BUG: Incorrect Parsing During Selecting Data of a Complex Object
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import networkx as nx

# Create a graph object with 2 edges and 3 nodes
dg1 = nx.DiGraph()
dg1.add_edge(1,2)
dg1.add_edge(3,2)

# Create a graph object with 2 edges and 3 nodes
dg2 = nx.DiGraph()
dg2.add_edge(1,2)
dg2.add_edge('a',2)

l = [dg1, dg2]

# Print their type name
print(list(map(type, l)))

# Create a df to store the graphs
df=pd.DataFrame({'a': [0, 1]})
df['dg'] = l

# Mask selecting, here, got incorrect series object (actually it's the nodes of the graph)
print(type(df['dg'][df['a']==1]))
print(type(df['dg'].loc[df['a']==1]))

# Non-mask selecting, here, got correct graph object
print(type(df['dg'][1]))
print(type(df['dg'].values[1]))
print(type(df['dg'].loc[1]))
```

#### Problem description

Mask selecting got the incorrect objects.

Environment:
platform : win-64
user-agent : conda/4.6.1 requests/2.18.4 CPython/3.6.5 Windows/10 Windows/10.0.16299
pandas                    0.24.1           py36ha925a31_0
networkx                  2.2                      py36_1

#### Expected Output
Mask selecting and non-mask selecting should return the same objects as the originally stored ones.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 45 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.1
pytest: None
pip: 19.0.3
setuptools: 40.8.0
Cython: None
numpy: 1.15.4
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.3.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.2
openpyxl: 2.6.0
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.3.1
bs4: 4.7.1
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
