Groupby transform idxmax return floats
`Transform` with `idxmax` return wrong output - floats instead `datetimes`

Sample: 

    rng = pd.date_range('1/1/2011', periods=15, freq='D') 
    np.random.seed(4)
    
    stocks = pd.DataFrame({ 
        'price':(np.random.randn(15).cumsum() + 10) },index = rng)
    
    stocks['week_id'] = pd.to_datetime(stocks.index).week #used for the groupby
    print (stocks)
                    price  week_id
    2011-01-01  10.050562       52
    2011-01-02  10.550513       52
    2011-01-03   9.554604        1
    2011-01-04  10.248203        1
    2011-01-05   9.829901        1
    2011-01-06   8.245324        1
    2011-01-07   7.597617        1
    2011-01-08   8.196192        1
    2011-01-09   8.528442        1
    2011-01-10   7.380966        2
    2011-01-11   7.999635        2
    2011-01-12   7.911648        2
    2011-01-13   8.336721        2
    2011-01-14   8.668974        2
    2011-01-15   7.512158        2

<!-- -->
    
    print (stocks.groupby(stocks['week_id'])['price'].transform('idxmax'))
    2011-01-01    1.293926e+18
    2011-01-02    1.293926e+18
    2011-01-03    1.294099e+18
    2011-01-04    1.294099e+18
    2011-01-05    1.294099e+18
    2011-01-06    1.294099e+18
    2011-01-07    1.294099e+18
    2011-01-08    1.294099e+18
    2011-01-09    1.294099e+18
    2011-01-10    1.294963e+18
    2011-01-11    1.294963e+18
    2011-01-12    1.294963e+18
    2011-01-13    1.294963e+18
    2011-01-14    1.294963e+18
    2011-01-15    1.294963e+18
    Freq: D, Name: price, dtype: float64
    
    print (stocks.groupby(stocks['week_id'])['price'].idxmax())
    week_id
    1    2011-01-04
    2    2011-01-14
    52   2011-01-02
    Name: price, dtype: datetime64[ns]

[SO question](http://stackoverflow.com/questions/42045549/using-groupby-and-transform-to-get-idxmax-per-week).

    print (pd.show_versions())
    
    INSTALLED VERSIONS
    ------------------
    commit: None
    python: 3.5.1.final.0
    python-bits: 64
    OS: Windows
    OS-release: 7
    machine: AMD64
    processor: Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
    byteorder: little
    LC_ALL: None
    LANG: sk_SK
    LOCALE: None.None
    
    pandas: 0.19.2+0.g825876c.dirty
    nose: 1.3.7
    pip: 8.1.1
    setuptools: 20.3
    Cython: 0.23.4
    numpy: 1.11.0
    scipy: 0.17.0
    statsmodels: 0.6.1
    xarray: None
    IPython: 4.1.2
    sphinx: 1.3.1
    patsy: 0.4.0
    dateutil: 2.5.1
    pytz: 2016.2
    blosc: None
    bottleneck: 1.0.0
    tables: 3.2.2
    numexpr: 2.5.1
    matplotlib: 1.5.1
    openpyxl: 2.3.2
    xlrd: 0.9.4
    xlwt: 1.0.0
    xlsxwriter: 0.8.4
    lxml: 3.6.0
    bs4: 4.4.1
    html5lib: 0.999
    httplib2: None
    apiclient: None
    sqlalchemy: 1.0.12
    pymysql: None
    psycopg2: None
    jinja2: 2.8
    boto: 2.39.0
    pandas_datareader: 0.2.1
    None

