setting column value with .loc based on a condition
#### Code Sample, a copy-pastable example if possible

```python
>>> import pandas as pd
>>> from shapely.geometry import LineString

>>> line_1 = LineString(((0,0), (1,1)))
>>> line_2 = LineString(((3,3), (5,5)))

>>> df = pd.DataFrame(data={"line_id":"999", "geometry":[line_1]})
>>> print("inital dataframe:\n%s\n" % df)

# Isolate column value
>>> condition = df["line_id"] == "999"
>>> print("location of condition:\n%s\n" % df.loc[condition, "geometry"])

# [Fail] Set geometry value by the location of condition
>>> try:
>>>     df.loc[condition,  "geometry"] = line_2
>>> except ValueError as e:
>>>     print(e, "\n")

# [Pass] Set geometry value by index location
>>> df.loc[0, "geometry"] = line_2
>>> print(df)

```
#### Problem description

*Migrated from geopandas/geopandas#831*.

The flexibility to set values based on a certain condition when index location is unknown is critical for some spatial workflows. This seems to be unexpected behavior in `pandas` (though I may be wrong). Also, as @martinfleis [suggested](https://github.com/geopandas/geopandas/issues/831#issuecomment-540169829), it may be related to `np.array(LineString(((0,0), (1,1))))` returning an array of coordinates.


#### Expected Output

*see problem description*

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.0.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.1
numpy            : 1.17.2
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 19.2.3
setuptools       : 41.4.0
Cython           : 0.29.13
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.8.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
</details>
