Code Sample, a copy-pastable example

# Your code here
df = pd.DataFrame([[pd.Timestamp(2017,12,17), pd.Timestamp(2017,12,18)], [pd.Timestamp(2017,12,31), pd.NaT]])

In [7]: df
Out[7]:
           0          1
0 2017-12-17 2017-12-18
1 2017-12-31        NaT

In [8]: df < pd.Timestamp(2017,1,1)
Out[8]:
       0      1
0  False  False
1  False   True

In [9]: df[1] < pd.Timestamp(2017,1,1)
Out[9]:
0    False
1    False

Problem description

When comparing a dataframe of dtype Timestamp to a scalar value (Timestamp or datetime), the result to NaT is always True no matter what operator is used(==, <, >, ...).

But it is not the case when compares a series of Timestamps.

Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.2.final.0 python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 70 Stepping 1, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: None.None pandas: 0.21.1 pytest: 3.0.5 pip: 9.0.1 setuptools: 27.2.0 Cython: 0.25.2 numpy: 1.13.3 scipy: 0.18.1 pyarrow: None xarray: 0.9.6 IPython: 6.1.0 sphinx: 1.5.1 patsy: 0.4.1 dateutil: 2.6.1 pytz: 2017.3 blosc: None bottleneck: 1.2.0 tables: 3.4.2 numexpr: 2.6.1 feather: None matplotlib: 2.1.0 openpyxl: 2.4.1 xlrd: 1.0.0 xlwt: 1.2.0 xlsxwriter: 0.9.6 lxml: 3.7.2 bs4: 4.5.3 html5lib: None sqlalchemy: 1.1.5 pymysql: None psycopg2: None jinja2: 2.9.4 s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: 0.5.0

Comment From: jreback

duplicate of #15697