Reading the Docklight CO2 instrument text file

In [1]:

    

'''
Docklight Log File (ASCII) - Started 6/14/2013 11:34:17.033 
 RH0000   P1040X<CR><LF>
2013/06/04 19:42:23 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>
2013/06/04 19:42:25 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>
2013/06/04 19:42:27 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>
2013/06/04 19:42:29 - G 498.00 T26.79    HT0000 RH0000   P1040X<CR><LF>
2013/06/04 19:42:31 - G 498.00 T26.80    HT0000 RH0000   P1042X<CR><LF>
'''


    

    
Out[1]:





'\nDocklight Log File (ASCII) - Started 6/14/2013 11:34:17.033 \n RH0000   P1040X<CR><LF>\n2013/06/04 19:42:23 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>\n2013/06/04 19:42:25 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>\n2013/06/04 19:42:27 - G 498.00 T26.78    HT0000 RH0000   P1040X<CR><LF>\n2013/06/04 19:42:29 - G 498.00 T26.79    HT0000 RH0000   P1040X<CR><LF>\n2013/06/04 19:42:31 - G 498.00 T26.80    HT0000 RH0000   P1042X<CR><LF>\n'

In [2]:

    

import pandas as pd


    

In [3]:

    

col_specs=[(0,10), (11,19), (23,30), (32,37), (43,47), (50,54), (58,62)]


    

In [4]:

    

df = pd.read_fwf('/usgs/data2/notebook/data/ICO2sensordata_v1.txt',
        colspecs=col_specs, skiprows=2, parse_dates =[[0,1]], index_col=0, 
        names=['date','time','CO2','Temperature',
           'Humidity','Relative Humidity','Pressure'],
        header=None, nrows=500000)


    

In [ ]:

    

df = pd.read_fwf('/usgs/data2/notebook/data/ICO2sensordata_v1.txt',
        colspecs=col_specs, skiprows=2, parse_dates =[[0,1]], index_col=0, 
        names=['date','time','CO2','Temperature',
           'Humidity','Relative Humidity','Pressure'],
        header=None, nrows=500000)


    

In [ ]:

    

df


    

In [5]:

    

df.head()


    

    
Out[5]:






  

    

      

      
CO2
      
Temperature
      
Humidity
      
Relative Humidity
      
Pressure
    
    

      
date_time
      

      

      

      

      

    
  
  

    

      
2013-06-04 19:42:23
      
 498
      
 26.78
      
 0
      
 0
      
 1040
    
    

      
2013-06-04 19:42:25
      
 498
      
 26.78
      
 0
      
 0
      
 1040
    
    

      
2013-06-04 19:42:27
      
 498
      
 26.78
      
 0
      
 0
      
 1040
    
    

      
2013-06-04 19:42:29
      
 498
      
 26.79
      
 0
      
 0
      
 1040
    
    

      
2013-06-04 19:42:31
      
 498
      
 26.80
      
 0
      
 0
      
 1042
    
  

In [6]:

    

df_5m=df.resample('5min',how='mean')


    

In [7]:

    

df_5m


    

    
Out[7]:




&ltclass 'pandas.core.frame.DataFrame'>
DatetimeIndex: 2831 entries, 2013-06-04 19:40:00 to 2013-06-14 15:30:00
Freq: 5T
Data columns (total 5 columns):
CO2                  1990  non-null values
Temperature          1990  non-null values
Humidity             1990  non-null values
Relative Humidity    1990  non-null values
Pressure             1990  non-null values
dtypes: float64(5)

In [8]:

    

df_5m[['CO2','Temperature']].plot(figsize=(10,4),secondary_y='Temperature',grid=True);


    

In [ ]: