Description
Code Sample, a copy-pastable example if possible
# Starting the interpreter with `python -Werror::DeprecationWarning:pandas.core.dtypes.cast`
>>> import numpy as np
>>> import pandas as pd
>>> pd.Series("2018-03-08", index=pd.RangeIndex(stop=1), dtype="datetime64[ns]")
0 2018-03-08
dtype: datetime64[ns]
>>> pd.Series(np.datetime64("2018-03-08"), index=pd.RangeIndex(stop=1), dtype="datetime64[ns]")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "$VIRTUAL_ENV/local/lib/python2.7/site-packages/pandas/core/series.py", line 275, in __init__
raise_cast_failure=True)
File "$VIRTUAL_ENV/local/lib/python2.7/site-packages/pandas/core/series.py", line 4132, in _sanitize_array
subarr = _try_cast(data, False)
File "$VIRTUAL_ENV/local/lib/python2.7/site-packages/pandas/core/series.py", line 4044, in _try_cast
subarr = maybe_cast_to_datetime(arr, dtype)
File "$VIRTUAL_ENV/local/lib/python2.7/site-packages/pandas/core/dtypes/cast.py", line 1021, in maybe_cast_to_datetime
if value == iNaT or isna(value):
DeprecationWarning: elementwise == comparison failed; this will raise an error in the future.Problem description
The above code triggers a numpy DeprecationWarning when using a numpy scalar value as input to the series.
Expected Output
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.60-linuxkit-aufs
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.4
pytest: None
pip: 10.0.1
setuptools: 40.0.0
Cython: None
numpy: 1.14.5
scipy: None
pyarrow: 0.10.0
xarray: None
IPython: 5.7.0
sphinx: 1.6.7
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: 1.2.9
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None