Inconsistent .values for tz-aware columns · Issue #14052 · pandas-dev/pandas (original) (raw)

When getting the values of a dataframe with multiple columns with a single type datetime64[ns,UTC], it returns a numpy array with dtype=object instead of dtype=datetime64[ns,UTC].
When returning a single column with dtype=datetime64[ns,UTC] or returning a multiple columns of dtype=datetime64[ns] (ie without tz), it works.
Looking at the code, it appears that SingleBlockManager.is_mixed_type returns False in the first case (datetime64[ns,UTC]) and True in the two other cases (single datetime64[ns,UTC] or multiple datetime64[ns]).

Code Sample, a copy-pastable example if possible

import pandas

idx = pandas.date_range("2010", "2011", tz="UTC")
df = pandas.DataFrame(index=idx)
df["A"] = idx
df["B"] = idx
print(df[["B"]].values.dtype)
print(df[["A", "B"]].values.dtype)

Actual Output

datetime64[ns, UTC]
object

Expected Output

datetime64[ns, UTC]
datetime64[ns, UTC]

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.5.2.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 23.0.0
Cython: None
numpy: 1.11.0
scipy: 0.17.1
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext)
jinja2: 2.8
boto: None
pandas_datareader: None