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 """
