unexpected numpy array returned when using .loc

[sunt05]

Code Sample, a copy-pastable example if possible

# Your code here
dt=pd.date_range('2012','2013',freq='d')
df_test=pd.DataFrame(index=dt)
df_test['x']=123
df_test.loc['2012 2','x']

Problem description

.loc operation above used to return a pd.Series but in v0.25.0 returns a numpy array.

Expected Output

output:

array([123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123,
       123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123,
       123, 123, 123])

Output of pd.show_versions()

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 : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 0.25.0
numpy : 1.17.0
pytz : 2019.1
dateutil : 2.8.0
pip : 19.1.1
setuptools : 41.0.1
Cython : 0.29.12
pytest : 5.0.1
hypothesis : None
sphinx : 2.1.2
blosc : None
feather : None
xlsxwriter : 1.1.8
lxml.etree : 4.3.4
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2 : 2.10.1
IPython : 7.6.1
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.3.4
matplotlib : 3.1.0
numexpr : 2.6.9
odfpy : None
openpyxl : 2.6.2
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.0
sqlalchemy : 1.3.5
tables : 3.5.2
xarray : 0.12.1
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.1.8

[TomAugspurger]

Duplicate of #27516 (I just changed the title to be more accurate).

Going to fix for 0.25.1. In the meantime you can do two indexing calls, df_test.loc['2012-02']['x'].