Fix Timedelta.__floordiv__, __rfloordiv__
State: closed

It would not at all surprise me to learn that there are more corner cases that this misses.  Needs some eyeballs.

- [x] closes #18846
- [x] tests added / passed
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] whatsnew entry


Labels:
name: Bug
name: Timedelta
description: Timedelta data type

Comments:
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=h1) Report
> Merging [#18961](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/e1888f09630bdd236be1f3ec9577c275d6d67457?src=pr&el=desc) will **decrease** coverage by `49.91%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/18961/graphs/tree.svg?token=eZ4WkYLtcO&src=pr&width=650&height=150)](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=tree)

```diff
@@             Coverage Diff             @@
##           master   #18961       +/-   ##
===========================================
- Coverage   91.53%   41.61%   -49.92%     
===========================================
  Files         148      148               
  Lines       48688    48754       +66     
===========================================
- Hits        44566    20289    -24277     
- Misses       4122    28465    +24343
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `?` | |
| #single | `41.61% <ø> (-0.02%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/tseries/converter.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL3RzZXJpZXMvY29udmVydGVyLnB5) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/lib.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL2xpYi5weQ==) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/tools/hashing.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL3Rvb2xzL2hhc2hpbmcucHk=) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/tslib.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL3RzbGliLnB5) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/parser.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL3BhcnNlci5weQ==) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/io/sas/sas\_constants.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL3Nhcy9zYXNfY29uc3RhbnRzLnB5) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/types/concat.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL3R5cGVzL2NvbmNhdC5weQ==) | `0% <0%> (-100%)` | :arrow_down: |
| [pandas/io/sas/sas7bdat.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL3Nhcy9zYXM3YmRhdC5weQ==) | `0% <0%> (-91.08%)` | :arrow_down: |
| [pandas/io/sas/sas\_xport.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL3Nhcy9zYXNfeHBvcnQucHk=) | `0% <0%> (-90.28%)` | :arrow_down: |
| [pandas/core/tools/numeric.py](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvdG9vbHMvbnVtZXJpYy5weQ==) | `10.44% <0%> (-89.56%)` | :arrow_down: |
| ... and [109 more](https://codecov.io/gh/pandas-dev/pandas/pull/18961/diff?src=pr&el=tree-more) | |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=footer). Last update [e1888f0...f101378](https://codecov.io/gh/pandas-dev/pandas/pull/18961?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

The linting doesn't like `np.testing.assert_array_equal`.  What is the preferred usage?
we have banned all numpy functions, e.g. ``np.testing.assert_array_equal`` instead use ``tm.assert_numpy_array_equal``; they are not generally flexibile enough and some are buggy (don't compare object arrays correctly for example)
Ping
thanks!