Make pd.Series(index=values) equivalent to pd.Series(index=pd.Index(values))?

Code Sample, a copy-pastable example if possible

In [2]: d = {(0, 1) : 2, (3, 4) : 5}

In [3]: pd.Index(d)
Out[3]: Index([(0, 1), (3, 4)], dtype='object')

In [4]: pd.Index(list(d))
Out[4]: 
MultiIndex(levels=[[0, 3], [1, 4]],
           labels=[[0, 1], [0, 1]])

In [5]: pd.Series(d).index
Out[5]: 
MultiIndex(levels=[[0, 3], [1, 4]],
           labels=[[0, 1], [0, 1]])

In [6]: pd.Series(index=list(d)).index
Out[6]: Index([(0, 1), (3, 4)], dtype='object')

Problem description

I guess Out[3]: and Out[6]: are wrong.

Expected Output

Out[4]:

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None python: 3.5.3.final.0 python-bits: 64 OS: Linux OS-release: 4.9.0-4-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8

pandas: 0.22.0.dev0+202.g97bd66ea8 pytest: 3.0.6 pip: 9.0.1 setuptools: 33.1.1 Cython: 0.25.2 numpy: 1.12.1 scipy: 0.18.1 pyarrow: None xarray: None IPython: 5.2.2 sphinx: None patsy: 0.4.1+dev dateutil: 2.6.0 pytz: 2016.10 blosc: None bottleneck: 1.2.0 tables: 3.3.0 numexpr: 2.6.1 feather: 0.3.1 matplotlib: 2.0.0 openpyxl: 2.3.0 xlrd: 1.0.0 xlwt: 1.2.0 xlsxwriter: None lxml: 3.7.1 bs4: 4.5.3 html5lib: 0.999999999 sqlalchemy: 1.0.15 pymysql: None psycopg2: None jinja2: 2.8 s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: None

[jreback]

[2] is invalid but prob not checked

these are not hashable sub elements

absolutely we do not want to add complexity like this

[jreback]

suppress _ensure_index, which becomes redundant (since it seems to me it isn’t catching any other case)

the original intent of _ensure_index was I think to infer whether things should be an Index or a MultiIndex. If you can remove code great.