I have two data frame, first named df1 having data as:
                 Date  Exact   Latitude  Longitude
0 1993-01-01 00:00:00    0.0  29.456137  85.506958
1 2017-10-01 05:00:00    0.0  27.694225  85.291702
2 2017-10-01 06:00:00    0.0  28.962729  80.912323
3 2017-10-02 05:00:00    0.0  27.699097  85.299431
4 2017-10-03 04:00:00    0.0  27.700438  85.329933
and df2 as
               Date (LT)  Raw Conc.
6551 2017-10-01 00:00:00       10.0
6552 2017-10-01 01:00:00        7.0
6553 2017-10-01 02:00:00       11.0
6554 2017-10-01 03:00:00       11.0
6555 2017-10-01 04:00:00       12.0
6556 2017-10-01 05:00:00        9.0
6557 2017-10-01 06:00:00        7.0
6558 2017-10-01 07:00:00        7.0
I want to merge the two dataframe based on common date and time in columns column Date and Date(LT) so that the final output is like:
Date                  Exact            Raw Conc.
2017-10-02 05:00:00    0.0               9.0
I tried to merge it by using the date of both data frame as an index by using df1.set_index('Date'). But, when I tried to check the index by using df1.index, it had not been used as an index. I also tried using :
newfile=df1.loc[(df1.Date==df2.Date)]
It gives me error:
ValueError: Can only compare identically-labeled Series objects
What is it I am missing ?
 
    