title: Pandas comparing dataframe with series containing datetime
body: <p>I'm trying to compare a Dataframe with a Series to check if one of the rows in the df is equal to the series, e.g.</p>
  
  <pre><code>import pandas as pd
  import datetime as dt
  
  d = pd.DataFrame([[1, dt.datetime(1990,12,10)],
                    [2, dt.datetime(1990,12,11)]])
  s = d.loc[0].copy()
  
  print(d == s)  # or d.gt(s) which should do the same
  </code></pre>
  
  <p>This breaks with the following error</p>
  
  <blockquote>
    <p>TypeError: int() argument must be a string, a bytes-like object or a number, not 'Timestamp'</p>
  </blockquote>
  
  <p>Comparing the <code>values</code> yields the expected results:</p>
  
  <pre><code>d.values == s.values
  array([[ True,  True],
         [False, False]], dtype=bool)
  </code></pre>
  
  <p>Also this error isn't raised using strings:</p>
  
  <pre><code>d = pd.DataFrame([[1, "a"], [2, "b"]])
  
  s = d.loc[1].copy()
  
  print(s == d)
  #       0      1
  #0   True   True
  #1  False  False
  </code></pre>
  
  <p>Is this a bug in pandas or am I doing something wrong?</p>
  
  <p>EDIT:</p>
  
  <p>I'm using python 3.6 with pandas 0.20.3</p>
  
  <p>I opened an issue on pandas github:
  <a href="https://github.com/pandas-dev/pandas/issues/17411" rel="nofollow noreferrer">17411</a></p>