df.loc modifies datetime columns
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
>>> df = pd.DataFrame.from_dict({"date": [1485264372711, 1485265925110, 1540215845888, 1540282121025]})
>>> df["date_dt"] = pd.to_datetime(df["date"], unit='ms', cache=True)
>>> df
            date                 date_dt
0  1485264372711 2017-01-24 13:26:12.711
1  1485265925110 2017-01-24 13:52:05.110
2  1540215845888 2018-10-22 13:44:05.888
3  1540282121025 2018-10-23 08:08:41.025
>>> df.loc[:, "date_dt_cp"] = df.loc[:, "date_dt"]
>>> df
            date                 date_dt              date_dt_cp
0  1485264372711 2017-01-24 13:26:12.711 2017-01-24 13:26:12.711
1  1485265925110 2017-01-24 13:52:05.110 2017-01-24 13:52:05.110
2  1540215845888 2018-10-22 13:44:05.888 2018-10-22 13:44:05.888
3  1540282121025 2018-10-23 08:08:41.025 2018-10-23 08:08:41.025
>>> df.loc[[2,3], "date_dt_cp"] = df.loc[[2,3], "date_dt"]
>>> df
            date                 date_dt                    date_dt_cp
0  1485264372711 2017-01-24 13:26:12.711 2017-01-24 13:26:12.711000064
1  1485265925110 2017-01-24 13:52:05.110 2017-01-24 13:52:05.110000128
2  1540215845888 2018-10-22 13:44:05.888 2018-10-22 13:44:05.888000000
3  1540282121025 2018-10-23 08:08:41.025 2018-10-23 08:08:41.024999936
```
#### Problem description

Using `.loc[]` on datetime columns to assign values modifies the dates.
When `.loc[]` is used on all the lines (`df.loc[:, "date_dt_cp"] = df.loc[:, "date_dt"]`) the dates are unchanged
```python
>>> df
            date                 date_dt              date_dt_cp
0  1485264372711 2017-01-24 13:26:12.711 2017-01-24 13:26:12.711
1  1485265925110 2017-01-24 13:52:05.110 2017-01-24 13:52:05.110
2  1540215845888 2018-10-22 13:44:05.888 2018-10-22 13:44:05.888
3  1540282121025 2018-10-23 08:08:41.025 2018-10-23 08:08:41.025
```

but when selecting only a subset of lines (`df.loc[[2,3], "date_dt_cp"] = df.loc[[2,3], "date_dt"]`), the values of the dates are changed:
```python
>>> df
            date                 date_dt                    date_dt_cp
0  1485264372711 2017-01-24 13:26:12.711 2017-01-24 13:26:12.711000064
1  1485265925110 2017-01-24 13:52:05.110 2017-01-24 13:52:05.110000128
2  1540215845888 2018-10-22 13:44:05.888 2018-10-22 13:44:05.888000000
3  1540282121025 2018-10-23 08:08:41.025 2018-10-23 08:08:41.024999936
```

#### Expected Output
The last assignment in the example above shouldn't update the values:
```python
            date                 date_dt              date_dt_cp
0  1485264372711 2017-01-24 13:26:12.711 2017-01-24 13:26:12.711
1  1485265925110 2017-01-24 13:52:05.110 2017-01-24 13:52:05.110
2  1540215845888 2018-10-22 13:44:05.888 2018-10-22 13:44:05.888
3  1540282121025 2018-10-23 08:08:41.025 2018-10-23 08:08:41.025
```
#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : fr_FR.UTF-8
LOCALE           : fr_FR.UTF-8

pandas           : 0.25.1
numpy            : 1.17.2
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.1.1
setuptools       : 41.0.1
Cython           : 0.29.10
pytest           : 3.7.4
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.3 (dt dec pq3 ext lo64)
jinja2           : 2.10.1
IPython          : 7.3.0
pandas_datareader: None
bs4              : None
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.0.0
numexpr          : 2.7.0
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.3.0
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : 1.3.0
xlsxwriter       : None
</details>
