BUG: drop_duplicates() throws exception if DF has duplicate column names

[sjachim]

Code Sample, a copy-pastable example if possible

# Your code here
df=pd.DataFrame([[1,2],[3,4]], columns=list('aa')) . # NOTICE TWO COLUMNS EACH CALLED 'a' 
df.drop_duplicates()

Problem description

May be related to 10161

Above code blows up with exception:

[...]
/opt/virtualenvs/luigi/local/lib/python2.7/dist-packages/pandas/core/frame.pyc in f(vals)
3095 labels, shape = algos.factorize(vals,
3096 size_hint=min(len(self),
-> 3097 _SIZE_HINT_LIMIT))
3098 return labels.astype('i8', copy=False), len(shape)
3099

/opt/virtualenvs/luigi/local/lib/python2.7/dist-packages/pandas/core/algorithms.pyc in factorize(values, sort, order, na_sentinel, size_hint)
183 table = hash_klass(size_hint or len(vals))
184 uniques = vec_klass()
--> 185 labels = table.get_labels(vals, uniques, 0, na_sentinel, True)
186
187 labels = com._ensure_platform_int(labels)

pandas/hashtable.pyx in pandas.hashtable.Int64HashTable.get_labels (pandas/hashtable.c:7941)()

ValueError: Buffer has wrong number of dimensions (expected 1, got 2)

Expected Output

I was excepting simple dataframe output as there are no duplicate rows there.

a a
0 1 2
1 3 4

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.32-15.41.amzn1.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: None
pip: 9.0.1
setuptools: 36.4.0
Cython: None
numpy: 1.11.0
scipy: 0.17.1
statsmodels: 0.8.0
xarray: None
IPython: 5.4.1
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
httplib2: None
apiclient: None
sqlalchemy: 1.1.14
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.7.3
boto: 2.48.0
pandas_datareader: None

[jreback]

you have an older version of pandas (current is 0.20.3), 0.21.0 shortly. But this is an issue on master as well.

duplicate support for columns is limited, but this should work. pull-requests to fix welcome.