DataFrame.ffill behaves different than DataFrame.interpolate(method='ffill') along axes
It looks like `df.ffill(axis=0)` has the same behavior as `test_df.interpolate(method='ffill', axis=1)`.

```
from pandas.util.testing import assert_frame_equal
import numpy as np
import pandas as pd

n = np.nan
test_df = pd.DataFrame([[0, 2, n, n],
                        [1, n, 4, 6],
                        [n, 3, 5, n]])

assert_frame_equal(
    test_df.interpolate(method='ffill', axis=1),
    test_df.ffill(axis=0),
)
```

Is this the desired behavior?

```
In [2]: pandas.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 15.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.0
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3.1
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: 1.3.5
patsy: 0.4.0
dateutil: 2.5.2
pytz: 2016.3
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5
matplotlib: 1.4.3
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.7.3
boto: 2.39.0
```
