SparseDataFrame from_dict doesn't adhere to sparse input semantics
## Code Sample 

```python
from pandas import DataFrame, SparseDataFrame

list_of_sparse_semantics = [{0: 1, 4: 1, 22: 1, 1001: 2}, {0: 1, 3: 1}, {0: 1, 55: 1}]

df = DataFrame.from_dict(list_of_sparse_semantics)
sdf = SparseDataFrame.from_dict(list_of_sparse_semantics)
```

## Problem description

It may seem as if `SparseDataFrame` does not follow the sparse semantics that are followed by `DataFrame`'s `from_dict` method. It stuffs each dict as a single column/element, rather than treating its key-val tuples as sparse content for building the equivalent sparse row as `DataFrame` does.

## Expected Output

```
sdf.equals(df)
```
> True

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

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-130-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: 3.2.1
pip: 10.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.14.3
scipy: 0.19.1
xarray: None
IPython: 6.4.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.8.1
s3fs: None
pandas_gbq: None
pandas_datareader: None
```