Pandas: Assign Datetime object to time intervals

I’m trying to create a new variable in which datetime64[ns] objects are assigned to 5 minute intervals. The new interval variable should span every 5 minute period from 00:00 to 23:55. The criteria for assignment is whether the time of the datetime64[ns] object falls within the corresponding 5 min interval. My actual data has numerous dates in the DateTime variable, but these different dates shouldn’t be taken into account – only the time element matters for assignment.

I’ve simulated this below. This example focuses on the time period circa 23:30 to 23:45, but it should exemplify what I’m trying to achieve for all the intervals from 00:00 to 23:55. I have included two random dates to illustrate how the dates should not have any bearing.

DateTime
2009-02-18 23:32:29 - would map to interval 23:30
2009-02-18 23:34:41 - would map to interval 23:30
2009-02-18 23:35:40 - would map to interval 23.35
2009-02-18 23:39:29 - would map to interval 23:35
2009-02-18 23:39:37 - would map to interval 23:35
2009-02-18 23:40:14 - would map to interval 23:40
2009-02-18 23:43:23 - would map to interval 23:40
2009-02-18 23:44:17 - would map to interval 23:40
...
2010-03-18 23:31:19 - also maps to interval 23:30 regardless of date
2010-03-18 23:33:31 - also maps to interval 23:30 regardless of date
2010-03-18 23:36:30 - also maps to interval 23.35 regardless of date
2010-03-18 23:38:21 - also maps to interval 23:35 regardless of date
2010-03-18 23:39:07 - also maps to interval 23:35 regardless of date
2010-03-18 23:41:44 - also maps to interval 23:40 regardless of date
2010-03-18 23:42:13 - also maps to interval 23:40 regardless of date
2010-03-18 23:43:37 - also maps to interval 23:40 regardless of date

For the sake of clarity I’m aiming for this result:

DateTime             Interval 
2009-02-18 23:32:29  23:30
2009-02-18 23:34:41  23:30
2009-02-18 23:35:40  23.35
2009-02-18 23:39:29  23:35
2009-02-18 23:39:37  23:35
2009-02-18 23:40:14  23:40
2009-02-18 23:43:23  23:40
2009-02-18 23:44:17  23:40
...
2010-03-18 23:31:19  23:30
2010-03-18 23:33:31  23:30
2010-03-18 23:36:30  23.35
2010-03-18 23:38:21  23:35
2010-03-18 23:39:07  23:35
2010-03-18 23:41:44  23:40
2010-03-18 23:42:13  23:40
2010-03-18 23:43:37  23:40

I’ve read the pandas documentation thoroughly and some questions on here that very loosely relate, but I can’t seem to get anything to achieve the right result.

---

Update

These are my library and system versions:

Pandas: 0.16.2
Numpy: 1.9.2
System version: '3.4.3 |Anaconda 2.3.0 (x86_64)| (default, Mar  6 2015, 12:07:41) n[GCC 4.2.1 (Apple Inc. build 5577)]

This is the error in full. Here you can see that with my actual data I’m working with a datetime64[ns] Series called question_time.

TypeError Traceback (most recent call last)
<ipython-input-416-d5c3256e6b40> in <module>()
----> 1 df_unique['Interval'] = ((df_unique['question_time'] - pd.TimedeltaIndex(df_unique['question_time'].dt.minute % 5, 'm')) - pd.TimedeltaIndex(df_unique['question_time'].dt.second , 's')).dt.time

//anaconda/lib/python3.4/site-packages/pandas/core/frame.py in __setitem__(self, key, value)
   2125         else:
   2126             # set column
-> 2127             self._set_item(key, value)
   2128 
   2129     def _setitem_slice(self, key, value):

//anaconda/lib/python3.4/site-packages/pandas/core/frame.py in _set_item(self, key, value)
   2209         # value exeption to occur first
   2210         if len(self):
-> 2211             self._check_setitem_copy()
   2212 
   2213     def insert(self, loc, column, value, allow_duplicates=False):

//anaconda/lib/python3.4/site-packages/pandas/core/generic.py in _check_setitem_copy(self, stacklevel, t, force)
   1302                 raise SettingWithCopyError(t)
   1303             elif value == 'warn':
-> 1304                 warnings.warn(t, SettingWithCopyWarning, stacklevel=stacklevel)
   1305 
   1306     def __delitem__(self, key):

TypeError: issubclass() arg 2 must be a class or tuple of classes

The issue seems to be with the SettingWithCopyError. I tried resetting all my variables and now I am getting this same warning with another operation as well.

Answer

Not sure of a better method but you can construct 2 TimeDeltaIndices and subtract this from your value, I use modulus op % to calc the number of minutes to subtract:

In [129]:
df['Interval'] = ((df['DateTime'] - pd.TimedeltaIndex(df['DateTime'].dt.minute % 5, 'm')) - pd.TimedeltaIndex(df['DateTime'].dt.second , 's')).dt.time
df

Out[129]:
              DateTime  Interval
0  2009-02-18 23:32:29  23:30:00
1  2009-02-18 23:34:41  23:30:00
2  2009-02-18 23:35:40  23:35:00
3  2009-02-18 23:39:29  23:35:00
4  2009-02-18 23:39:37  23:35:00
5  2009-02-18 23:40:14  23:40:00
6  2009-02-18 23:43:23  23:40:00
7  2009-02-18 23:44:17  23:40:00
8  2010-03-18 23:31:19  23:30:00
9  2010-03-18 23:33:31  23:30:00
10 2010-03-18 23:36:30  23:35:00
11 2010-03-18 23:38:21  23:35:00
12 2010-03-18 23:39:07  23:35:00
13 2010-03-18 23:41:44  23:40:00
14 2010-03-18 23:42:13  23:40:00
15 2010-03-18 23:43:37  23:40:00