Pandas and DateTime TypeError: cannot compare a TimedeltaIndex with type float

Question

I have a pandas DataFrame Series time differences that looks like::

 print(delta_t)

 1       0 days 00:00:59
 3       0 days 00:04:22
 6       0 days 00:00:56
 8       0 days 00:01:21
 19      0 days 00:01:09
 22      0 days 00:00:36
 ...

(the full DataFrame had a bunch of NaNs which I dropped).

I'd like to know which delta_t's are less than 1 day, 1 hour, 1 minute, so I tried:

delta_t_lt1day = delta_t[np.where(delta_t < 30.)]

but then got a:

TypeError: cannot compare a TimedeltaIndex with type float

Little help?!?!

Answer 1

Assuming your Series is in timedelta format, you can skip the np.where, and index using something like this, where you compare your actual values to other timedeltas, using the appropriate units:

delta_t_lt1day = delta_t[delta_t < pd.Timedelta(1,'D')]

delta_t_lt1hour = delta_t[delta_t < pd.Timedelta(1,'h')]

delta_t_lt1minute = delta_t[delta_t < pd.Timedelta(1,'m')]

You'll get the following series:

>>> delta_t_lt1day
0
1    00:00:59
3    00:04:22
6    00:00:56
8    00:01:21
19   00:01:09
22   00:00:36
Name: 1, dtype: timedelta64[ns]
>>> delta_t_lt1hour
0
1    00:00:59
3    00:04:22
6    00:00:56
8    00:01:21
19   00:01:09
22   00:00:36
Name: 1, dtype: timedelta64[ns]
>>> delta_t_lt1minute
0
1    00:00:59
6    00:00:56
22   00:00:36
Name: 1, dtype: timedelta64[ns]