In [4]:

    

import pandas as pd


    

    




/Users/charilaostsarouchas/anaconda/lib/python2.7/site-packages/pytz/__init__.py:29: UserWarning: Module argparse was already imported from /Users/charilaostsarouchas/anaconda/lib/python2.7/argparse.pyc, but /Users/charilaostsarouchas/anaconda/lib/python2.7/site-packages is being added to sys.path
  from pkg_resources import resource_stream

In [16]:

    

# transform to date time 
print "examples of dates in string format: "
date_strings = ['12:00-1:00 AM', '1:00-2:00AM', '2:00-3:00AM', '3:00-4:00AM', '4:00-5:00AM', '5:00-6:00AM', '6:00-7:00AM', '7:00-8:00AM', '8:00-9:00AM', '9:00-10:00AM', '10:00-11:00AM', '11:00-12:00PM', '12:00-1:00PM', '1:00-2:00PM', '2:00-3:00PM', '3:00-4:00PM', '4:00-5:00PM', '5:00-6:00PM', '6:00-7:00PM', '7:00-8:00PM', '8:00-9:00PM', '9:00-10:00PM', '10:00-11:00PM', '11:00-12:00AM']
print date_strings

# usually we are interested for the starting time and not the range
date_strings = [x.split("-")[0] + x[-2:] for x in date_strings]
print "formated date strings: "
print date_strings

print "the dates are parsed to date time objects:"
timestamps = pd.to_datetime(date_strings).values
for ii, x in enumerate(date_strings):
    print date_strings[ii], "=>",  timestamps[ii]


    

    




examples of dates in string format: 
['12:00-1:00 AM', '1:00-2:00AM', '2:00-3:00AM', '3:00-4:00AM', '4:00-5:00AM', '5:00-6:00AM', '6:00-7:00AM', '7:00-8:00AM', '8:00-9:00AM', '9:00-10:00AM', '10:00-11:00AM', '11:00-12:00PM', '12:00-1:00PM', '1:00-2:00PM', '2:00-3:00PM', '3:00-4:00PM', '4:00-5:00PM', '5:00-6:00PM', '6:00-7:00PM', '7:00-8:00PM', '8:00-9:00PM', '9:00-10:00PM', '10:00-11:00PM', '11:00-12:00AM']
the dates are parsed to date time objects:
12:00-1:00 AM => 2015-09-30T03:00:00.000000000+0200
1:00-2:00AM => 2015-09-30T05:00:00.000000000+0200
2:00-3:00AM => 2015-09-30T07:00:00.000000000+0200
3:00-4:00AM => 2015-09-30T09:00:00.000000000+0200
4:00-5:00AM => 2015-09-30T11:00:00.000000000+0200
5:00-6:00AM => 2015-09-30T13:00:00.000000000+0200
6:00-7:00AM => 2015-09-30T15:00:00.000000000+0200
7:00-8:00AM => 2015-09-30T17:00:00.000000000+0200
8:00-9:00AM => 2015-09-30T19:00:00.000000000+0200
9:00-10:00AM => 2015-09-30T21:00:00.000000000+0200
10:00-11:00AM => 2015-09-30T23:00:00.000000000+0200
11:00-12:00PM => 2015-10-01T13:00:00.000000000+0200
12:00-1:00PM => 2015-09-30T15:00:00.000000000+0200
1:00-2:00PM => 2015-09-30T17:00:00.000000000+0200
2:00-3:00PM => 2015-09-30T19:00:00.000000000+0200
3:00-4:00PM => 2015-09-30T21:00:00.000000000+0200
4:00-5:00PM => 2015-09-30T23:00:00.000000000+0200
5:00-6:00PM => 2015-10-01T01:00:00.000000000+0200
6:00-7:00PM => 2015-10-01T03:00:00.000000000+0200
7:00-8:00PM => 2015-10-01T05:00:00.000000000+0200
8:00-9:00PM => 2015-10-01T07:00:00.000000000+0200
9:00-10:00PM => 2015-10-01T09:00:00.000000000+0200
10:00-11:00PM => 2015-10-01T11:00:00.000000000+0200
11:00-12:00AM => 2015-10-01T01:00:00.000000000+0200

In [18]:

    

# And if we want to transform to the weekday
pd.to_datetime(date_strings).dayofweek


    

    
Out[18]:





array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3,
       2], dtype=int32)

In [20]:

    

#Date of week mapping
DAY_OF_WEEK = {                                                                
    0: 'Monday',                                                               
    1: 'Tuesday',                                                              
    2: 'Wednesday',                                                            
    3: 'Thursday',                                                             
    4: 'Friday',                                                               
    5: 'Saturday',                                                             
    6: 'Sunday'                                                                
}  
# And if we want to transform it to week days
[DAY_OF_WEEK[x] for x in pd.to_datetime(date_strings).dayofweek]


    

    
Out[20]:





['Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Thursday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Wednesday',
 'Thursday',
 'Thursday',
 'Thursday',
 'Thursday',
 'Thursday',
 'Wednesday']

In [ ]: