BUG/API: date_conversion in read_csv with int vs float component parts
from the ML
https://groups.google.com/forum/?fromgroups#!topic/pydata/Lc10-vz4NpU

not really sure if this is a bug, more of a convention

```
In [58]: data = "YEAR,DOY,TEMP\n2001,1,10.5\n2001,2,11.8\n2001,3,67.4"

In [59]: def date_converter(x):                                                                                                         
        return dt.datetime.strptime(x, '%Y %j')

In [60]: pandas.read_csv(StringIO(data), parse_dates=[[0,1]], index_col=0, sep=",", keep_date_col=True, date_parser=date_converter)
Out[60]: 
            YEAR DOY  TEMP
YEAR_DOY                  
2001-01-01  2001   1  10.5
2001-01-02  2001   2  11.8
2001-01-03  2001   3  67.4

In [61]: data = "YEAR,DOY,TEMP\n2001.0,1.0,10.5\n2001.0,2.0,11.8\n2001.0,3,67.4"

In [62]: def date_converter2(*args):                                                                                                     
    return dt.datetime(int(float(args[0])),int(float(args[1])),1)
   ....: 

In [63]: pandas.read_csv(StringIO(data), parse_dates=[[0,1]], index_col=0, sep=",", keep_date_col=True, date_parser=date_converter2)
Out[63]: 
              YEAR  DOY  TEMP
YEAR_DOY                     
2001-01-01  2001.0  1.0  10.5
2001-02-01  2001.0  2.0  11.8
2001-03-01  2001.0    3  67.4

```
