BUG: infer_dtype is incorrect for numpy arrays containing strings and NaN
#### Code Sample, a copy-pastable example if possible
On master:
```python
In [3]: values = ['a', 'b', np.nan]

In [4]: lib.infer_dtype(np.array(values))
Out[4]: 'string'
```

This returns 'mixed' if the list itself or a Series is passed:
```python
In [5]: lib.infer_dtype(values)
Out[5]: 'mixed'

In [6]: lib.infer_dtype(pd.Series(values))
Out[6]: 'mixed'
```

This is a problem because it impacts any function that uses hash tables, as it causes NaN to be returned as a string (notice the quotes around `'nan'` below):
```python 
In [7]: pd.unique(np.array(values))
Out[7]: array(['a', 'b', 'nan'], dtype=object)
```

Again, this doesn't happen if the list itself or a Series is passed:
```python
In [8]: pd.unique(values)
Out[8]: array(['a', 'b', nan], dtype=object)

In [9]: pd.unique(pd.Series(values))
Out[9]: array(['a', 'b', nan], dtype=object)
```

Which appears to be caused by `infer_dtype` returning 'string' instead of 'mixed' here:
https://github.com/pandas-dev/pandas/blob/488db6f9a0f19e1d18559e6c2056e9545fe14704/pandas/core/algorithms.py#L207-L211

#### Problem description
`infer_dtype` incorrectly returns 'string', causing NaN to get converted to a string by functions that use hash tables.

#### Expected Output
`infer_dtype` to return 'mixed'.

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

<details>

INSTALLED VERSIONS
------------------
commit: 488db6f9a0f19e1d18559e6c2056e9545fe14704
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0.dev0+74.g488db6f
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.1
scipy: 0.19.1
pyarrow: 0.6.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: 0.4.0
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: None
html5lib: 0.999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: 0.1.0
pandas_gbq: None
pandas_datareader: None

</details>
