Python Pandas - how to apply boolean series to extract rows from dataframe

Question

I have a boolean series that I got from using .duplicated. I'm trying to figure out what rows of my dataframe are returning True (and what the data is in those rows). How can I use this boolean series to extract those rows?

Thanks - KC

EDIT- Data sample:

level_0 index   ID       date_time      value
54967   54967   54967   1/06/2016 19:30  1.00 
54968   54968   54968   1/06/2016 19:30  2.00 
54969   54969   54969   1/06/2016 19:43  3.00 
54970   54970   54970   1/06/2016 19:46  4.00 

Want to return this:

level_0 index   ID       date_time      value
54967   54967   54967   1/06/2016 19:30  1.00 
54968   54968   54968   1/06/2016 19:30  2.00 

Answer 1

use keep=False parameter when calling .duplicated()

df[df.duplicated(subset='date_time', keep=False)]

Test:

In [53]: df
Out[53]:
   evel_0  index     ID           date_time  value
0   54967  54967  54967 2016-01-06 19:30:00    1.0
1   54968  54968  54968 2016-01-06 19:30:00    2.0
2   54969  54969  54969 2016-01-06 19:43:00    3.0
3   54968  54968  54968 2016-01-06 19:30:00    5.0
4   54970  54970  54970 2016-01-06 19:46:00    4.0

In [54]: df[df.duplicated(subset='date_time', keep=False)]
Out[54]:
   evel_0  index     ID           date_time  value
0   54967  54967  54967 2016-01-06 19:30:00    1.0
1   54968  54968  54968 2016-01-06 19:30:00    2.0
3   54968  54968  54968 2016-01-06 19:30:00    5.0