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importpandasaspddt=pd.Series([pd.Timestamp('2017-01-05 10:20:27.569000'), pd.NaT])
print("\nBefore")
print(dt)
# Should not modify the objectranks=dt.rank()
print("\nAfter")
print(dt)
Before
0 2017-01-05 10:20:27.569
1 NaT
dtype: datetime64[ns]
After
0 2017-01-05 10:20:27.569000000
1 2262-04-11 23:47:16.854775807
dtype: datetime64[ns]
Problem description
The rank() method replaces NaT with a concrete date value in the object.
Expected Output
No change in the object.
Output of pd.show_versions()
/Users/naure/Library/Python/3.6/lib/python/site-packages/xarray/core/formatting.py:16: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version.
from pandas.tslib import OutOfBoundsDatetime
Code Sample
Problem description
The rank() method replaces NaT with a concrete date value in the object.
Expected Output
No change in the object.
Output of
pd.show_versions()
/Users/naure/Library/Python/3.6/lib/python/site-packages/xarray/core/formatting.py:16: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version.
from pandas.tslib import OutOfBoundsDatetime
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.20.1
pytest: None
pip: 9.0.1
setuptools: 36.0.1
Cython: None
numpy: 1.13.1
scipy: 0.19.0
xarray: 0.9.5
IPython: 6.1.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.0
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
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