I have one dataframe like the following:
A
2014-06-02 09:00:00 ...
2014-06-02 10:00:00 ...
2014-06-02 11:00:00 ...
2014-06-02 12:00:00 ...
2014-06-03 09:00:00 ...
2014-06-03 10:00:00 ...
2014-06-04 11:00:00 ...
2014-06-04 12:00:00 ...
2014-06-05 11:00:00 ...
2014-06-05 12:00:00 ...
And another like the following
A
2014-06-03 13:14:00 ...
2014-06-04 16:33:00 ...
I need one dataframe like the following:
A
2014-06-02 09:00:00 ...
2014-06-02 10:00:00 ...
2014-06-02 11:00:00 ...
2014-06-02 12:00:00 ...
2014-06-05 11:00:00 ...
2014-06-05 12:00:00 ...
That is: Drop from the first dataframe every row having year-month-day in the second dataframe
You could use floor
, and ~
(invert symbol), and check to see if index of dfb isin
dfa:
dfa[~dfa.index.floor('D').isin(dfb.index.floor('D'))]
Note both indexes need to be datetime dtypes.
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