In [1]:

    

'''
Read data from a file that looks like this:

2013-03-26 08:51:18     69.35   20.75
2013-03-26 08:56:19     69.35   20.75
2013-03-26 09:01:19     69.125  20.625
2013-03-26 09:06:20     69.6866 20.937
'''


    

    
Out[1]:





'\nRead data from a file that looks like this:\n\n2013-03-26 08:51:18     69.35   20.75\n2013-03-26 08:56:19     69.35   20.75\n2013-03-26 09:01:19     69.125  20.625\n2013-03-26 09:06:20     69.6866 20.937\n'

In [2]:

    

import pandas as pd
log_file = './data/temperaturedata2013-03-25-22-19-23.log'
df = pd.read_csv(log_file, parse_dates =[[0,1]],header=None,index_col=0,
    sep=r"\s*",names=['date','time','F','C'])
df.plot();ylabel('temp')


    

    
Out[2]:





<matplotlib.text.Text at 0x319af90>






    

In [7]:

    

df_15 = df.resample('15min',how='mean')
df_15.plot();ylabel('temp')


    

    
Out[7]:





<matplotlib.text.Text at 0x3963790>






    

In [4]:

    

df.head(10)


    

    
Out[4]:






  

    

      

      
F
      
C
    
    

      
date_time
      

      

    
  
  

    

      
2013-03-26 08:51:18
      
 69.3500
      
 20.750
    
    

      
2013-03-26 08:56:19
      
 69.3500
      
 20.750
    
    

      
2013-03-26 09:01:19
      
 69.1250
      
 20.625
    
    

      
2013-03-26 09:06:20
      
 69.6866
      
 20.937
    
    

      
2013-03-26 09:11:21
      
 69.3500
      
 20.750
    
    

      
2013-03-26 09:16:21
      
 69.2366
      
 20.687
    
    

      
2013-03-26 09:21:22
      
 69.2366
      
 20.687
    
    

      
2013-03-26 09:26:22
      
 69.4616
      
 20.812
    
    

      
2013-03-26 09:31:23
      
 69.4616
      
 20.812
    
    

      
2013-03-26 09:36:24
      
 69.5750
      
 20.875
    
  

In [ ]:

    




    

In [3]:

    

import numpy as np
import matplotlib.dates as mdates
import matplotlib.pyplot as plt


    

In [17]:

    

data=np.genfromtxt(log_file,dtype=None,names=['date','time','F','C'])


    

In [20]:

    

dates=mdates.datestr2num(data['date']) # get the integer day
times,null=np.modf(mdates.datestr2num(data['time']))  # get fractional day


    

In [22]:

    

jd=dates+times # add fractional day to integer day


    

In [38]:

    

fig=plt.figure(figsize=(10,5)) 
ax1 = fig.add_subplot(111)
ax1.plot_date(jd,data['C'],'ko-');
plt.grid()
plt.ylabel('Temp')


    

    
Out[38]:





<matplotlib.text.Text at 0x4275090>






    

In [ ]: