Possible inconsistency between creation of Series and DataFrame with list of dicts
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd


# skip block when no sklean is installed

# I simply show where the list of dicts come from:
from sklearn.model_selection import ParameterGrid
par_grid = ParameterGrid({"x": [0,1,2,3]})
lod = list(par_grid)  
# Output:
# [{'x': 0}, {'x': 1}, {'x': 2}, {'x': 3}]

# end block

lod = [{'x': 0}, {'x': 1}, {'x': 2}, {'x': 3}]

pd.DataFrame(lod)

#Output:
#     x
# 0  0
# 1  1
# 2  2
# 3  3

pd.Series(lod)

# Output:
# 0    {'x': 0}
# 1    {'x': 1}
# 2    {'x': 2}
# 3    {'x': 3}
# dtype: object

```
#### Problem description

I am not sure whether this is actually an issue or wanted behaviour. But I expected for the two cases (DataFrame and Series) a similar output as below: 

#### Expected Output

```python
pd.Series([e["x"] for e in lod], name="x")
#or:
pd.DataFrame(lod).iloc[:, 0]

# Output:
# 0    0
# 1    1
# 2    2
# 3    3
# Name: x, dtype: int64

```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.0-43-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.0
pytest: None
pip: 10.0.1
setuptools: 39.2.0
Cython: None
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: None
dateutil: 2.7.2
pytz: 2018.3
blosc: None
bottleneck: None
tables: 3.4.3
numexpr: 2.6.4
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
