Merge on key idenfitied by column index is not possible
#### Code Sample

```python
>>> import pandas
>>> a = pandas.DataFrame([[1,2,3], [4,5,6], [7, 8, 9]], columns=['a', 'b', 'a'])
>>> b = pandas.DataFrame({'a': [1,1,1], 'c': [10,11,12]})
>>> a
   a  b  a
0  1  2  3
1  4  5  6
2  7  8  9
>>> b
   a   c
0  1  10
1  1  11
2  1  12
>>> b.merge(a, left_on=0, right_on=0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/mitar/.virtualenv/test/lib/python3.6/site-packages/pandas/core/frame.py", line 6929, in merge
    copy=copy, indicator=indicator, validate=validate)
  File "/home/mitar/.virtualenv/test/lib/python3.6/site-packages/pandas/core/reshape/merge.py", line 46, in merge
    validate=validate)
  File "/home/mitar/.virtualenv/test/lib/python3.6/site-packages/pandas/core/reshape/merge.py", line 534, in __init__
    self.join_names) = self._get_merge_keys()
  File "/home/mitar/.virtualenv/test/lib/python3.6/site-packages/pandas/core/reshape/merge.py", line 875, in _get_merge_keys
    right._get_label_or_level_values(rk))
  File "/home/mitar/.virtualenv/test/lib/python3.6/site-packages/pandas/core/generic.py", line 1741, in _get_label_or_level_values
    raise KeyError(key)
KeyError: 0
```

#### Problem description

If column names are not unique (which happens to us much more often than one would hope for, for example, when reading multiple CSV files and horizontally concatenating them together) merge operation cannot operate on them. If you try, you get `ValueError: The column label 'a' is not unique.` exception. Which is understandable, because it is not possible to know on which column really you want to do the merge.

But there is also no other way currently. You cannot merge by specifying the index of the column you want to do join on. I would suggest such an option/argument should be added.

#### Expected Output

```
   a   c  b  a
0  1  10  2  3
1  1  11  2  3
2  1  12  2  3
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 4.18.0-20-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.25.0.dev0+610.gd2beaf3c8
pytest: None
pip: 18.1
setuptools: 40.7.1
Cython: 0.29.7
numpy: 1.15.4
scipy: 1.2.0
pyarrow: 0.13.0
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.5
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>
