COMPAT: datetime.date comparisons with datetime64[ns]

This should probably work

In [16]: df = pd.DataFrame({'A':[pd.Timestamp('20130101'), np.nan]})

In [17]: df
Out[17]: 
           A
0 2013-01-01
1        NaT

In [18]: pd.Timestamp('20130101').to_pydatetime()>=df.A
Out[18]: 
0     True
1    False
Name: A, dtype: bool

In [20]: pd.Timestamp('20130101').to_pydatetime().date()>=df.A
ValueError: cannot set a Timestamp with a non-timestamp

[jreback]

These just need wrapping

In [7]: pd.Timestamp(datetime.date(2017, 10, 24)) < pd.Timestamp('2017-10-24 17:02')
Out[7]: True

[akrherz]

I think a MCVE for @liuli1735 's post is this

import pandas as pd
df = pd.DataFrame({'dates': pd.date_range('2000-01-01', '2010-12-31')})
date = df['dates'].unique()[0]
print(df.loc[df['dates'] == date])

Result with 0.20.3-py27_1 on conda-forge (linux64 python2.7)

$ python mcve.py 
       dates
0 2000-01-01

Result with 0.21.0-py27_0 on conda-forge (linux64 python2.7)

$ python mcve.py 
Traceback (most recent call last):
  File "mcve.py", line 5, in <module>
    print(df.loc[df['dates'] == date])
  File "/opt/miniconda2/lib/python2.7/site-packages/pandas/core/ops.py", line 879, in wrapper
    res = na_op(values, other)
  File "/opt/miniconda2/lib/python2.7/site-packages/pandas/core/ops.py", line 808, in na_op
    y = libindex.convert_scalar(x, _values_from_object(y))
  File "pandas/_libs/index.pyx", line 494, in pandas._libs.index.convert_scalar
  File "pandas/_libs/index.pyx", line 509, in pandas._libs.index.convert_scalar
ValueError: cannot set a Timestamp with a non-timestamp