
      
0.0
    
    

      
2014-01-01 00:02:00
      
0.0
    
    

      
2014-01-01 00:03:00
      
0.0
    
    

      
2014-01-01 00:04:00
      
0.0