For example we have dataframe like this:

                   SPY        AAPL         IBM        GOOG         GLD

2017-01-03  222.073914  114.311760  160.947433  786.140015  110.470001

2017-01-04  223.395081  114.183815  162.940125  786.900024  110.860001

2017-01-05  223.217606  114.764473  162.401047  794.020020  112.580002

2017-01-06  224.016220  116.043915  163.200043  806.150024  111.750000

2017-01-09  223.276779  117.106812  161.390244  806.650024  112.669998
...

Now we only we want to get highlighted part:

                   SPY        AAPL         IBM        GOOG         GLD

2017-01-03  222.073914  114.311760  160.947433  786.140015  110.470001

2017-01-04  223.395081  114.183815  162.940125  786.900024  110.860001

2017-01-05  223.217606  114.764473  162.401047  794.020020  112.580002

2017-01-06  224.016220  116.043915  163.200043  806.150024  111.750000

2017-01-09  223.276779  117.106812  161.390244  806.650024  112.669998

We can use Dataframe.ix[] method to get date related index data from the list.

if __name__ == '__main__':

    data=get_data()

    data=data.ix['2017-12-01':'2017-12-15', ['IBM', 'GOOG']]

    print(data)

    """

                       IBM         GOOG

    2017-12-01  154.759995  1010.169983

    2017-12-04  156.460007   998.679993

    2017-12-05  155.350006  1005.150024

    2017-12-06  154.100006  1018.380005

    2017-12-07  153.570007  1030.930054

    2017-12-08  154.809998  1037.050049

    2017-12-11  155.410004  1041.099976

    2017-12-12  156.740005  1040.479980

    2017-12-13  153.910004  1040.609985

    2017-12-15  152.500000  1064.189941

    """

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