unwanted cast of string to datetime
Note how the string 'M15' becomes somehow 8/15/2015!

> > > pandas.Series([datetime.datetime(2015,1,1), 'M15'])
> > > 0   2015-01-01
> > > 1   2015-08-15
> > > dtype: datetime64[ns]

Compare other arbitrary strings that are left alone:

> > > pandas.Series([datetime.datetime(2015,1,1), 'MM15'])
> > > 0    2015-01-01 00:00:00
> > > 1                   MM15
> > > dtype: object

Thank you for your prompt answers.

1) your dtype solution does not work for me:

> > > pd.Series([datetime.datetime(2015,1,1), 'M15'], dtype=object)
> > > 0   2015-01-01
> > > 1   2015-08-15
> > > dtype: datetime64[ns]

2) there are further inconsistencies when initializing a dataframe with the string 'M15'.  printing the dataframe shows the string M15, but examining the first irow (or doing a loop over iterrows()) shows the data instead.  this is in my opinion dangerous behaviour.  

> > > pd.DataFrame( dict(start=[ pd.datetime(2015,1,1) ], end=['M15'] ) )
> > >    end      start
> > > 0  M15 2015-01-01
> > > 
> > > pd.DataFrame( dict(start=[ pd.datetime(2015,1,1) ], end=['M15'] ) )['end']
> > > 0    M15
> > > Name: end, dtype: object
> > > 
> > > pd.DataFrame( dict(start=[ pd.datetime(2015,1,1) ], end=['M15'] ) ).irow(0)
> > > end     2015-08-15
> > > start   2015-01-01
> > > Name: 0, dtype: datetime64[ns]

In case it matters:

> > > pd.**version**
> > > '0.15.2'
