BUG: cython groupby cummin/cummax assumes groups ordered
#### Code Sample, a copy-pastable example if possible

```python
>>> import pandas as pd
>>> pd.DataFrame(dict(a=[1,2,1], b=[2,1,1])).groupby('a').b.cummax()
0    2
1    1
2    1
Name: b, dtype: int64
```
#### Problem description

The current github version of pandas has cython implementations of `groupby.cummin` and `groupby.cummax` which give the wrong answer when the groups are unordered. (See #15048, 0fe491d.)

#### Expected Output

```python
0    2
1    1
2    2
Name: b, dtype: int64
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.8-100.fc24.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: C
LANG: C
LOCALE: None.None

pandas: 0.19.0+575.g5667a3a
pytest: 3.0.5
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
xarray: 0.9.1
IPython: 4.2.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.0
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: 0.999
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
