Issue 1:
Hi all,

just figured out that the following code

pd.DataFrame({'x':None}, index=[0])

works in 0.18.1 but not 0.19.0, is that the expected behavior? Thanks!

Best,

Jie

Issue 2:
A small, complete example of the issue

# Your code here

import pandas as pd
pd.Dataframe(dict(a=None), index= [0])

In [3]: pd.DataFrame(dict(a=None),index=[0])
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-3-20b65f605ca3> in <module>()
----> 1 pd.DataFrame(dict(a=None),index=[0])

miniconda2/envs/readout2/lib/python2.7/site-packages/pandas/core/frame.pyc in __init__(self, data, index, columns, dtype, copy)
264 dtype=dtype, copy=copy)
265 elif isinstance(data, dict):
--> 266 mgr = self._init_dict(data, index, columns, dtype=dtype)
267 elif isinstance(data, ma.MaskedArray):
268 import numpy.ma.mrecords as mrecords

miniconda2/envs/readout2/lib/python2.7/site-packages/pandas/core/frame.pyc in _init_dict(self, data, index, columns, dtype)
400 arrays = [data[k] for k in keys]
401
--> 402 return _arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
403
404 def _init_ndarray(self, values, index, columns, dtype=None, copy=False):

miniconda2/envs/readout2/lib/python2.7/site-packages/pandas/core/frame.pyc in _arrays_to_mgr(arrays, arr_names, index, columns, dtype)
5382
5383 # don't force copy because getting jammed in an ndarray anyway
-> 5384 arrays = _homogenize(arrays, index, dtype)
5385
5386 # from BlockManager perspective

miniconda2/envs/readout2/lib/python2.7/site-packages/pandas/core/frame.pyc in _homogenize(data, index, dtype)
5693 v = lib.fast_multiget(v, oindex.values, default=NA)
5694 v = _sanitize_array(v, index, dtype=dtype, copy=False,
-> 5695 raise_cast_failure=False)
5696
5697 homogenized.append(v)

miniconda2/envs/readout2/lib/python2.7/site-packages/pandas/core/series.pyc in _sanitize_array(data, index, dtype, copy, raise_cast_failure)
2917
2918 # scalar like
-> 2919 if subarr.ndim == 0:
2920 if isinstance(data, list): # pragma: no cover
2921 subarr = np.array(data, dtype=object)

AttributeError: 'NoneType' object has no attribute 'ndim'

Expected Output

This previously worked with a sensible output in 0.18.1:

In [2]: pd.DataFrame(dict(a=None),index=[0])

Out[2]:

a

0 None

Output of pd.show_versions()

Working version:
## INSTALLED VERSIONS

commit: None

python: 2.7.12.final.0

python-bits: 64

OS: Linux

OS-release: 3.2.0-4-amd64

machine: x86_64

processor:

byteorder: little

LC_ALL: None

LANG: en_US.UTF-8

pandas: 0.18.1

nose: 1.3.7

pip: 8.1.2

setuptools: 27.2.0

Cython: 0.24

numpy: 1.11.2

scipy: 0.17.0

statsmodels: 0.6.1

xarray: None

IPython: 4.2.0

sphinx: 1.4.1

patsy: 0.4.1

dateutil: 2.5.3

pytz: 2016.7

blosc: None

bottleneck: 1.0.0

tables: 3.2.2

numexpr: 2.4.4

matplotlib: 1.5.1

openpyxl: 2.3.2

xlrd: 0.9.4

xlwt: 1.0.0

xlsxwriter: 0.8.5

lxml: 3.6.0

bs4: 4.3.2

html5lib: None

httplib2: None

apiclient: None

sqlalchemy: 1.0.12

pymysql: None

psycopg2: None

jinja2: 2.8

boto: 2.39.0

pandas_datareader: None

Broken version:

INSTALLED VERSIONS

commit: None

python: 2.7.12.final.0

python-bits: 64

OS: Linux

OS-release: 3.2.0-4-amd64

machine: x86_64

processor:

byteorder: little

LC_ALL: None

LANG: en_US.UTF-8

LOCALE: None.None

pandas: 0.19.0

nose: 1.3.7

pip: 8.1.2

setuptools: 27.2.0

Cython: 0.24

numpy: 1.11.2

scipy: 0.17.0

statsmodels: 0.6.1

xarray: None

IPython: 4.2.0

sphinx: 1.4.1

patsy: 0.4.1

dateutil: 2.5.3

pytz: 2016.7

blosc: None

bottleneck: 1.0.0

tables: 3.2.2

numexpr: 2.4.4

matplotlib: 1.5.1

openpyxl: 2.3.2

xlrd: 0.9.4

xlwt: 1.0.0

xlsxwriter: 0.8.5

lxml: 3.6.0

bs4: 4.3.2

html5lib: None

httplib2: None

apiclient: None

sqlalchemy: 1.0.12

pymysql: None

psycopg2: None

jinja2: 2.8

boto: 2.39.0

pandas_datareader: None