ENH: Added functionality in resample to resolve #10530
closes #10530 

I'm not 100% sure that I implemented this per the documentation or that my tests are complete but I'd be glad to make any necessary changes.

@jreback — thanks!
 @jreback — any comments on the updates?
 @jreback: I've been working on this and managed to move the code to `_get_time_delta_bins` and get it passing tests. However, the addition of the code to the `_get_time_delta_bins` function causes a segmentation fault (:gasp:). I traced this specific segfault to Numpy's `multiarray` module, though looking through resources on the Numpy side of things didn't return anything helpful.  

Do you have any insights on this?

**Reproducibility Instructions**

```
In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: np.__version__
Out[3]: '1.9.2'

In [4]: rng = pd.timedelta_range(start = '0s', periods = 25, freq = 's')                                                                                                             

In [5]: ts = pd.Series(np.random.randn(len(rng)), index = rng)

In [6]: with_base = ts.resample('2s', base = 5)
All good after if in _get_binner_for_resample
All good after grouping
All good after setting values in _resample_timestamps
python(45587,0x7fff79f72300) malloc: *** error for object 0x4000000000000000: pointer being freed was not allocated
*** set a breakpoint in malloc_error_break to debug
/Users/safia/anaconda/bin/python.app: line 3: 45587 Abort trap: 6           /Users/safia/anaconda/python.app/Contents/MacOS/python "$@"
```

And the crash report:

```
Process:               python [45587]
Path:                  /Users/USER/*/python.app/Contents/MacOS/python
Identifier:            python
Version:               ???
Code Type:             X86-64 (Native)
Parent Process:        bash [45586]
Responsible:           Terminal [1158]
User ID:               501

Date/Time:             2015-07-27 21:53:18.854 -0700
OS Version:            Mac OS X 10.90 (14A389)
Report Version:        11
Anonymous UUID:        DF1BBB33-4990-2AE4-9F20-0908197EB0E8

Sleep/Wake UUID:       49651817-F061-435F-AEF2-1606CDE5746E

Time Awake Since Boot: 41000 seconds
Time Since Wake:       10000 seconds

Crashed Thread:        0  Dispatch queue: com.apple.main-thread

Exception Type:        EXC_CRASH (SIGABRT)
Exception Codes:       0x0000000000000000, 0x0000000000000000

Application Specific Information:
abort() called
*** error for object 0x4000000000000000: pointer being freed was not allocated


Thread 0 Crashed:: Dispatch queue: com.apple.main-thread
0   libsystem_kernel.dylib          0x00007fff8feb1282 __pthread_kill + 10
1   libsystem_c.dylib               0x00007fff8b292b73 abort + 129
2   libsystem_malloc.dylib          0x00007fff934ef937 free + 428
3   multiarray.so                   0x0000000103ab081e _buffer_clear_info + 110
4   multiarray.so                   0x0000000103ab079a _array_dealloc_buffer_info + 74
5   multiarray.so                   0x0000000103a8c3f2 array_dealloc + 18
6   algos.so                        0x00000001049c0022 __pyx_pw_6pandas_5algos_417group_mean_bin_float64 + 4058 (algos.c:130491)
7   libpython2.7.dylib              0x00000001000c39bd PyEval_EvalFrameEx + 24989
8   libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
9   libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
10  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
11  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
12  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
13  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
14  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
15  libpython2.7.dylib              0x000000010003e1d0 function_call + 176
16  libpython2.7.dylib              0x000000010000c7b2 PyObject_Call + 98
17  libpython2.7.dylib              0x00000001000bea0a PyEval_EvalFrameEx + 4586
18  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
19  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
20  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
21  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
22  libpython2.7.dylib              0x00000001000c505b PyEval_EvalFrameEx + 30779
23  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
24  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
25  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
26  libpython2.7.dylib              0x00000001000c5275 PyEval_EvalFrameEx + 31317
27  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
28  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
29  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
30  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
31  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
32  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
33  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
34  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
35  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
36  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
37  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
38  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
39  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
40  libpython2.7.dylib              0x000000010003e1d0 function_call + 176
41  libpython2.7.dylib              0x000000010000c7b2 PyObject_Call + 98
42  libpython2.7.dylib              0x00000001000bea0a PyEval_EvalFrameEx + 4586
43  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
44  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
45  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
46  libpython2.7.dylib              0x00000001000c5dc6 PyEval_EvalCode + 54
47  libpython2.7.dylib              0x00000001000eb17e PyRun_FileExFlags + 174
48  libpython2.7.dylib              0x00000001000eb41a PyRun_SimpleFileExFlags + 458
49  libpython2.7.dylib              0x000000010010248d Py_Main + 3165
50  com.continuum.python            0x0000000100000f54 start + 52

Thread 1:
0   libsystem_kernel.dylib          0x00007fff8feb1132 __psynch_cvwait + 10
1   libpython2.7.dylib              0x00000001000ff7b4 PyThread_acquire_lock + 116
2   libpython2.7.dylib              0x0000000100104295 lock_PyThread_acquire_lock + 69
3   libpython2.7.dylib              0x00000001000c39bd PyEval_EvalFrameEx + 24989
4   libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
5   libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
6   libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
7   libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
8   libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
9   libpython2.7.dylib              0x000000010003e1d0 function_call + 176
10  libpython2.7.dylib              0x000000010000c7b2 PyObject_Call + 98
11  libpython2.7.dylib              0x00000001000bea0a PyEval_EvalFrameEx + 4586
12  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
13  libpython2.7.dylib              0x00000001000c3d10 PyEval_EvalFrameEx + 25840
14  libpython2.7.dylib              0x00000001000c505b PyEval_EvalFrameEx + 30779
15  libpython2.7.dylib              0x00000001000c505b PyEval_EvalFrameEx + 30779
16  libpython2.7.dylib              0x00000001000c5ca3 PyEval_EvalCodeEx + 2115
17  libpython2.7.dylib              0x000000010003e1d0 function_call + 176
18  libpython2.7.dylib              0x000000010000c7b2 PyObject_Call + 98
19  libpython2.7.dylib              0x000000010001dccd instancemethod_call + 333
20  libpython2.7.dylib              0x000000010000c7b2 PyObject_Call + 98
21  libpython2.7.dylib              0x00000001000bc567 PyEval_CallObjectWithKeywords + 87
22  libpython2.7.dylib              0x00000001001047a7 t_bootstrap + 71
23  libsystem_pthread.dylib         0x00007fff8f7272fc _pthread_body + 131
24  libsystem_pthread.dylib         0x00007fff8f727279 _pthread_start + 176
25  libsystem_pthread.dylib         0x00007fff8f7254b1 thread_start + 13

Thread 2:
0   libsystem_kernel.dylib          0x00007fff8feb1132 __psynch_cvwait + 10
1   interpreter.so                  0x00000001052a707b th_worker(void*) + 171
2   libsystem_pthread.dylib         0x00007fff8f7272fc _pthread_body + 131
3   libsystem_pthread.dylib         0x00007fff8f727279 _pthread_start + 176
4   libsystem_pthread.dylib         0x00007fff8f7254b1 thread_start + 13

Thread 3:
0   libsystem_kernel.dylib          0x00007fff8feb1132 __psynch_cvwait + 10
1   interpreter.so                  0x00000001052a707b th_worker(void*) + 171
2   libsystem_pthread.dylib         0x00007fff8f7272fc _pthread_body + 131
3   libsystem_pthread.dylib         0x00007fff8f727279 _pthread_start + 176
4   libsystem_pthread.dylib         0x00007fff8f7254b1 thread_start + 13

Thread 4:
0   libsystem_kernel.dylib          0x00007fff8feb1132 __psynch_cvwait + 10
1   interpreter.so                  0x00000001052a707b th_worker(void*) + 171
2   libsystem_pthread.dylib         0x00007fff8f7272fc _pthread_body + 131
3   libsystem_pthread.dylib         0x00007fff8f727279 _pthread_start + 176
4   libsystem_pthread.dylib         0x00007fff8f7254b1 thread_start + 13

Thread 5:
0   libsystem_kernel.dylib          0x00007fff8feb1132 __psynch_cvwait + 10
1   interpreter.so                  0x00000001052a707b th_worker(void*) + 171
2   libsystem_pthread.dylib         0x00007fff8f7272fc _pthread_body + 131
3   libsystem_pthread.dylib         0x00007fff8f727279 _pthread_start + 176
4   libsystem_pthread.dylib         0x00007fff8f7254b1 thread_start + 13

Thread 0 crashed with X86 Thread State (64-bit):
  rax: 0x0000000000000000  rbx: 0x0000000000000006  rcx: 0x00007fff5fbfb648  rdx: 0x0000000000000000
  rdi: 0x0000000000000513  rsi: 0x0000000000000006  rbp: 0x00007fff5fbfb670  rsp: 0x00007fff5fbfb648
   r8: 0x0000000000000001   r9: 0x0000000000000000  r10: 0x0000000008000000  r11: 0x0000000000000206
  r12: 0x000000010564e230  r13: 0x0000000000000001  r14: 0x00007fff79f72300  r15: 0x0000000000000000
  rip: 0x00007fff8feb1282  rfl: 0x0000000000000206  cr2: 0x00007fff7975ffd8

Logical CPU:     0
Error Code:      0x02000148
Trap Number:     133


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```
 try this: https://github.com/jreback/pandas/commit/f593a22c2f8e3f161c868344d37d32fb41ada7a0

your test is not right though. it should be the same length as resampling w/o the base. It just shifts the labels.
 @jreback: The documentation is a little vague on this and I haven't used `TimeDeltaIndex`s much specifically, but my thought process was that the `base` variable shifts just the origin of the index up to but not past the end of the original index. For example,

```
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: rng = pd.date_range('1/1/2000 00:00:00', '1/1/2000 02:00', freq='s') 
In [4]: ts = pd.Series(np.random.randn(len(rng)), index=rng)
In [5]: ts.resample("5min")
Out[6]: 
2000-01-01 00:00:00    0.013062
2000-01-01 00:05:00    0.139534
2000-01-01 00:10:00   -0.041256
2000-01-01 00:15:00    0.053652
2000-01-01 00:20:00   -0.001729
2000-01-01 00:25:00   -0.029746
2000-01-01 00:30:00    0.088576
2000-01-01 00:35:00    0.037251
2000-01-01 00:40:00    0.026843
2000-01-01 00:45:00    0.072279
2000-01-01 00:50:00   -0.027181
2000-01-01 00:55:00    0.000295
2000-01-01 01:00:00   -0.011841
2000-01-01 01:05:00    0.012241
2000-01-01 01:10:00    0.066539
2000-01-01 01:15:00   -0.084721
2000-01-01 01:20:00   -0.172637
2000-01-01 01:25:00    0.006850
2000-01-01 01:30:00    0.060185
2000-01-01 01:35:00   -0.025297
2000-01-01 01:40:00    0.076625
2000-01-01 01:45:00    0.052509
2000-01-01 01:50:00    0.052641
2000-01-01 01:55:00   -0.027289
2000-01-01 02:00:00    0.153006
Freq: 5T, dtype: float64

In [7]: ts.resample("5min", base = 2)
Out[7]: 
1999-12-31 23:57:00    0.024507
2000-01-01 00:02:00    0.051019
2000-01-01 00:07:00    0.097611
2000-01-01 00:12:00   -0.009624
2000-01-01 00:17:00    0.069433
2000-01-01 00:22:00   -0.038853
2000-01-01 00:27:00   -0.071469
2000-01-01 00:32:00    0.100760
2000-01-01 00:37:00    0.049147
2000-01-01 00:42:00    0.035064
2000-01-01 00:47:00    0.071487
2000-01-01 00:52:00   -0.017152
2000-01-01 00:57:00   -0.030361
2000-01-01 01:02:00   -0.034262
2000-01-01 01:07:00    0.093033
2000-01-01 01:12:00   -0.000299
2000-01-01 01:17:00   -0.100216
2000-01-01 01:22:00   -0.124684
2000-01-01 01:27:00   -0.023405
2000-01-01 01:32:00    0.068558
2000-01-01 01:37:00    0.028446
2000-01-01 01:42:00    0.049118
2000-01-01 01:47:00    0.035673
2000-01-01 01:52:00    0.047628
2000-01-01 01:57:00   -0.030767
Freq: 5T, dtype: float64

In [8]: ts.resample("5min", base = 8)
Out[8]: 
1999-12-31 23:58:00   -0.006227
2000-01-01 00:03:00    0.125830
2000-01-01 00:08:00    0.003593
2000-01-01 00:13:00    0.013914
2000-01-01 00:18:00    0.073193
2000-01-01 00:23:00   -0.054944
2000-01-01 00:28:00   -0.025494
2000-01-01 00:33:00    0.073621
2000-01-01 00:38:00    0.046354
2000-01-01 00:43:00    0.094799
2000-01-01 00:48:00    0.028624
2000-01-01 00:53:00   -0.041689
2000-01-01 00:58:00   -0.031873
2000-01-01 01:03:00   -0.017953
2000-01-01 01:08:00    0.100750
2000-01-01 01:13:00   -0.070052
2000-01-01 01:18:00   -0.090126
2000-01-01 01:23:00   -0.078358
2000-01-01 01:28:00    0.021255
2000-01-01 01:33:00   -0.005668
2000-01-01 01:38:00    0.054962
2000-01-01 01:43:00    0.074532
2000-01-01 01:48:00    0.022946
2000-01-01 01:53:00    0.004059
2000-01-01 01:58:00    0.047995
Freq: 5T, dtype: float64
```

An explanation would be much appreciated as I'm not so savvy with TimeDeltaIndex! :)

![49878803](https://cloud.githubusercontent.com/assets/1857993/8972826/83af9878-3612-11e5-82b9-73579dcf7adb.jpg)
 base should work the same for any of the datetimelikes

it's just an add to every value 

it's not really s shift but it works the same way
so let's implement it by adding I think is easiest 
(FYI this is one of those oddball parameters - not even sure what a good use case is)
 @jreback — Agreed. The documentation on it is pretty poor. Did another retrace of how `base` is applied on `DateTimeIndex` and it looks like [these lines](https://github.com/pydata/pandas/blob/master/pandas/tseries/resample.py#L422) have the desired affect. I'll take another look at it this weekend and submit the (what I hope will be last) pull request.
 > (FYI this is one of those oddball parameters - not even sure what a good use case is)

I actually use `base` all the time with DatetimeIndex -- it's useful for doing resampling a time-series to daily values with the origin not at midnight (e.g., from noon to noon instead).
 @jreback: Made updates. Updated the tests a bit so that functionality aligns with what happens when you `resample` with a `DatetimeIndex`. Let me know how it looks.
 looks good

pls rebase on master and squash 
 @jreback — squashed.
 pls add a note in whatsnew 
 That outta do it, @jreback — let me know if it needs anything else.
 merged via https://github.com/pydata/pandas/commit/433602022bfbb9ee2424b77694c60f276065dee8

thanks!
