SeriesGroupby.cumsum raises on object dtype
```
import pandas as pd

s = pd.Series(list('ABCDEF'))
grouper = pd.Series([0]*3+[1]*3)
```

The obvious attempt to obtain

```
0      A
1     AB
2    ABC
3      D
4     DE
5    DEF
dtype: object
```

using

```
s.groupby(grouper).cumsum()
```

raises a `DataError: No numeric types to aggregate`. A workaround is available via

```
s.groupby(grouper).apply(pd.Series.cumsum)
```

`SeriesGroupby.cumsum` should follow the behavior of `SeriesGroupby.sum`, where both `s.groupby(grouper).apply(pd.Series.sum)` and `s.groupby(grouper).sum()` produce the correct output:

```
0    ABC
1    DEF
dtype: object
```

This was introduced some time between 0.15.2 and 0.18.1, as observed [here](http://stackoverflow.com/a/38935108/509824).
#### output of `pd.show_versions()`

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Darwin
OS-release: 15.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.0
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: None
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
```
