DataFrameGroupBy.ffill with Duplicate Column Labels ValueError
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np


df1 = pd.DataFrame({'field1': [1, 2, 3, 4],
                   'field2': [1, 2, 3, 4],
                   'field3': [1, 2, 3, 4]
                   })
df2 = pd.DataFrame({'field1': [1, 2, np.nan, 4],
                   })

same_col = pd.concat([df1, df2], axis=1)

print(same_col)
#    field1  field2  field3  field1
# 0       1       1       1     1.0
# 1       2       2       2     2.0
# 2       3       3       3     NaN
# 3       4       4       4     4.0


print(same_col.ffill())
#    field1  field2  field3  field1
# 0       1       1       1     1.0
# 1       2       2       2     2.0
# 2       3       3       3     2.0
# 3       4       4       4     4.0

for k, v in same_col.groupby(by=['field2']):
    print(v.ffill())
    #    field1  field2  field3  field1
    # 0       1       1       1     1.0
    #    field1  field2  field3  field1
    # 1       2       2       2     2.0
    #    field1  field2  field3  field1
    # 2       3       3       3     NaN
    #    field1  field2  field3  field1
    # 3       4       4       4     4.0

same_col.groupby(by=['field2']).ffill()
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)

```

#### Problem description
A _DataFrameGroupBy.ffill_ with 2 or more column with the same name produce an error:
`ValueError: Buffer has wrong number of dimensions (expected 1, got 2)`
Pandas 0.22.0 did not have this bud. It seems that it was introduced recently. Or if this is an expected behaviour, it must be consistent with the behaviour of a _DataFrame.ffill_ with 2 or more column with the same name and have a meaningful error.

#### Expected Output

```
#    field1  field2  field3  field1
# 0       1       1       1     1.0
# 1       2       2       2     2.0
# 2       3       3       3     NaN
# 3       4       4       4     4.0
```

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: en_GB.UTF-8
pandas: 0.24.1
pytest: None
pip: 10.0.1
setuptools: 39.1.0
Cython: None
numpy: 1.16.2
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
